Subjects -> COMPUTER SCIENCE (Total: 2313 journals)
    - ANIMATION AND SIMULATION (33 journals)
    - ARTIFICIAL INTELLIGENCE (133 journals)
    - AUTOMATION AND ROBOTICS (116 journals)
    - CLOUD COMPUTING AND NETWORKS (75 journals)
    - COMPUTER ARCHITECTURE (11 journals)
    - COMPUTER ENGINEERING (12 journals)
    - COMPUTER GAMES (23 journals)
    - COMPUTER PROGRAMMING (25 journals)
    - COMPUTER SCIENCE (1305 journals)
    - COMPUTER SECURITY (59 journals)
    - DATA BASE MANAGEMENT (21 journals)
    - DATA MINING (50 journals)
    - E-BUSINESS (21 journals)
    - E-LEARNING (30 journals)
    - ELECTRONIC DATA PROCESSING (23 journals)
    - IMAGE AND VIDEO PROCESSING (42 journals)
    - INFORMATION SYSTEMS (109 journals)
    - INTERNET (111 journals)
    - SOCIAL WEB (61 journals)
    - SOFTWARE (43 journals)
    - THEORY OF COMPUTING (10 journals)

AUTOMATION AND ROBOTICS (116 journals)                     

Showing 1 - 101 of 101 Journals sorted alphabetically
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 10)
ACM Transactions on Human-Robot Interaction     Open Access   (Followers: 4)
Advanced Robotics     Hybrid Journal   (Followers: 29)
Advances in Computed Tomography     Open Access   (Followers: 2)
Advances in Image and Video Processing     Open Access   (Followers: 27)
Advances in Robotics & Automation     Open Access   (Followers: 12)
Artificial Life and Robotics     Hybrid Journal   (Followers: 17)
Augmented Human Research     Hybrid Journal  
Automated Software Engineering     Hybrid Journal   (Followers: 9)
Automatic Control and Information Sciences     Open Access   (Followers: 4)
Automation and Remote Control     Hybrid Journal   (Followers: 6)
Autonomous Agents and Multi-Agent Systems     Hybrid Journal   (Followers: 9)
Autonomous Robots     Hybrid Journal   (Followers: 11)
Biocybernetics and Biological Engineering     Full-text available via subscription   (Followers: 4)
Biological Cybernetics     Hybrid Journal   (Followers: 10)
Biomimetic Intelligence and Robotics     Open Access  
Cognitive Robotics     Open Access   (Followers: 4)
Computational Intelligence and Neuroscience     Open Access   (Followers: 18)
Computer-Aided Design     Hybrid Journal   (Followers: 9)
Construction Robotics     Hybrid Journal   (Followers: 5)
Current Robotics Reports     Hybrid Journal   (Followers: 4)
Cybernetics & Human Knowing     Full-text available via subscription   (Followers: 3)
Cybernetics and Systems Analysis     Hybrid Journal  
Cybernetics and Systems: An International Journal     Hybrid Journal   (Followers: 1)
Design Automation for Embedded Systems     Hybrid Journal   (Followers: 4)
Digital Zone : Jurnal Teknologi Informasi Dan Komunikasi     Open Access  
Drone Systems and Applications     Open Access   (Followers: 1)
Electrical Engineering and Automation     Open Access   (Followers: 9)
Facta Universitatis, Series : Automatic Control and Robotics     Open Access   (Followers: 1)
Foundations and Trends® in Robotics     Full-text available via subscription   (Followers: 4)
GIScience & Remote Sensing     Open Access   (Followers: 58)
IAES International Journal of Robotics and Automation     Open Access   (Followers: 5)
IEEE Robotics & Automation Magazine     Full-text available via subscription   (Followers: 69)
IEEE Robotics and Automation Letters     Hybrid Journal   (Followers: 9)
IEEE Transactions on Affective Computing     Hybrid Journal   (Followers: 23)
IEEE Transactions on Audio, Speech, and Language Processing     Hybrid Journal   (Followers: 17)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 70)
IEEE Transactions on Cybernetics     Hybrid Journal   (Followers: 16)
IEEE Transactions on Intelligent Vehicles     Hybrid Journal   (Followers: 2)
IEEE Transactions on Medical Robotics and Bionics     Hybrid Journal   (Followers: 5)
IEEE Transactions on Neural Networks and Learning Systems     Hybrid Journal   (Followers: 57)
IEEE Transactions on Robotics     Hybrid Journal   (Followers: 71)
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews     Hybrid Journal   (Followers: 16)
IET Cyber-systems and Robotics     Open Access   (Followers: 2)
IET Systems Biology     Open Access   (Followers: 1)
Industrial Robot An International Journal     Hybrid Journal   (Followers: 2)
Intelligent Control and Automation     Open Access   (Followers: 6)
Intelligent Service Robotics     Hybrid Journal   (Followers: 2)
International Journal of Adaptive, Resilient and Autonomic Systems     Full-text available via subscription   (Followers: 3)
International Journal of Advanced Pervasive and Ubiquitous Computing     Full-text available via subscription   (Followers: 4)
International Journal of Advanced Robotic Systems     Full-text available via subscription   (Followers: 1)
International Journal of Agent Technologies and Systems     Full-text available via subscription   (Followers: 4)
International Journal of Ambient Computing and Intelligence     Full-text available via subscription   (Followers: 3)
International Journal of Applied Evolutionary Computation     Full-text available via subscription   (Followers: 3)
International Journal of Artificial Life Research     Full-text available via subscription  
International Journal of Automation and Control     Hybrid Journal   (Followers: 11)
International Journal of Automation and Control Engineering     Open Access   (Followers: 5)
International Journal of Automation and Logistics     Hybrid Journal   (Followers: 4)
International Journal of Automation and Smart Technology     Open Access   (Followers: 3)
International Journal of Bioinformatics Research and Applications     Hybrid Journal   (Followers: 14)
International Journal of Biomechatronics and Biomedical Robotics     Hybrid Journal   (Followers: 2)
International Journal of Humanoid Robotics     Hybrid Journal   (Followers: 6)
International Journal of Imaging & Robotics     Full-text available via subscription   (Followers: 3)
International Journal of Intelligent Information Technologies     Full-text available via subscription   (Followers: 1)
International Journal of Intelligent Machines and Robotics     Hybrid Journal   (Followers: 3)
International Journal of Intelligent Mechatronics and Robotics     Full-text available via subscription   (Followers: 5)
International Journal of Intelligent Robotics and Applications     Hybrid Journal  
International Journal of Intelligent Systems Design and Computing     Hybrid Journal   (Followers: 2)
International Journal of Intelligent Unmanned Systems     Hybrid Journal   (Followers: 3)
International Journal of Machine Consciousness     Hybrid Journal   (Followers: 7)
International Journal of Machine Learning and Cybernetics     Hybrid Journal   (Followers: 31)
International Journal of Mechanisms and Robotic Systems     Hybrid Journal   (Followers: 2)
International Journal of Mechatronics and Automation     Hybrid Journal   (Followers: 5)
International Journal of Robotics and Automation     Full-text available via subscription   (Followers: 8)
International Journal of Robotics and Control     Open Access   (Followers: 3)
International Journal of Robotics Applications and Technologies     Full-text available via subscription   (Followers: 1)
International Journal of Robotics Research     Hybrid Journal   (Followers: 15)
International Journal of Space-Based and Situated Computing     Hybrid Journal   (Followers: 2)
International Journal of Synthetic Emotions     Full-text available via subscription  
International Journal of Tomography & Simulation     Full-text available via subscription   (Followers: 1)
Journal of Automation and Control     Open Access   (Followers: 9)
Journal of Computer Assisted Tomography     Hybrid Journal   (Followers: 2)
Journal of Control & Instrumentation     Full-text available via subscription   (Followers: 19)
Journal of Control, Automation and Electrical Systems     Hybrid Journal   (Followers: 11)
Journal of Intelligent and Robotic Systems     Hybrid Journal   (Followers: 6)
Journal of Intelligent Learning Systems and Applications     Open Access   (Followers: 4)
Journal of Robotic Surgery     Hybrid Journal   (Followers: 3)
Jurnal Otomasi Kontrol dan Instrumentasi     Open Access  
Machine Translation     Hybrid Journal   (Followers: 12)
Proceedings of the ACM on Human-Computer Interaction     Hybrid Journal   (Followers: 2)
Results in Control and Optimization     Open Access   (Followers: 5)
Revista Iberoamericana de Automática e Informática Industrial RIAI     Open Access  
ROBOMECH Journal     Open Access   (Followers: 1)
Robotic Surgery : Research and Reviews     Open Access   (Followers: 1)
Robotica     Hybrid Journal   (Followers: 5)
Robotics and Autonomous Systems     Hybrid Journal   (Followers: 19)
Robotics and Biomimetics     Open Access   (Followers: 1)
Robotics and Computer-Integrated Manufacturing     Hybrid Journal   (Followers: 7)
Science Robotics     Full-text available via subscription   (Followers: 11)
Unmanned Systems     Hybrid Journal   (Followers: 4)
Wearable Technologies     Open Access   (Followers: 4)

           

Similar Journals
Journal Cover
International Journal of Robotics Research
Journal Prestige (SJR): 2.471
Citation Impact (citeScore): 6
Number of Followers: 15  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0278-3649 - ISSN (Online) 1741-3176
Published by Sage Publications Homepage  [1176 journals]
  • Machine learning for shipwreck segmentation from side scan sonar imagery:
           Dataset and benchmark

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      Authors: Advaith V. Sethuraman, Anja Sheppard, Onur Bagoren, Christopher Pinnow, Jamey Anderson, Timothy C. Havens, Katherine A. Skinner
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Open-source benchmark datasets have been a critical component for advancing machine learning for robot perception in terrestrial applications. Benchmark datasets enable the widespread development of state-of-the-art machine learning methods, which require large datasets for training, validation, and thorough comparison to competing approaches. Underwater environments impose several operational challenges that hinder efforts to collect large benchmark datasets for marine robot perception. Furthermore, a low abundance of targets of interest relative to the size of the search space leads to increased time and cost required to collect useful datasets for a specific task. As a result, there is limited availability of labeled benchmark datasets for underwater applications. We present the AI4Shipwrecks dataset, which consists of 28 distinct shipwrecks totaling 286 high-resolution labeled side scan sonar images to advance the state-of-the-art in autonomous sonar image understanding. We leverage the unique abundance of targets in Thunder Bay National Marine Sanctuary in Lake Huron, MI, to collect and compile a sonar imagery benchmark dataset through surveys with an autonomous underwater vehicle (AUV). We consulted with expert marine archaeologists for the labeling of robotically gathered data. We then leverage this dataset to perform benchmark experiments for comparison of state-of-the-art supervised segmentation methods, and we present insights on opportunities and open challenges for the field. The dataset and benchmarking tools will be released as an open-source benchmark dataset to spur innovation in machine learning for Great Lakes and ocean exploration. The dataset and accompanying software are available at https://umfieldrobotics.github.io/ai4shipwrecks/.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-07-21T07:42:42Z
      DOI: 10.1177/02783649241266853
       
