Subjects -> COMPUTER SCIENCE (Total: 2313 journals)
    - ANIMATION AND SIMULATION (33 journals)
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    - AUTOMATION AND ROBOTICS (116 journals)
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AUTOMATION AND ROBOTICS (116 journals)                     

Showing 1 - 103 of 103 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: 28)
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 Biomechanical Engineering     Full-text available via subscription   (Followers: 12)
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)
Soft Robotics     Hybrid Journal   (Followers: 5)
Unmanned Systems     Hybrid Journal   (Followers: 4)
Wearable Technologies     Open Access   (Followers: 4)

           

Similar Journals
Journal Cover
International Journal of Intelligent Robotics and Applications
Number of Followers: 0  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2366-5971 - ISSN (Online) 2366-598X
Published by Springer-Verlag Homepage  [2468 journals]
  • Redundancy resolution of a mobile manipulator using the KSOM based
           learning algorithm

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      Abstract: Abstract A learning-based strategy for the trajectory tracking of redundant mobile manipulators (MM) was presented in this study. A five-degrees-of-freedom (DOF) manipulator is mounted on the differential drive (DD) mobile robot. The advantage of using a redundant system is to avoid joint limits, obstacles, and singularities towards desired trajectory tracking. The proposed approach is based on the Kohonen Self-Organizing Map (KSOM) advanced with Weighted Least Norm (WLN) matrix algorithm. This approach is the recommended neural network for inverse kinematics solutions because of its stability, preserved topology, and capacity to optimize the joint space trajectory while producing a smooth minimal joint angle. A proposed method for redundancy resolution in MM has been simulated using MATLAB simulation code and the Gazebo real-time simulation physical environment. The simulation results are evaluated with the joint limit method of redundancy resolution and other existing controllers for verification purposes. The conventional method of redundancy resolution is local optimum and infeasible for the end-effector motion in the entire workspace. The KSOM uses different steps of error correction that improve the system’s performance as well as ensure the global asymptotical stability of the system. The Root Mean Square Error (RMSE) values for straight-line, circular, Lissajious, and irregular sinusoidal path motions of the proposed method using KSOM are given as 0.0095 m, 0.009945 m, 0.009897 m, and 0.009758 m, respectively. The simulation results of the proposed method confirm the effectiveness of the proposed approach.
      PubDate: 2024-07-25
       
  • Neural admittance control based on motion intention estimation and force
           feedforward compensation for human–robot collaboration

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      Abstract: Abstract To enhance robotic manipulator adaptation to human partners and minimize human energy consumption in human–robot collaboration, this paper introduces a neural admittance control framework, which integrates human motion intention estimation and force feedforward compensation. Maximum likelihood estimation is employed to derive human motion intention and stiffness within human–robot collaboration, which are seamlessly merged into admittance control. Force feedforward compensation is proposed to minimize interaction force and position tracking fluctuations based on estimated human intention and stiffness. RBF neural network control is used to refine position inner loop dynamics and to improve position tracking accuracy and response speed. Comprehensive comparative simulations validate the method’s effectiveness in diminishing human–robot interaction force, enhancing position response speed, and mitigating interaction force and position fluctuations. The experiment performed on the Franka Emika Panda robot platform, illustrates that the proposed method is effective and enhance human-robot collaboration.
      PubDate: 2024-07-22
       
  • Multiobjective optimization-based trajectory planning for laser 3D scanner
           robots

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      Abstract: Abstract In our industrial material defect detecting processes, the multi criteria is considered in two-level motion planning structure. Firstly, the feed speed of the end-effector should be programmed in optimal time for satisfying the requirement of high efficiency. Secondly, the planned joint velocities and accelaration are characterized by high-order derivatives to guarantee smooth motion, taking into account the kinematic constraints. Last but not least, energy consumption of the robot’s movement is a focus during designing trajectories. The Pareto optimal method is applied to solve the trajectory planning problem. The results of the experiments suggest that the Pareto approach can realize effective multi-objective optimization and deliver a group of Pareto solutions for decision makers. Based on the actual requirements, suitable Pareto-optimal trajectory can be achieved and the practical operation of the industrial robot is good.
      PubDate: 2024-07-13
       
  • Development of a leech-inspired peristaltic crawling soft robot for
           intestine inspection

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      Abstract: Abstract The development of a non-destructive and patient-friendly method for examining the intestines is crucial for early prevention and timely diagnosis of prevalent intestinal diseases that pose a threat to human health worldwide. Although the soft robot shows promise as an examination method due to its safe human-machine interaction and high maneuverability, achieving controlled and non-damaging movements within the flexible and delicate structure of the intestines remains a significant challenge. In this study, we propose and design a leech-inspired soft robot capable of operating in an intestine-like environment while ensuring lossless and controllable functionality. The soft robot consists of two dual-chambered adsorption actuators serving as “feet” and a retractable actuator as the body, enabling the robot to crawl by programmatically controlling the alternating movements of the adsorption actuators and the cooperation of the retractable actuator. Through numerical simulations, and movement tests in various scenarios such as planes, slopes, and intestine-like pipelines, we verified the adsorption characteristics and regulation mechanism of the adsorption actuator, as well as the movement performance of the robot. The results demonstrate that the adsorption actuator achieves a maximum adsorption force