  • Group-k consistent measurement set maximization via maximum clique over
           k-uniform hypergraphs for robust multi-robot map merging

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      Authors: Brendon Forsgren, Michael Kaess, Ram Vasudevan, Timothy W. McLain, Joshua G. Mangelson
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      This paper unifies the theory of consistent-set maximization for robust outlier detection in a simultaneous localization and mapping framework. We first describe the notion of pairwise consistency before discussing how a consistency graph can be formed by evaluating pairs of measurements for consistency. Finding the largest set of consistent measurements is transformed into an instance of the maximum clique problem and can be solved relatively quickly using existing maximum-clique solvers. We then generalize our algorithm to check consistency on a group-k basis by using a generalized notion of consistency and using generalized graphs. We also present modified maximum clique algorithms that function over generalized graphs to find the set of measurements that is internally group-k consistent. We address the exponential nature of group-k consistency and present methods that can substantially decrease the number of necessary checks performed when evaluating consistency. We extend our prior work to perform data association, and to multi-agent systems in both simulation and hardware, and provide a comparison with other state-of-the-art methods.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-07-02T09:25:27Z
      DOI: 10.1177/02783649241256970
       
  • Behavior-predefined adaptive control for heterogeneous continuum robots

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      Authors: Ning Tan, Peng Yu, Xin Wang, Kai Huang
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Continuum robots have great application value and broad prospects in various fields due to their dexterity and compliance. To fully exploit their advantages, it is crucial to develop an effective, accurate and robust control system for them. However, research on continuum robot control is still in its infancy and there are many problems remaining unsolved in this field. In particular, this paper focuses on the task-space behavior and the generic control of heterogeneous continuum robots. First, a controller is proposed to achieve the kinematic motion control and visual servoing of continuum robots with predefined task-space behavior. The predefined behavior is twofold: prescribed task-space error and predefined convergence time. Then, the proposed controller is integrated with a velocity-level kinematic mapping estimator to obtain a model-free control system, which is applicable to heterogeneous continuum robots. Furthermore, a re-adjustable performance function is proposed to ensure the effectiveness and robustness of the proposed control system in the presence of external disturbance. Finally, extensive simulations and experiments are performed based on heterogeneous continuum robots, including the cable-driven continuum robot, the parallel continuum robot, the concentric-tube robot, the flexible endoscope, and the pneumatic continuum robot. Our results demonstrate that the task-space error of heterogeneous continuum robots complies with the prescribed boundaries and converges to steady state in predefined time, which reveals the efficacy of the proposed control method.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-06-21T12:49:55Z
      DOI: 10.1177/02783649241259138
       
  • Robot control based on motor primitives: A comparison of two approaches

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      Authors: Moses C. Nah, Johannes Lachner, Neville Hogan
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Motor primitives are fundamental building blocks of a controller which enable dynamic robot behavior with minimal high-level intervention. By treating motor primitives as basic “modules,” different modules can be sequenced or superimposed to generate a rich repertoire of motor behavior. In robotics, two distinct approaches have been proposed: Dynamic Movement Primitives (DMPs) and Elementary Dynamic Actions (EDAs). While both approaches instantiate similar ideas, significant differences also exist. This paper attempts to clarify the distinction and provide a unifying view by delineating the similarities and differences between DMPs and EDAs. We provide nine robot control examples, including sequencing or superimposing movements, managing kinematic redundancy and singularity, control of both position and orientation of the robot’s end-effector, obstacle avoidance, and managing physical interaction. We show that the two approaches clearly diverge in their implementation. We also provide a real-robot demonstration to show how DMPs and EDAs can be combined to get the best of both approaches. With this detailed comparison, we enable researchers to make informed decisions to select the most suitable approach for specific robot tasks and applications.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-06-21T11:31:45Z
      DOI: 10.1177/02783649241258782
       
  • AstroSLAM: Autonomous monocular navigation in the vicinity of a celestial
           small body—Theory and experiments

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      Authors: Mehregan Dor, Travis Driver, Kenneth Getzandanner, Panagiotis Tsiotras
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      We propose AstroSLAM, a standalone vision-based solution for autonomous online navigation around an unknown celestial target small body. AstroSLAM is predicated on the formulation of the SLAM problem as an incrementally growing factor graph, facilitated by the use of the GTSAM library and the iSAM2 engine. By combining sensor fusion with orbital motion priors, we achieve improved performance over a baseline SLAM solution and outperform state-of-the-art methods predicated on pre-integrated inertial measurement unit factors. We incorporate orbital motion constraints into the factor graph by devising a novel relative dynamics—RelDyn—factor, which links the relative pose of the spacecraft to the problem of predicting trajectories stemming from the motion of the spacecraft in the vicinity of the small body. We demonstrate AstroSLAM’s performance and compare against the state-of-the-art methods using both real legacy mission imagery and trajectory data courtesy of NASA’s Planetary Data System, as well as real in-lab imagery data produced on a 3 degree-of-freedom spacecraft simulator test-bed.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-06-21T11:15:54Z
      DOI: 10.1177/02783649241234367
       
  • Optimal potential shaping on SE(3) via neural ordinary differential
           equations on Lie groups

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      Authors: Yannik P. Wotte, Federico Califano, Stefano Stramigioli
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      This work presents a novel approach for the optimization of dynamic systems on finite-dimensional Lie groups. We rephrase dynamic systems as so-called neural ordinary differential equations (neural ODEs), and formulate the optimization problem on Lie groups. A gradient descent optimization algorithm is presented to tackle the optimization numerically. Our algorithm is scalable, and applicable to any finite-dimensional Lie group, including matrix Lie groups. By representing the system at the Lie algebra level, we reduce the computational cost of the gradient computation. In an extensive example, optimal potential energy shaping for control of a rigid body is treated. The optimal control problem is phrased as an optimization of a neural ODE on the Lie group SE(3), and the controller is iteratively optimized. The final controller is validated on a state-regulation task.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-06-14T11:16:50Z
      DOI: 10.1177/02783649241256044
       
  • YUTO MMS: A comprehensive SLAM dataset for urban mobile mapping with
           tilted LiDAR and panoramic camera integration

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      Authors: Yiujia Zhang, SeyedMostafa Ahmadi, Jungwon Kang, Zahra Arjmandi, Gunho Sohn
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      The York University Teledyne Optech (YUTO) Mobile Mapping System (MMS) Dataset, encompassing four sequences totaling 20.1 km, was thoroughly assembled through two data collection expeditions on August 12, 2020, and June 21, 2019. Acquisitions were performed using a uniquely equipped vehicle, fortified with a panoramic camera, a tilted LiDAR, a Global Positioning System (GPS), and an Inertial Measurement Unit (IMU), journeying through two strategic locations: the York University Keele Campus in Toronto and the Teledyne Optech headquarters in City of Vaughan, Canada. This paper not only delineates the comprehensive overview of the YUTO MMS dataset, delving into aspects such as the collection procedure, sensor configuration, synchronization, data structure and format but also presents a robust benchmark of prevailing Simultaneous Localization and Mapping (SLAM) systems. By subjecting them to analysis utilizing the introduced dataset, this research lays a foundational baseline for ensuing studies, thereby contributing to advancements and enhancements in the SLAM-integrated mobile mapping system. The dataset can be downloaded from: https://ausmlab.github.io/yutomms/.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-06-13T08:28:01Z
      DOI: 10.1177/02783649241261079
       
  • ASIMO: Agent-centric scene representation in multi-object manipulation

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      Authors: Cheol-Hui Min, Young Min Kim
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Vision-based reinforcement learning (RL) is a generalizable way to control an agent because it is agnostic of specific hardware configurations. As visual observations are highly entangled, attempts for vision-based RL rely on scene representation that discerns individual entities and establishes intuitive physics to constitute the world model. However, most existing works on scene representation learning cannot successfully be deployed to train an RL agent, as they are often highly unstable and fail to sustain for a long enough temporal horizon. We propose ASIMO, a fully unsupervised scene decomposition to perform interaction-rich tasks with a vision-based RL agent. ASIMO decomposes agent-object interaction videos of episodic-length into the agent, objects, and background, predicting their long-term interactions. Further, we explicitly model possible occlusion in the image observations and stably track individual objects. Then, we can correctly deduce the updated positions of individual entities in response to the agent action, only from partial visual observation. Based on the stable entity-wise decomposition and temporal prediction, we formulate a hierarchical framework to train the RL agent that focuses on the context around the object of interest. We demonstrate that our formulation for scene representation can be universally deployed to train different configurations of agents and accomplish several tasks that involve pushing, arranging, and placing multiple rigid objects.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-06-10T08:17:56Z
      DOI: 10.1177/02783649241257537
       
  • Retraction Notice

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      Abstract: The International Journal of Robotics Research, Ahead of Print.

      Citation: The International Journal of Robotics Research
      PubDate: 2024-06-07T07:46:11Z
      DOI: 10.1177/02783649241261054
       
  • Electrostatic brakes enable individual joint control of underactuated,
           highly articulated robots

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      Authors: Patrick Lancaster, Christoforos Mavrogiannis, Siddhartha Srinivasa, Joshua R. Smith
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Highly articulated organisms serve as blueprints for incredibly dexterous mechanisms, but building similarly capable robotic counterparts has been hindered by the difficulties of developing electromechanical actuators with both the high strength and compactness of biological muscle. We develop a stackable electrostatic brake that has comparable specific tension and weight to that of muscles and integrate it into a robotic joint. High degree-of-freedom mechanisms composed of such electrostatic brake enabled joints can then employ established control algorithms to achieve hybrid motor-brake actuated dexterous manipulation. Specifically, our joint design enables a ten degree-of-freedom robot equipped with only one motor to manipulate multiple objects simultaneously. We also show that the use of brakes allows a two-fingered robot to perform in-hand re-positioning of an object 45% more quickly and with 53% lower positioning error than without brakes. Relative to fully actuated robots, robots equipped with such electrostatic brakes will have lower weight, volume, and power consumption yet retain the ability to reach arbitrary joint configurations.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-06-05T11:21:01Z
      DOI: 10.1177/02783649241250362
       
  • Set-valued rigid-body dynamics for simultaneous, inelastic, frictional
           impacts

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      Authors: Mathew Halm, Michael Posa
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Robotic manipulation and locomotion often entail nearly-simultaneous collisions—such as heel and toe strikes during a foot step—with outcomes that are extremely sensitive to the order in which impacts occur. Robotic simulators and state estimation commonly lack the fidelity and accuracy to predict this ordering, and instead pick one with a heuristic. This discrepancy degrades performance when model-based controllers and policies learned in simulation are placed on a real robot. We reconcile this issue with a set-valued rigid-body model which generates a broad set of outcomes to simultaneous frictional impacts with any impact ordering. We first extend Routh’s impact model to multiple impacts by reformulating it as a differential inclusion (DI), and show that any solution will resolve all impacts in finite time. By considering time as a state, we embed this model into another DI which captures the continuous-time evolution of rigid-body dynamics, and guarantee existence of solutions. We finally cast simulation of simultaneous impacts as a linear complementarity problem (LCP), and develop an algorithm for tight approximation of the post-impact velocity set with probabilistic guarantees. We demonstrate our approach on several examples drawn from manipulation and legged locomotion, and compare the predictions to other models of rigid and compliant collisions.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-05-25T01:06:57Z
      DOI: 10.1177/02783649241236860
       
  • Spiral complete coverage path planning based on conformal slit mapping in
           multi-connected domains

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      Authors: Changqing Shen, Sihao Mao, Bingzhou Xu, Ziwei Wang, Xiaojian Zhang, Sijie Yan, Han Ding
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      The generation of smoother and shorter spiral complete coverage paths in multi-connected domains is a crucial research topic in path planning for robotic cavity machining and other related fields. Traditional methods for spiral path planning in multi-connected domains typically incorporate a subregion division procedure that leads to excessive subregion bridging, requiring longer, more sharply turning, and unevenly spaced spirals to achieve complete coverage. To address this issue, this paper proposes a novel spiral complete coverage path planning method using conformal slit mapping. It takes advantage of the fact that conformal slit mapping can transform multi-connected domains into regular disks or annuluses without the need for subregion division. Firstly, a slit mapping calculation technique is proposed for segmented cubic spline boundaries with corners. Secondly, a spiral path spacing control method is developed based on the maximum inscribed circle radius between adjacent conformal slit mapping iso-parameters. Thirdly, the spiral coverage path is derived by offsetting iso-parameters. Numerical experiments indicate that our method shares a comparable order-of-magnitude in computation time with the traditional PDE-based spiral complete coverage path method, but it excels in optimizing total path length, smoothness, and spacing consistency. Finally, we performed experiments on cavity milling and dry runs to compare the new method with the traditional PDE-based method in terms of machining duration and steering impact, respectively. The comparison reveals that, with both algorithms achieving complete coverage, the new algorithm reduces machining time and steering impact by 12.34% and 22.78%, respectively, compared with the traditional PDE-based method.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-05-10T12:37:41Z
      DOI: 10.1177/02783649241251385
       
  • Planning for heterogeneous teams of robots with temporal logic,
           capability, and resource constraints

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      Authors: Gustavo A. Cardona, Cristian-Ioan Vasile
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      This paper presents a comprehensive approach for planning for teams of heterogeneous robots with different capabilities and the transportation of resources. We use Capability Temporal Logic (CaTL), a formal language that helps express tasks involving robots with multiple capabilities with spatial, temporal, and logical constraints. We extend CaTL to also capture resource constraints, where resources can be divisible and indivisible, for instance, sand and bricks, respectively. Robots transport resources using various storage types, such as uniform (shared storage among resources) and compartmental (individual storage per resource). Robots’ resource transportation capacity is defined based on resource type and robot class. Robot and resource dynamics and the CaTL mission are jointly encoded in a Mixed Integer Linear Programming (MILP), which maximizes disjoint robot and resource robustness while minimizing spurious movement of both. We propose a multi-robustness approach for Multi-Class Signal Temporal Logic (mcSTL), allowing for generalized quantitative semantics across multiple predicate classes. Thus, we compute availability robustness scores for robots and resources separately. Finally, we conduct multiple experiments demonstrating functionality and time performance by varying resources and storage types.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-04-29T04:12:04Z
      DOI: 10.1177/02783649241247285
       
  • Reactive optimal motion planning to anywhere in the presence of moving
           obstacles

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      Authors: Panagiotis Rousseas, Charalampos Bechlioulis, Kostas Kyriakopoulos
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      In this paper, a novel optimal motion planning framework that enables navigating optimally from any initial, to any final position within confined workspaces with convex, moving obstacles is presented. Our method outputs a smooth velocity vector field, which is then employed as a reference controller in order to sub-optimally avoid moving obstacles. The proposed approach leverages and extends desirable properties of reactive methods in order to provide a provably convergent and safe solution. Our algorithm is evaluated with both static and moving obstacles in synthetic environments and is compared against a variety of existing methods. The efficacy and applicability of the proposed scheme is finally validated in a high-fidelity simulation environment.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-04-23T07:12:07Z
      DOI: 10.1177/02783649241245729
       
  • Multimotion visual odometry

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      Authors: Kevin M. Judd, Jonathan D. Gammell
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Visual motion estimation is a well-studied challenge in autonomous navigation. Recent work has focused on addressing multimotion estimation in highly dynamic environments. These environments not only comprise multiple, complex motions but also tend to exhibit significant occlusion. Estimating third-party motions simultaneously with the sensor egomotion is difficult because an object’s observed motion consists of both its true motion and the sensor motion. Most previous works in multimotion estimation simplify this problem by relying on appearance-based object detection or application-specific motion constraints. These approaches are effective in specific applications and environments but do not generalize well to the full multimotion estimation problem (MEP). This paper presents Multimotion Visual Odometry (MVO), a multimotion estimation pipeline that estimates the full SE(3) trajectory of every motion in the scene, including the sensor egomotion, without relying on appearance-based information. MVO extends the traditional visual odometry (VO) pipeline with multimotion segmentation and tracking techniques. It uses physically founded motion priors to extrapolate motions through temporary occlusions and identify the reappearance of motions through motion closure. Evaluations on real-world data from the Oxford Multimotion Dataset (OMD) and the KITTI Vision Benchmark Suite demonstrate that MVO achieves good estimation accuracy compared to similar approaches and is applicable to a variety of multimotion estimation challenges.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-04-18T09:50:36Z
      DOI: 10.1177/02783649241229095
       
  • MUN-FRL: A Visual-Inertial-LiDAR Dataset for Aerial Autonomous Navigation
           and Mapping

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      Authors: Ravindu G Thalagala, Oscar De Silva, Awantha Jayasiri, Arthur Gubbels, George KI Mann, Raymond G Gosine
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      This paper presents a unique outdoor aerial visual-inertial-LiDAR dataset captured using a multi-sensor payload to promote the global navigation satellite system (GNSS)-denied navigation research. The dataset features flight distances ranging from 300 m to 5 km, collected using a DJI-M600 hexacopter drone and the National Research Council (NRC) Bell412 Advanced Systems Research Aircraft (ASRA). The dataset consists of hardware-synchronized monocular images, inertial measurement unit (IMU) measurements, 3D light detection and ranging (LiDAR) point-clouds, and high-precision real-time kinematic (RTK)-GNSS based ground truth. Nine data sequences were collected as robot operating system (ROS) bags over 100 mins of outdoor environment footage ranging from urban areas, highways, airports, hillsides, prairies, and waterfronts. The dataset was collected to facilitate the development of visual-inertial-LiDAR odometry and mapping algorithms, visual-inertial navigation algorithms, object detection, segmentation, and landing zone detection algorithms based on real-world drone and full-scale helicopter data. All the data sequences contain raw sensor measurements, hardware timestamps, and spatio-temporally aligned ground truth. The intrinsic and extrinsic calibrations of the sensors are also provided, along with raw calibration datasets. A performance summary of state-of-the-art methods applied on the data sequences is also provided.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-04-16T09:25:16Z
      DOI: 10.1177/02783649241238358
       
  • A framework for collaborative multi-robot mapping using spectral graph
           wavelets

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      Authors: Lukas Bernreiter, Shehryar Khattak, Lionel Ott, Roland Siegwart, Marco Hutter, Cesar Cadena
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      The exploration of large-scale unknown environments can benefit from the deployment of multiple robots for collaborative mapping. Each robot explores a section of the environment and communicates onboard pose estimates and maps to a central server to build an optimized global multi-robot map. Naturally, inconsistencies can arise between onboard and server estimates due to onboard odometry drift, failures, or degeneracies. The mapping server can correct and overcome such failure cases using computationally expensive operations such as inter-robot loop closure detection and multi-modal mapping. However, the individual robots do not benefit from the collaborative map if the mapping server provides no feedback. Although server updates from the multi-robot map can greatly alleviate the robotic mission strategically, most existing work lacks them, due to their associated computational and bandwidth-related costs. Motivated by this challenge, this paper proposes a novel collaborative mapping framework that enables global mapping consistency among robots and the mapping server. In particular, we propose graph spectral analysis, at different spatial scales, to detect structural differences between robot and server graphs, and to generate necessary constraints for the individual robot pose graphs. Our approach specifically finds the nodes that correspond to the drift’s origin rather than the nodes where the error becomes too large. We thoroughly analyze and validate our proposed framework using several real-world multi-robot field deployments where we show improvements of the onboard system up to 90% and can recover the onboard estimation from localization failures and even from the degeneracies within its estimation.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-04-15T10:54:26Z
      DOI: 10.1177/02783649241246847
       
  • Reactive collision-free motion generation in joint space via dynamical
           systems and sampling-based MPC

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      Authors: Mikhail Koptev, Nadia Figueroa, Aude Billard
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Dynamical system (DS) based motion planning offers collision-free motion, with closed-loop reactivity thanks to their analytical expression. It ensures that obstacles are not penetrated by reshaping a nominal DS through matrix modulation, which is constructed using continuously differentiable obstacle representations. However, state-of-the-art approaches may suffer from local minima induced by non-convex obstacles, thus failing to scale to complex, high-dimensional joint spaces. On the other hand, sampling-based Model Predictive Control (MPC) techniques provide feasible collision-free paths in joint-space, yet are limited to quasi-reactive scenarios due to computational complexity that grows cubically with space dimensionality and horizon length. To control the robot in the cluttered environment with moving obstacles, and to generate feasible and highly reactive collision-free motion in robots’ joint space, we present an approach for modulating joint-space DS using sampling-based MPC. Specifically, a nominal DS representing an unconstrained desired joint space motion to a target is locally deflected with obstacle-tangential velocity components navigating the robot around obstacles and avoiding local minima. Such tangential velocity components are constructed from receding horizon collision-free paths generated asynchronously by the sampling-based MPC. Notably, the MPC is not required to run constantly, but only activated when the local minima is detected. The approach is validated in simulation and real-world experiments on a 7-DoF robot demonstrating the capability of avoiding concave obstacles, while maintaining local attractor stability in both quasi-static and highly dynamic cluttered environments.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-04-12T04:54:19Z
      DOI: 10.1177/02783649241246557
       
  • Decentralized state estimation: An approach using pseudomeasurements and
           preintegration

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      Authors: Charles Champagne Cossette, Mohammed Ayman Shalaby, David Saussié, James Richard Forbes
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      This paper addresses the problem of decentralized, collaborative state estimation in robotic teams. In particular, this paper considers problems where individual robots estimate similar physical quantities, such as each other’s position relative to themselves. The use of pseudomeasurements is introduced as a means of modeling such relationships between robots’ state estimates and is shown to be a tractable way to approach the decentralized state estimation problem. Moreover, this formulation easily leads to a general-purpose observability test that simultaneously accounts for measurements that robots collect from their own sensors, as well as the communication structure within the team. Finally, input preintegration is proposed as a communication-efficient way of sharing odometry information between robots, and the entire theory is appropriate for both vector-space and Lie-group state definitions. To overcome the need for communicating preintegrated covariance information, a deep autoencoder is proposed that reconstructs the covariance information from the inputs, hence further reducing the communication requirements. The proposed framework is evaluated on three different simulated problems, and one experiment involving three quadcopters.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-04-04T01:24:46Z
      DOI: 10.1177/02783649241230993
       
  • HeLiPR: Heterogeneous LiDAR dataset for inter-LiDAR place recognition
           under spatiotemporal variations

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      Authors: Minwoo Jung, Wooseong Yang, Dongjae Lee, Hyeonjae Gil, Giseop Kim, Ayoung Kim
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Place recognition is crucial for robot localization and loop closure in simultaneous localization and mapping (SLAM). Light Detection and Ranging (LiDAR), known for its robust sensing capabilities and measurement consistency even in varying illumination conditions, has become pivotal in various fields, surpassing traditional imaging sensors in certain applications. Among various types of LiDAR, spinning LiDARs are widely used, while non-repetitive scanning patterns have recently been utilized in robotics applications. Some LiDARs provide additional measurements such as reflectivity, Near Infrared (NIR), and velocity from Frequency modulated continuous wave (FMCW) LiDARs. Despite these advances, there is a lack of comprehensive datasets reflecting the broad spectrum of LiDAR configurations for place recognition. To tackle this issue, our paper proposes the HeLiPR dataset, curated especially for place recognition with heterogeneous LiDARs, embodying spatiotemporal variations. To the best of our knowledge, the HeLiPR dataset is the first heterogeneous LiDAR dataset supporting inter-LiDAR place recognition with both non-repetitive and spinning LiDARs, accommodating different field of view (FOV)s and varying numbers of rays. The dataset covers diverse environments, from urban cityscapes to high-dynamic freeways, over a month, enhancing adaptability and robustness across scenarios. Notably, HeLiPR dataset includes trajectories parallel to MulRan sequences, making it valuable for research in heterogeneous LiDAR place recognition and long-term studies. The dataset is accessible at https://sites.google.com/view/heliprdataset.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-04-03T07:00:33Z
      DOI: 10.1177/02783649241242136
       
  • Non-linearity Measure for POMDP-based Motion Planning

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      Authors: Marcus Hoerger, Hanna Kurniawati, Alberto Elfes
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Motion planning under uncertainty is essential for reliable robot operation. Despite substantial advances over the past decade, the problem remains difficult for systems with complex dynamics. Most state-of-the-art methods perform search that relies on a large number of forward simulations. For systems with complex dynamics, this generally requires costly numerical integrations, which significantly slows down the planning process. Linearization-based methods have been proposed that can alleviate the above problem. However, it is not clear how linearization affects the quality of the generated motion strategy, and when such simplifications are admissible. To answer these questions, we propose a non-linearity measure, called Statistical-distance-based Non-linearity Measure (SNM), that can identify where linearization is beneficial and where it should be avoided. We show that when the problem is framed as the Partially Observable Markov Decision Process, the value difference between the optimal strategy for the original model and the linearized model can be upper-bounded by a function linear in SNM. Comparisons with an existing measure on various scenarios indicate that SNM is more suitable in estimating the effectiveness of linearization-based solvers. To test the applicability of SNM in motion planning, we propose a simple online planner that uses SNM as a heuristic to switch between a general and a linearization-based solver. Results on a car-like robot with second order dynamics and 4-DOFs and 7-DOFs torque-controlled manipulators indicate that SNM can appropriately decide if and when a linearization-based solver should be used.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-03-27T05:59:02Z
      DOI: 10.1177/02783649241239077
       
  • Boundary-aware value function generation for safe stochastic motion
           planning

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      Authors: Junhong Xu, Kai Yin, Jason M. Gregory, Kris Hauser, Lantao Liu
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Navigation safety is critical for many autonomous systems such as self-driving vehicles in an urban environment. It requires an explicit consideration of boundary constraints that describe the borders of any infeasible, non-navigable, or unsafe regions. We propose a principled boundary-aware safe stochastic planning framework with promising results. Our method generates a value function that can strictly distinguish the state values between free (safe) and non-navigable (boundary) spaces in the continuous state, naturally leading to a safe boundary-aware policy. At the core of our solution lies a seamless integration of finite elements and kernel-based functions, where the finite elements allow us to characterize safety-critical states’ borders accurately, and the kernel-based function speeds up computation for the non-safety-critical states. The proposed method was evaluated through extensive simulations and demonstrated safe navigation behaviors in mobile navigation tasks. Additionally, we demonstrate that our approach can maneuver safely and efficiently in cluttered real-world environments using a ground vehicle with strong external disturbances, such as navigating on a slippery floor and against external human intervention.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-03-22T01:05:04Z
      DOI: 10.1177/02783649241238766
       
  • Path signatures for diversity in probabilistic trajectory optimisation

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      Authors: Lucas Barcelos, Tin Lai, Rafael Oliveira, Paulo Borges, Fabio Ramos
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Motion planning can be cast as a trajectory optimisation problem where a cost is minimised as a function of the trajectory being generated. In complex environments with several obstacles and complicated geometry, this optimisation problem is usually difficult to solve and prone to local minima. However, recent advancements in computing hardware allow for parallel trajectory optimisation where multiple solutions are obtained simultaneously, each initialised from a different starting point. Unfortunately, without a strategy preventing two solutions to collapse on each other, naive parallel optimisation can suffer from mode collapse diminishing the efficiency of the approach and the likelihood of finding a global solution. In this paper, we leverage on recent advances in the theory of rough paths to devise an algorithm for parallel trajectory optimisation that promotes diversity over the range of solutions, therefore avoiding mode collapses and achieving better global properties. Our approach builds on path signatures and Hilbert space representations of trajectories and connects parallel variational inference for trajectory estimation with diversity-promoting kernels. We empirically demonstrate that this strategy achieves lower average costs than competing alternatives on a range of problems, from 2D navigation to robotic manipulators operating in cluttered environments.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-03-14T10:00:37Z
      DOI: 10.1177/02783649241233300
       
  • Proprioceptive learning with soft polyhedral networks

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      Authors: Xiaobo Liu, Xudong Han, Wei Hong, Fang Wan, Chaoyang Song
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Proprioception is the “sixth sense” that detects limb postures with motor neurons. It requires a natural integration between the musculoskeletal systems and sensory receptors, which is challenging among modern robots that aim for lightweight, adaptive, and sensitive designs at low costs in mechanical design and algorithmic computation. Here, we present the Soft Polyhedral Network with an embedded vision for physical interactions, capable of adaptive kinesthesia and viscoelastic proprioception by learning kinetic features. This design enables passive adaptations to omni-directional interactions, visually captured by a miniature high-speed motion-tracking system embedded inside for proprioceptive learning. The results show that the soft network can infer real-time 6D forces and torques with accuracies of 0.25/0.24/0.35 N and 0.025/0.034/0.006 Nm in dynamic interactions. We also incorporate viscoelasticity in proprioception during static adaptation by adding a creep and relaxation modifier to refine the predicted results. The proposed soft network combines simplicity in design, omni-adaptation, and proprioceptive sensing with high accuracy, making it a versatile solution for robotics at a low material cost with more than one million use cycles for tasks such as sensitive and competitive grasping and touch-based geometry reconstruction. This study offers new insights into vision-based proprioception for soft robots in adaptive grasping, soft manipulation, and human-robot interaction.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-03-13T12:15:25Z
      DOI: 10.1177/02783649241238765
       
  • The role of heterogeneity in autonomous perimeter defense problems

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      Authors: Aviv Adler, Oscar Mickelin, Ragesh K. Ramachandran, Gaurav S. Sukhatme, Sertac Karaman
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      When is heterogeneity in the composition of an autonomous robotic team beneficial and when is it detrimental' We investigate and answer this question in the context of a minimally viable model that examines the role of heterogeneous speeds in perimeter defense problems, where defenders share a total allocated speed budget. We consider two distinct problem settings and develop strategies based on dynamic programming and on local interaction rules. We present a theoretical analysis of both approaches and our results are extensively validated using simulations. Interestingly, our results demonstrate that the viability of heterogeneous teams depends on the amount of information available to the defenders. Moreover, our results suggest a universality property: across a wide range of problem parameters the optimal ratio of the speeds of the defenders remains nearly constant.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-03-11T03:51:49Z
      DOI: 10.1177/02783649241237544
       
  • Modeling and Control of a Novel Variable Stiffness Three DoFs Wrist

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      Authors: Giuseppe Milazzo, Manuel G. Catalano, Antonio Bicchi, Giorgio Grioli
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      This study introduces an innovative design for a Variable Stiffness 3 Degrees of Freedom actuated wrist capable of actively and continuously adjusting its overall stiffness by modulating the active length of non-linear elastic elements. This modulation is akin to human muscular cocontraction and is achieved using only four motors. The mechanical configuration employed results in a compact and lightweight device with anthropomorphic characteristics, making it potentially suitable for applications such as prosthetics and humanoid robotics. This design aims to enhance performance in dynamic tasks, improve task adaptability, and ensure safety during interactions with both people and objects. The paper details the first hardware implementation of the proposed design, providing insights into the theoretical model, mechanical and electronic components, as well as the control architecture. System performance is assessed using a motion capture system. The results demonstrate that the prototype offers a broad range of motion ([55, −45]° for flexion/extension, ±48° for radial/ulnar deviation, and ±180° for pronation/supination) while having the capability to triple its stiffness. Furthermore, following proper calibration, the wrist posture can be reconstructed through multivariate linear regression using rotational encoders and the forward kinematic model. This reconstruction achieves an average Root Mean Square Error of 6.6°, with an R2 value of 0.93.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-03-09T07:00:33Z
      DOI: 10.1177/02783649241236204
       
  • Compliance while resisting: A shear-thickening fluid controller for
           physical human-robot interaction

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      Authors: Lu Chen, Lipeng Chen, Xiangchi Chen, Haojian Lu, Yu Zheng, Jun Wu, Yue Wang, Zhengyou Zhang, Rong Xiong
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Physical human-robot interaction (pHRI) is widely needed in many fields, such as industrial manipulation, home services, and medical rehabilitation, and puts higher demands on the safety of robots. Due to the uncertainty of the working environment, the pHRI may receive unexpected impact interference, which affects the safety and smoothness of the task execution. The commonly used linear admittance control (L-AC) can cope well with high-frequency small-amplitude noise, but for medium-frequency high-intensity impact, the effect is not as good. Inspired by the solid-liquid phase change nature of shear-thickening fluid, we propose a shear-thickening fluid control (SFC) that can achieve both an easy human-robot collaboration and resistance to impact interference. The SFC’s stability, passivity, and phase trajectory are analyzed in detail, the frequency and time domain properties are quantified, and parameter constraints in discrete control and coupled stability conditions are provided. We conducted simulations to compare the frequency and time domain characteristics of L-AC, nonlinear admittance controller (N-AC), and SFC and validated their dynamic properties. In real-world experiments, we compared the performance of L-AC, N-AC, and SFC in both fixed and mobile manipulators. L-AC exhibits weak resistance to impact. N-AC can resist moderate impacts but not high-intensity ones and may exhibit self-excited oscillations. In contrast, SFC demonstrated superior impact resistance and maintained stable collaboration, enhancing comfort in cooperative water delivery tasks. Additionally, a case study was conducted in a factory setting, further affirming the SFC’s capability in facilitating human-robot collaborative manipulation and underscoring its potential in industrial applications.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-03-04T01:43:10Z
      DOI: 10.1177/02783649241234364
       
  • Minimal configuration point cloud odometry and mapping

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      Authors: Vedant Bhandari, Tyson Govan Phillips, Peter Ross McAree
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Simultaneous Localization and Mapping (SLAM) refers to the common requirement for autonomous platforms to estimate their pose and map their surroundings. There are many robust and real-time methods available for solving the SLAM problem. Most are divided into a front-end, which performs incremental pose estimation, and a back-end, which smooths and corrects the results. A low-drift front-end odometry solution is needed for robust and accurate back-end performance. Front-end methods employ various techniques, such as point cloud-to-point cloud (PC2PC) registration, key feature extraction and matching, and deep learning-based approaches. The front-end algorithms have become increasingly complex in the search for low-drift solutions and many now have large configuration parameter sets. It is desirable that the front-end algorithm should be inherently robust so that it does not need to be tuned by several, perhaps many, configuration parameters to achieve low drift in various environments. To address this issue, we propose Simple Mapping and Localization Estimation (SiMpLE), a front-end LiDAR-only odometry method that requires five low-sensitivity configurable parameters. SiMpLE is a scan-to-map point cloud registration algorithm that is straightforward to understand, configure, and implement. We evaluate SiMpLE using the KITTI, MulRan, UrbanNav, and a dataset created at the University of Queensland. SiMpLE performs among the top-ranked algorithms in the KITTI dataset and outperformed all prominent open-source approaches in the MulRan dataset whilst having the smallest configuration set. The UQ dataset also demonstrated accurate odometry with low-density point clouds using Velodyne VLP-16 and Livox Horizon LiDARs. SiMpLE is a front-end odometry solution that can be integrated with other sensing modalities and pose graph-based back-end methods for increased accuracy and long-term mapping. The lightweight and portable code for SiMpLE is available at: https://github.com/vb44/SiMpLE.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-02-29T07:50:54Z
      DOI: 10.1177/02783649241235325
       
  • Scaling effects of manufacturing processes and actuation sources on
           control of remotely powered micro actuators

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      Authors: Jae-Kyung Heo, Kausthubharam, Minyong Jung, Wonjin Kim, Suhwan Jeong, Dae-Seob Song, Ying-Jun Quan, Ji Ho Jeon, Rodrigo Ribeiro de Moura, Sung-Hoon Ahn
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Over the past decade, remotely powered micro actuators have gained increased attention for biomedical and environmental remediation applications, owing to their ability to access confined regions and the nonintrusive nature of control. Recent studies focus on improving the functionality and versatility of micro actuators through the development of new fabrication and actuation techniques. However, there is a possibility that a limited understanding of the scaling impact of various physical principles governing design and control has affected the successful implementation of such devices in practical scenarios. Thus, the main focus of this review is to evaluate the most widely utilized manufacturing methods and remote actuation sources in light of various characteristics such as resolution, productivity, shape complexity, actuation speed, actuation mode, operating medium, and so on. State-of-the-art developments in each type of manufacturing and actuation are introduced and delineated. Finally, the limitations of current devices are reviewed, and the future direction to enable the full potential of this field is provided.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-02-22T11:39:04Z
      DOI: 10.1177/02783649241235215
       
  • Ergonomically optimized path-planning for industrial human–robot
           collaboration

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      Authors: Atieh Merikh Nejadasl, Jihad Achaoui, Ilias El Makrini, Greet Van De Perre, Tom Verstraten, Bram Vanderborght
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      This paper focuses on improving the ergonomics of industrial workers. It addresses the critical implications of poor ergonomics, which can lead to musculoskeletal disorders over time. A novel methodology for a path-planning algorithm designed for human–robot collaboration was introduced to tackle this challenge. The algorithm’s essential contribution lies in determining the most ergonomic path for a robot to guide a human’s hand during task execution, facilitating a transition toward an optimized body configuration. The algorithm effectively charts the ergonomic path by adopting a Cartesian path-planning approach and employing the cell decomposition method. The methodology was implemented on a dataset of ten individuals, representing a diverse group of male and female subjects aged between 20 and 35, with one participant being left-handed. The algorithm was applied to three different activities: “stacking an item,” “taking an object from a shelf,” and “assembling an object by sitting over a table.” The results demonstrated a significant improvement in the REBA score (as a measure of ergonomics condition) of the individuals after applying the algorithm. This outcome reinforces the efficacy of the methodology in enhancing the ergonomics of industrial workers. Furthermore, the study compared the performance of A* with three heuristic functions against Dijkstra’s algorithm, aiming to identify the most effective approach for achieving optimal ergonomic paths in human–robot collaboration. The findings revealed that A* with a specific heuristic function surpassed Dijkstra’s algorithm, underscoring its superiority in this context. The findings highlight the potential for optimizing human–robot collaboration and offer practical implications for designing more efficient industrial work environments.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-02-22T08:03:04Z
      DOI: 10.1177/02783649241235670
       
  • RoBUTCHER: A novel robotic meat factory cell platform

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      Authors: Alex Mason, Ian de Medeiros Esper, Olga Korostynska, Luis Eduardo Cordova-Lopez, Dmytro Romanov, Michaela Pinceková, Per Håkon Bjørnstad, Ole Alvseike, Anton Popov, Oleh Smolkin, Maksym Manko, Lars Bager Christensen, Kristóf Takács, Tamás Haidegger
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Automation is critically important for sustainability in meat production, where heavy reliance on human labour is a growing challenge. In this work, a novel robotic Meat Factory Cell (MFC) platform presents the opportunity for unconventional automation in pork meat processing, particularly abattoirs. Instead of following line-based approaches, which are the main option today, it uses robotics and Artificial Intelligence (AI) to perform complex cutting and manipulation operations on entire unchilled pork carcasses, with awareness of biological variation and deformation. The long-term goal of the MFC is to take a pork carcass as an input and produce seven primal outputs: hams, shoulders, saddle, belly and entire organ set. However, the MFC platform is under continuous development – therefore, this paper aims to demonstrate it through a specific use-case: shoulder removal. The system is evaluated based on data from testing and development sessions (June–November 2022), with a total of 34 attempted shoulder removals. Data regarding the MFCs’ ability to handle variation, in addition to success rate and process timing models are presented. Qualitative feedback from skilled butchers is also discussed. The authors propose that, as well as technical development of the platform, it is important to consider new ways of comparing unconventional systems with their conventional counterparts. Innovative manufacturing systems have more to offer than raw speed and volume; traits such as flexibility, robustness and scalability – particularly economic scalability – should play a prominent role. Future legislation and standards must also encourage innovation rather than hinder innovative robotics solutions.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-02-21T12:42:06Z
      DOI: 10.1177/02783649241234035
       
  • A transhumeral prosthesis with an artificial neuromuscular system:
           Sim2real-guided design, modeling, and control

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      Authors: Alexander Toedtheide, Edmundo Pozo Fortunić, Johannes Kühn, Elisabeth Jensen, Sami Haddadin
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      In this work we introduce a new type of human-inspired upper-limb prostheses. The Artificial Neuromuscular Prosthesis (ANP) imitates the human neuromuscular system in the sense of its compliance, backdrivability, natural motion, proprioceptive sensing, and kinesthetics. To realize this challenging goal, we introduce a novel human-inspired and simulation-based development paradigm to design the prosthesis mechatronics in correspondence to the human body. The ANP provides body awareness, contact awareness, and human-like contact response, realized via floating base rigid-body models, disturbance observers, and joint impedance control—concepts known from established state-of-the-art robotics. The ANP mechatronics is characterized by a four degrees of freedom (dof) torque-controlled human-like kinematics, a tendon-driven 2-dof wrist, and spatial orientation sensing at a weight of 1.7 kg (without hand and battery). The paper deals with the rigorous mathematical modeling, control, design and evaluation of this device type along initially defined requirements within a single prototype only. The proposed systemic and grasping capabilities are verified under laboratory conditions by an unimpaired user. Future work will increase the technology readiness level of the next generation device, where human studies with impaired users will be done.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-02-21T05:38:41Z
      DOI: 10.1177/02783649231218719
       
  • The surface edge explorer (SEE): A measurement-direct approach to next
           best view planning

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      Authors: Rowan Border, Jonathan D. Gammell
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      High-quality observations of the real world are crucial for a variety of applications, including producing 3D printed replicas of small-scale scenes and conducting inspections of large-scale infrastructure. These 3D observations are commonly obtained by combining multiple sensor measurements from different views. Guiding the selection of suitable views is known as the Next Best View (NBV) planning problem. Most NBV approaches reason about measurements using rigid data structures (e.g., surface meshes or voxel grids). This simplifies next best view selection but can be computationally expensive, reduces real-world fidelity and couples the selection of a next best view with the final data processing. This paper presents the Surface Edge Explorer (SEE), a NBV approach that selects new observations directly from previous sensor measurements without requiring rigid data structures. SEE uses measurement density to propose next best views that increase coverage of insufficiently observed surfaces while avoiding potential occlusions. Statistical results from simulated experiments show that SEE can attain similar or better surface coverage with less observation time and travel distance than evaluated volumetric approaches on both small- and large-scale scenes. Real-world experiments demonstrate SEE autonomously observing a deer statue using a 3D sensor affixed to a robotic arm.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-02-15T08:23:52Z
      DOI: 10.1177/02783649241230098
       
  • Magnetic needle steering control using Lyapunov redesign

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      Authors: Richard L. Pratt, Andrew J. Petruska
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Using steerable needles to enable course correction and curved trajectories can improve surgical outcomes in numerous clinical interventions including electrode placement for deep brain stimulation. In this work, a physically motivated kinematic model for an actively steered magnetic-tipped needle is used in closed-loop control to perform insertion trajectories. The applied control law is derived using the Lyapunov redesign. Simulation results show this control method to be accurate for a wide range of conditions including randomized target trajectories. Control is performed experimentally in a brain tissue phantom for both initial position offset recovery and curved trajectories. Converged error results average 0.52 mm from target trajectory. Simulation results demonstrate the robustness of the control implementation, while experimental results exceed the accuracy required for the target application, encouraging future use in a clinical setting. Beyond needle insertion, this work has implications in general vehicle steering, as this model and control can apply to systems with similar kinematics such as boats and wheeled vehicles that could benefit from a relaxed slip constraint.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-02-14T12:29:51Z
      DOI: 10.1177/02783649241231600
       
  • The INSANE dataset: Large number of sensors for challenging UAV flights in
           Mars analog, outdoor, and out-/indoor transition scenarios

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      Authors: Christian Brommer, Alessandro Fornasier, Martin Scheiber, Jeff Delaune, Roland Brockers, Jan Steinbrener, Stephan Weiss
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      For real-world applications, autonomous mobile robotic platforms must be capable of navigating safely in a multitude of different and dynamic environments with accurate and robust localization being a key prerequisite. To support further research in this domain, we present the INSANE datasets (Increased Number of Sensors for developing Advanced and Novel Estimators)—a collection of versatile Micro Aerial Vehicle (MAV) datasets for cross-environment localization. The datasets provide various scenarios with multiple stages of difficulty for localization methods. These scenarios range from trajectories in the controlled environment of an indoor motion capture facility, to experiments where the vehicle performs an outdoor maneuver and transitions into a building, requiring changes of sensor modalities, up to purely outdoor flight maneuvers in a challenging Mars analog environment to simulate scenarios which current and future Mars helicopters would need to perform. The presented work aims to provide data that reflects real-world scenarios and sensor effects. The extensive sensor suite includes various sensor categories, including multiple Inertial Measurement Units (IMUs) and cameras. Sensor data is made available as unprocessed measurements and each dataset provides highly accurate ground truth, including the outdoor experiments where a dual Real-Time Kinematic (RTK) Global Navigation Satellite System (GNSS) setup provides sub-degree and centimeter accuracy (1-sigma). The sensor suite also includes a dedicated high-rate IMU to capture all the vibration dynamics of the vehicle during flight to support research on novel machine learning-based sensor signal enhancement methods for improved localization. The datasets and post-processing tools are available at: https://sst.aau.at/cns/datasets/insane-dataset/
      Citation: The International Journal of Robotics Research
      PubDate: 2024-02-14T04:32:47Z
      DOI: 10.1177/02783649241227245
       
  • A survey on socially aware robot navigation: Taxonomy and future
           challenges

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      Authors: Phani Teja Singamaneni, Pilar Bachiller-Burgos, Luis J. Manso, Anaís Garrell, Alberto Sanfeliu, Anne Spalanzani, Rachid Alami
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Socially aware robot navigation is gaining popularity with the increase in delivery and assistive robots. The research is further fueled by a need for socially aware navigation skills in autonomous vehicles to move safely and appropriately in spaces shared with humans. Although most of these are ground robots, drones are also entering the field. In this paper, we present a literature survey of the works on socially aware robot navigation in the past 10 years. We propose four different faceted taxonomies to navigate the literature and examine the field from four different perspectives. Through the taxonomic review, we discuss the current research directions and the extending scope of applications in various domains. Further, we put forward a list of current research opportunities and present a discussion on possible future challenges that are likely to emerge in the field.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-02-13T06:50:56Z
      DOI: 10.1177/02783649241230562
       
  • Foundations of spatial perception for robotics: Hierarchical
           representations and real-time systems

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      Authors: Nathan Hughes, Yun Chang, Siyi Hu, Rajat Talak, Rumaia Abdulhai, Jared Strader, Luca Carlone
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      3D spatial perception is the problem of building and maintaining an actionable and persistent representation of the environment in real-time using sensor data and prior knowledge. Despite the fast-paced progress in robot perception, most existing methods either build purely geometric maps (as in traditional SLAM) or “flat” metric-semantic maps that do not scale to large environments or large dictionaries of semantic labels. The first part of this paper is concerned with representations: we show that scalable representations for spatial perception need to be hierarchical in nature. Hierarchical representations are efficient to store, and lead to layered graphs with small treewidth, which enable provably efficient inference. We then introduce an example of hierarchical representation for indoor environments, namely a 3D scene graph, and discuss its structure and properties. The second part of the paper focuses on algorithms to incrementally construct a 3D scene graph as the robot explores the environment. Our algorithms combine 3D geometry (e.g., to cluster the free space into a graph of places), topology (to cluster the places into rooms), and geometric deep learning (e.g., to classify the type of rooms the robot is moving across). The third part of the paper focuses on algorithms to maintain and correct 3D scene graphs during long-term operation. We propose hierarchical descriptors for loop closure detection and describe how to correct a scene graph in response to loop closures, by solving a 3D scene graph optimization problem. We conclude the paper by combining the proposed perception algorithms into Hydra, a real-time spatial perception system that builds a 3D scene graph from visual-inertial data in real-time. We showcase Hydra’s performance in photo-realistic simulations and real data collected by a Clearpath Jackal robots and a Unitree A1 robot. We release an open-source implementation of Hydra at https://github.com/MIT-SPARK/Hydra.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-02-12T11:30:32Z
      DOI: 10.1177/02783649241229725
       
  • A three degrees of freedom switchable impedance myoelectric prosthetic
           wrist

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      Authors: Patricia Capsi-Morales, Cristina Piazza, Giorgio Grioli, Antonio Bicchi, Manuel G. Catalano
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Wrist mobility contributes significantly to the execution of upper limb motor tasks. Despite this, current prosthetic wrists are far less advanced than other artificial joints. Typically, prosthetic wrists offer limited degrees of freedom, if any, which forces users to execute compensatory movements during task performance. This addition increases weight and complexity, two unwelcome factors in upper limb prostheses. This article presents the design of a 3-degree-of-freedom friction-lockable prosthetic wrist actuated by a single motor. The design features adaptable behavior when unlocked, promoting a gentle interaction with the environment, and enables users to adjust the hand configuration during pre-grasping phases. The proposed system was tested, combined with a hand prosthesis, and compared to a commercial rotational wrist during the execution of functional movements. Experiments involved nine able-bodied subjects and one prosthesis user. Participants also performed the experiments with their biological wrist (the intact wrist for the prosthesis user) as a control. Results showed that the lockable wrist was used actively 20% more often than the commercial solution without compromising users’ execution time. Interaction tests reveal that compensatory movements are reduced when using the proposed design, resulting in closer resemblance to the control wrist’s performance. The average satisfaction and usability scores were significantly higher for the proposed wrist, indicating its potential acceptance. Finally, the system was validated in a set of activities of daily living performed by the prosthesis user. The study contributes to the development of more intuitive and adaptable prostheses that can improve the quality of life of amputees.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-02-10T07:07:16Z
      DOI: 10.1177/02783649241231298
       
  • UTIL: An ultra-wideband time-difference-of-arrival indoor localization
           dataset

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      Authors: Wenda Zhao, Abhishek Goudar, Xinyuan Qiao, Angela P. Schoellig
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Ultra-wideband (UWB) time-difference-of-arrival (TDOA)-based localization has emerged as a promising, low-cost, and scalable indoor localization solution, which is especially suited for multi-robot applications. However, there is a lack of public datasets to study and benchmark UWB TDOA positioning technology in cluttered indoor environments. We fill in this gap by presenting a comprehensive dataset using Decawave’s DWM1000 UWB modules. To characterize the UWB TDOA measurement performance under various line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, we collected signal-to-noise ratio (SNR), power difference values, and raw UWB TDOA measurements during the identification experiments. We also conducted a cumulative total of around 150 min of real-world flight experiments on a customized quadrotor platform to benchmark the UWB TDOA localization performance for mobile robots. The quadrotor was commanded to fly with an average speed of 0.45 m/s in both obstacle-free and cluttered environments using four different UWB anchor constellations. Raw sensor data including UWB TDOA, inertial measurement unit (IMU), optical flow, time-of-flight (ToF) laser altitude, and millimeter-accurate ground truth robot poses were collected during the flights. The dataset and development kit are available at https://utiasdsl.github.io/util-uwb-dataset/.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-02-05T08:42:07Z
      DOI: 10.1177/02783649241230640
       
  • A bearing-angle approach for unknown target motion analysis based on
           visual measurements

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      Authors: Zian Ning, Yin Zhang, Jianan Li, Zhang Chen, Shiyu Zhao
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Vision-based estimation of the motion of a moving target is usually formulated as a bearing-only estimation problem where the visual measurement is modeled as a bearing vector. Although the bearing-only approach has been studied for decades, a fundamental limitation of this approach is that it requires extra lateral motion of the observer to enhance the target’s observability. Unfortunately, the extra lateral motion conflicts with the desired motion of the observer in many tasks. It is well-known that, once a target has been detected in an image, a bounding box that surrounds the target can be obtained. Surprisingly, this common visual measurement especially its size information has not been well explored up to now. In this paper, we propose a new bearing-angle approach to estimate the motion of a target by modeling its image bounding box as bearing-angle measurements. Both theoretical analysis and experimental results show that this approach can significantly enhance the observability without relying on additional lateral motion of the observer. The benefit of the bearing-angle approach comes with no additional cost because a bounding box is a standard output of object detection algorithms. The approach simply exploits the information that has not been fully exploited in the past. No additional sensing devices or special detection algorithms are required.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-02-03T04:04:10Z
      DOI: 10.1177/02783649241229172
       
  • Lazy incremental search for efficient replanning with bounded
           suboptimality guarantees

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      Authors: Jaein Lim, Mahdi Ghanei, R. Connor Lawson, Siddhartha Srinivasa, Panagiotis Tsiotras
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      We present a lazy incremental search algorithm, Lifelong-GLS (L-GLS), along with its bounded suboptimal version, Bounded L-GLS (B-LGLS) that combine the search efficiency of incremental search algorithms with the evaluation efficiency of lazy search algorithms for fast replanning in problem domains where edge evaluations are more expensive than vertex expansions. The proposed algorithms generalize Lifelong Planning A* (LPA*) and its bounded suboptimal version, Truncated LPA* (TLPA*), within the Generalized Lazy Search (GLS) framework, so as to restrict expensive edge evaluations only to the current shortest subpath when the cost-to-come inconsistencies are propagated during repair. We also present dynamic versions of the L-GLS and B-LGLS algorithms, called Generalized D* (GD*) and Bounded Generalized D* (B-GD*), respectively, for efficient replanning with non-stationary queries, designed specifically for navigation of mobile robots. We prove that the proposed algorithms are complete and correct in finding a solution that is guaranteed not to exceed the optimal solution cost by a user-chosen factor. Our numerical and experimental results support the claim that the proposed integration of the incremental and lazy search frameworks can help find solutions faster compared to the regular incremental or regular lazy search algorithms when the underlying graph representation changes often.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-01-30T06:20:41Z
      DOI: 10.1177/02783649241227869
       
  • Pose-and-shear-based tactile servoing

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      Authors: John Lloyd, Nathan F. Lepora
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Tactile servoing is an important technique because it enables robots to manipulate objects with precision and accuracy while adapting to changes in their environments in real-time. One approach for tactile servo control with high-resolution soft tactile sensors is to estimate the contact pose relative to an object surface using a convolutional neural network (CNN) for use as a feedback signal. In this paper, we investigate how the surface pose estimation model can be extended to include shear, and utilise these combined pose-and-shear models to develop a tactile robotic system that can be programmed for diverse non-prehensile manipulation tasks, such as object tracking, surface-following, single-arm object pushing and dual-arm object pushing. In doing this, two technical challenges had to be overcome. Firstly, the use of tactile data that includes shear-induced slippage can lead to error-prone estimates unsuitable for accurate control, and so we modified the CNN into a Gaussian-density neural network and used a discriminative Bayesian filter to improve the predictions with a state dynamics model that utilises the robot kinematics. Secondly, to achieve smooth robot motion in 3D space while interacting with objects, we used SE(3) velocity-based servo control, which required re-deriving the Bayesian filter update equations using Lie group theory, as many standard assumptions do not hold for state variables defined on non-Euclidean manifolds. In future, we believe that pose-and-shear-based tactile servoing will enable many object manipulation tasks and the fully-dexterous utilisation of multi-fingered tactile robot hands.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-01-30T02:42:23Z
      DOI: 10.1177/02783649231225811
       
  • MARS-LVIG dataset: A multi-sensor aerial robots SLAM dataset for
           LiDAR-visual-inertial-GNSS fusion

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      Authors: Haotian Li, Yuying Zou, Nan Chen, Jiarong Lin, Xiyuan Liu, Wei Xu, Chunran Zheng, Rundong Li, Dongjiao He, Fanze Kong, Yixi Cai, Zheng Liu, Shunbo Zhou, Kaiwen Xue, Fu Zhang
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      In recent years, advancements in Light Detection and Ranging (LiDAR) technology have made 3D LiDAR sensors more compact, lightweight, and affordable. This progress has spurred interest in integrating LiDAR with sensors such as Inertial Measurement Units (IMUs) and cameras for Simultaneous Localization and Mapping (SLAM) research. Public datasets covering different scenarios, platforms, and viewpoints are crucial for multi-sensor fusion SLAM studies, yet most focus on handheld or vehicle-mounted devices with front or 360-degree views. Data from aerial vehicles with downward-looking views is scarce, existing relevant datasets usually feature low altitudes and are mostly limited to small campus environments. To fill this gap, we introduce the Multi-sensor Aerial Robots SLAM dataset (MARS-LVIG dataset), providing unique aerial downward-looking LiDAR-Visual-Inertial-GNSS data with viewpoints from altitudes between 80 m and 130 m. The dataset not only offers new aspects to test and evaluate existing SLAM algorithms, but also brings new challenges which can facilitate researches and developments of more advanced SLAM algorithms. The MARS-LVIG dataset contains 21 sequences, acquired across diversified large-area environments including an aero-model airfield, an island, a rural town, and a valley. Within these sequences, the UAV has speeds varying from 3 m/s to 12 m/s, a scanning area reaching up to 577,000 m2, and the max path length of 7.148 km in a single flight. This dataset encapsulates data collected by a lightweight, hardware-synchronized sensor package that includes a solid-state 3D LiDAR, a global-shutter RGB camera, IMUs, and a raw message receiver of the Global Navigation Satellite System (GNSS). For algorithm evaluation, this dataset releases ground truth of both localization and mapping, which are acquired by on-board Real-time Kinematic (RTK) and DJI L1 (post-processed by its supporting software DJI Terra), respectively. The dataset can be downloaded from: https://mars.hku.hk/dataset.html.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-01-27T02:41:55Z
      DOI: 10.1177/02783649241227968
       
  • Theoretical and experimental investigation of variable contact forces on
           the rollers of a mecanum wheeled mobile robot

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      Authors: Can Tezel, Gokhan Bayar
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      The modeling structures of rollers, mecanum wheels, and mecanum wheeled mobile robots presented in the literature use single contact force assumption. This assumption may give good results in a simulation environment; however, it is not strong enough to reflect reality. To make an improvement, a new aspect of mecanum wheel model is proposed in this study. The model takes the variable roller contact forces into account and investigates their effects on the performance of motion of a mecanum wheeled mobile robot. It uses all points on each roller’s curved shape so that the slippage phenomena is also taken into consideration which makes it possible to get less position estimation errors in real-time operations. The modeling structure introduced aims to reflect reality both in simulation and real applications. A simulation environment is developed for this study. To make verification, an experimental setup including a four-mecanum-wheeled mobile robot, its mechanical and electrical hardware and software infrastructures, and a ground-truth system is designed and constructed. A Robot Operating System (ROS) based control system is created and integrated into the experimental system. Different types of reference trajectories including straight-line, square-shaped, Z-shaped, and wave(S)-shaped are used to test the performance of the model proposed in both simulation and experimental studies. The tests are also conducted using the model that involves single contact force assumption to make comparisons. The details of the variable contact forces model proposed, simulation environment developed, experimental setup built, simulation and experimental studies, their results, and comparisons are given in this paper.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-01-24T01:03:58Z
      DOI: 10.1177/02783649241228607
       
  • Soft modularized robotic arm for safe human–robot interaction based on
           visual and proprioceptive feedback

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      Authors: Subyeong Ku, Byung-Hyun Song, Taejun Park, Younghoon Lee, Yong-Lae Park
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      This study proposes a modularized soft robotic arm with integrated sensing of human touches for physical human–robot interactions. The proposed robotic arm is constructed by connecting multiple soft manipulator modules, each of which consists of three bellow-type soft actuators, pneumatic valves, and an on-board sensing and control circuit. By employing stereolithography three-dimensional (3D) printing technique, the bellow actuator is capable of incorporating embedded organogel channels in the thin wall of its body that are used for detecting human touches. The organogel thus serves as a soft interface for recognizing the intentions of the human operators, enabling the robot to interact with them while generating desired motions of the manipulator. In addition to the touch sensors, each manipulator module has compact, soft string sensors for detecting the displacements of the bellow actuators. When combined with an inertial measurement unit (IMU), the manipulator module has a capability of estimating its own pose or orientation internally. We also propose a localization method that allows us to estimate the location of the manipulator module and to acquire the 3D information of the target point in an uncontrolled environment. The proposed method uses only a single depth camera combined with a deep learning model and is thus much simpler than those of conventional motion capture systems that usually require multiple cameras in a controlled environment. Using the feedback information from the internal sensors and camera, we implemented closed-loop control algorithms to carry out tasks of reaching and grasping objects. The manipulator module shows structural robustness and the performance reliability over 5,000 cycles of repeated actuation. It shows a steady-state error and a standard deviation of 0.8 mm and 0.3 mm, respectively, using the proposed localization method and the string sensor data. We demonstrate an application example of human–robot interaction that uses human touches as triggers to pick up and manipulate target objects. The proposed soft robotic arm can be easily installed in a variety of human workspaces, since it has the ability to interact safely with humans, eliminating the need for strict control of the environments for visual perception. We believe that the proposed system has the potential to integrate soft robots into our daily lives.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-01-20T08:54:06Z
      DOI: 10.1177/02783649241227249
       
  • Kernel-based diffusion approximated Markov decision processes for
           autonomous navigation and control on unstructured terrains

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      Authors: Junhong Xu, Kai Yin, Zheng Chen, Jason M Gregory, Ethan A Stump, Lantao Liu
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      We propose a diffusion approximation method to the continuous-state Markov decision processes that can be utilized to address autonomous navigation and control in unstructured off-road environments. In contrast to most decision-theoretic planning frameworks that assume fully known state transition models, we design a method that eliminates such a strong assumption that is often extremely difficult to engineer in reality. We first take the second-order Taylor expansion of the value function. The Bellman optimality equation is then approximated by a partial differential equation, which only relies on the first and second moments of the transition model. By combining the kernel representation of the value function, we design an efficient policy iteration algorithm whose policy evaluation step can be represented as a linear system of equations characterized by a finite set of supporting states. We first validate the proposed method through extensive simulations in 2D obstacle avoidance and 2.5D terrain navigation problems. The results show that the proposed approach leads to a much superior performance over several baselines. We then develop a system that integrates our decision-making framework with onboard perception and conduct real-world experiments in both cluttered indoor and unstructured outdoor environments. The results from the physical systems further demonstrate the applicability of our method in challenging real-world environments.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-01-19T11:29:23Z
      DOI: 10.1177/02783649231225977
       
  • A cross-domain challenge with panoptic segmentation in agriculture

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      Authors: Michael Halstead, Patrick Zimmer, Chris McCool
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Automation in agriculture is a growing area of research with fundamental societal importance as farmers are expected to produce more and better crop with fewer resources. A key enabling factor is robotic vision techniques allowing us to sense and then interact with the environment. A limiting factor for these robotic vision systems is their cross-domain performance, that is, their ability to operate in a large range of environments. In this paper, we propose the use of auxiliary tasks to enhance cross-domain performance without the need for extra data. We perform experiments using four datasets (two in a glasshouse and two in arable farmland) for four cross-domain evaluations. These experiments demonstrate the effectiveness of our auxiliary tasks to improve network generalisability. In glasshouse experiments, our approach improves the panoptic quality of things from 10.4 to 18.5 and in arable farmland from 16.0 to 27.5; where a score of 100 is the best. To further evaluate the generalisability of our approach, we perform an ablation study using the large Crop and Weed dataset (CAW) where we improve cross-domain performance (panoptic quality of things) from 12.8 to 30.6 for the CAW dataset to our novel WeedAI dataset, and 21.2 to 36.0 from CAW to the other arable farmland dataset. Although our proposed approaches considerably improve cross-domain performance we still do not generally outperform in-domain trained systems. This highlights the potential room for improvement in this area and the importance of cross-domain research for robotic vision systems.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-01-19T07:04:33Z
      DOI: 10.1177/02783649241227448
       
  • Intelligent robotic sonographer: Mutual information-based disentangled
           reward learning from few demonstrations

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      Authors: Zhongliang Jiang, Yuan Bi, Mingchuan Zhou, Ying Hu, Michael Burke, Nassir Navab
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Ultrasound (US) imaging is widely used for biometric measurement and diagnosis of internal organs due to the advantages of being real-time and radiation-free. However, due to inter-operator variations, resulting images highly depend on the experience of sonographers. This work proposes an intelligent robotic sonographer to autonomously “explore” target anatomies and navigate a US probe to standard planes by learning from the expert. The underlying high-level physiological knowledge from experts is inferred by a neural reward function, using a ranked pairwise image comparison approach in a self-supervised fashion. This process can be referred to as understanding the “language of sonography.” Considering the generalization capability to overcome inter-patient variations, mutual information is estimated by a network to explicitly disentangle the task-related and domain features in latent space. The robotic localization is carried out in coarse-to-fine mode based on the predicted reward associated with B-mode images. To validate the effectiveness of the proposed reward inference network, representative experiments were performed on vascular phantoms (“line” target), two types of ex vivo animal organ phantoms (chicken heart and lamb kidney representing “point” target), and in vivo human carotids. To further validate the performance of the autonomous acquisition framework, physical robotic acquisitions were performed on three phantoms (vascular, chicken heart, and lamb kidney). The results demonstrated that the proposed advanced framework can robustly work on a variety of seen and unseen phantoms as well as in vivo human carotid data. Code: https://github.com/yuan-12138/MI-GPSR. Video: https://youtu.be/u4ThAA9onE0.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-01-16T12:11:10Z
      DOI: 10.1177/02783649231223547
       
  • Lane-level route planning for autonomous vehicles

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      Authors: Mitchell Jones, Maximilian Haas-Heger, Jur van den Berg
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      We present an algorithm that, given a representation of a road network in lane-level detail, computes a route that minimizes the expected cost to reach a given destination. In doing so, our algorithm allows us to solve for the complex trade-offs encountered when trying to decide not just which roads to follow, but also when to change between the lanes making up these roads, in order to—for example—reduce the likelihood of missing a left exit while not unnecessarily driving in the leftmost lane. This routing problem can naturally be formulated as a Markov Decision Process (MDP), in which lane change actions have stochastic outcomes. However, MDPs are known to be time-consuming to solve in general. In this paper, we show that—under reasonable assumptions—we can use a Dijkstra-like approach to solve this stochastic problem, and benefit from its efficient O(n log  n) running time. This enables an autonomous vehicle to exhibit lane-selection behavior as it efficiently plans an optimal route to its destination.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-01-10T09:23:35Z
      DOI: 10.1177/02783649231225474
       
  • Self-reflective terrain-aware robot adaptation for consistent off-road
           ground navigation

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      Authors: Sriram Siva, Maggie Wigness, John G. Rogers, Long Quang, Hao Zhang
      Abstract: The International Journal of Robotics Research, Ahead of Print.
      Ground robots require the crucial capability of traversing unstructured and unprepared terrains and avoiding obstacles to complete tasks in real-world robotics applications such as disaster response. When a robot operates in off-road field environments such as forests, the robot’s actual behaviors often do not match its expected or planned behaviors, due to changes in the characteristics of terrains and the robot itself. Therefore, the capability of robot adaptation for consistent behavior generation is essential for maneuverability on unstructured off-road terrains. In order to address the challenge, we propose a novel method of self-reflective terrain-aware adaptation for ground robots to generate consistent controls to navigate over unstructured off-road terrains, which enables robots to more accurately execute the expected behaviors through robot self-reflection while adapting to varying unstructured terrains. To evaluate our method’s performance, we conduct extensive experiments using real ground robots with various functionality changes over diverse unstructured off-road terrains. The comprehensive experimental results have shown that our self-reflective terrain-aware adaptation method enables ground robots to generate consistent navigational behaviors and outperforms the compared previous and baseline techniques.
      Citation: The International Journal of Robotics Research
      PubDate: 2024-01-06T07:59:32Z
      DOI: 10.1177/02783649231225243
       
 
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  Subjects -> COMPUTER SCIENCE (Total: 2313 journals)
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AUTOMATION AND ROBOTICS (116 journals)                     

Showing 1 - 101 of 101 Journals sorted alphabetically
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 10)
ACM Transactions on Human-Robot Interaction     Open Access   (Followers: 4)
Advanced Robotics     Hybrid Journal   (Followers: 29)
Advances in Computed Tomography     Open Access   (Followers: 2)
Advances in Image and Video Processing     Open Access   (Followers: 27)
Advances in Robotics & Automation     Open Access   (Followers: 12)
Artificial Life and Robotics     Hybrid Journal   (Followers: 17)
Augmented Human Research     Hybrid Journal  
Automated Software Engineering     Hybrid Journal   (Followers: 9)
Automatic Control and Information Sciences     Open Access   (Followers: 4)
Automation and Remote Control     Hybrid Journal   (Followers: 6)
Autonomous Agents and Multi-Agent Systems     Hybrid Journal   (Followers: 9)
Autonomous Robots     Hybrid Journal   (Followers: 11)
Biocybernetics and Biological Engineering     Full-text available via subscription   (Followers: 4)
Biological Cybernetics     Hybrid Journal   (Followers: 10)
Biomimetic Intelligence and Robotics     Open Access  
Cognitive Robotics     Open Access   (Followers: 4)
Computational Intelligence and Neuroscience     Open Access   (Followers: 18)
Computer-Aided Design     Hybrid Journal   (Followers: 9)
Construction Robotics     Hybrid Journal   (Followers: 5)
Current Robotics Reports     Hybrid Journal   (Followers: 4)
Cybernetics & Human Knowing     Full-text available via subscription   (Followers: 3)
Cybernetics and Systems Analysis     Hybrid Journal  
Cybernetics and Systems: An International Journal     Hybrid Journal   (Followers: 1)
Design Automation for Embedded Systems     Hybrid Journal   (Followers: 4)
Digital Zone : Jurnal Teknologi Informasi Dan Komunikasi     Open Access  
Drone Systems and Applications     Open Access   (Followers: 1)
Electrical Engineering and Automation     Open Access   (Followers: 9)
Facta Universitatis, Series : Automatic Control and Robotics     Open Access   (Followers: 1)
Foundations and Trends® in Robotics     Full-text available via subscription   (Followers: 4)
GIScience & Remote Sensing     Open Access   (Followers: 58)
IAES International Journal of Robotics and Automation     Open Access   (Followers: 5)
IEEE Robotics & Automation Magazine     Full-text available via subscription   (Followers: 69)
IEEE Robotics and Automation Letters     Hybrid Journal   (Followers: 9)
IEEE Transactions on Affective Computing     Hybrid Journal   (Followers: 23)
IEEE Transactions on Audio, Speech, and Language Processing     Hybrid Journal   (Followers: 17)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 70)
IEEE Transactions on Cybernetics     Hybrid Journal   (Followers: 16)
IEEE Transactions on Intelligent Vehicles     Hybrid Journal   (Followers: 2)
IEEE Transactions on Medical Robotics and Bionics     Hybrid Journal   (Followers: 5)
IEEE Transactions on Neural Networks and Learning Systems     Hybrid Journal   (Followers: 57)
IEEE Transactions on Robotics     Hybrid Journal   (Followers: 71)
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews     Hybrid Journal   (Followers: 16)
IET Cyber-systems and Robotics     Open Access   (Followers: 2)
IET Systems Biology     Open Access   (Followers: 1)
Industrial Robot An International Journal     Hybrid Journal   (Followers: 2)
Intelligent Control and Automation     Open Access   (Followers: 6)
Intelligent Service Robotics     Hybrid Journal   (Followers: 2)
International Journal of Adaptive, Resilient and Autonomic Systems     Full-text available via subscription   (Followers: 3)
International Journal of Advanced Pervasive and Ubiquitous Computing     Full-text available via subscription   (Followers: 4)
International Journal of Advanced Robotic Systems     Full-text available via subscription   (Followers: 1)
International Journal of Agent Technologies and Systems     Full-text available via subscription   (Followers: 4)
International Journal of Ambient Computing and Intelligence     Full-text available via subscription   (Followers: 3)
International Journal of Applied Evolutionary Computation     Full-text available via subscription   (Followers: 3)
International Journal of Artificial Life Research     Full-text available via subscription  
International Journal of Automation and Control     Hybrid Journal   (Followers: 11)
International Journal of Automation and Control Engineering     Open Access   (Followers: 5)
International Journal of Automation and Logistics     Hybrid Journal   (Followers: 4)
International Journal of Automation and Smart Technology     Open Access   (Followers: 3)
International Journal of Bioinformatics Research and Applications     Hybrid Journal   (Followers: 14)
International Journal of Biomechatronics and Biomedical Robotics     Hybrid Journal   (Followers: 2)
International Journal of Humanoid Robotics     Hybrid Journal   (Followers: 6)
International Journal of Imaging & Robotics     Full-text available via subscription   (Followers: 3)
International Journal of Intelligent Information Technologies     Full-text available via subscription   (Followers: 1)
International Journal of Intelligent Machines and Robotics     Hybrid Journal   (Followers: 3)
International Journal of Intelligent Mechatronics and Robotics     Full-text available via subscription   (Followers: 5)
International Journal of Intelligent Robotics and Applications     Hybrid Journal  
International Journal of Intelligent Systems Design and Computing     Hybrid Journal   (Followers: 2)
International Journal of Intelligent Unmanned Systems     Hybrid Journal   (Followers: 3)
International Journal of Machine Consciousness     Hybrid Journal   (Followers: 7)
International Journal of Machine Learning and Cybernetics     Hybrid Journal   (Followers: 31)
International Journal of Mechanisms and Robotic Systems     Hybrid Journal   (Followers: 2)
International Journal of Mechatronics and Automation     Hybrid Journal   (Followers: 5)
International Journal of Robotics and Automation     Full-text available via subscription   (Followers: 8)
International Journal of Robotics and Control     Open Access   (Followers: 3)
International Journal of Robotics Applications and Technologies     Full-text available via subscription   (Followers: 1)
International Journal of Robotics Research     Hybrid Journal   (Followers: 15)
International Journal of Space-Based and Situated Computing     Hybrid Journal   (Followers: 2)
International Journal of Synthetic Emotions     Full-text available via subscription  
International Journal of Tomography & Simulation     Full-text available via subscription   (Followers: 1)
Journal of Automation and Control     Open Access   (Followers: 9)
Journal of Computer Assisted Tomography     Hybrid Journal   (Followers: 2)
Journal of Control & Instrumentation     Full-text available via subscription   (Followers: 19)
Journal of Control, Automation and Electrical Systems     Hybrid Journal   (Followers: 11)
Journal of Intelligent and Robotic Systems     Hybrid Journal   (Followers: 6)
Journal of Intelligent Learning Systems and Applications     Open Access   (Followers: 4)
Journal of Robotic Surgery     Hybrid Journal   (Followers: 3)
Jurnal Otomasi Kontrol dan Instrumentasi     Open Access  
Machine Translation     Hybrid Journal   (Followers: 12)
Proceedings of the ACM on Human-Computer Interaction     Hybrid Journal   (Followers: 2)
Results in Control and Optimization     Open Access   (Followers: 5)
Revista Iberoamericana de Automática e Informática Industrial RIAI     Open Access  
ROBOMECH Journal     Open Access   (Followers: 1)
Robotic Surgery : Research and Reviews     Open Access   (Followers: 1)
Robotica     Hybrid Journal   (Followers: 5)
Robotics and Autonomous Systems     Hybrid Journal   (Followers: 19)
Robotics and Biomimetics     Open Access   (Followers: 1)
Robotics and Computer-Integrated Manufacturing     Hybrid Journal   (Followers: 7)
Science Robotics     Full-text available via subscription   (Followers: 11)
Unmanned Systems     Hybrid Journal   (Followers: 4)
Wearable Technologies     Open Access   (Followers: 4)

           

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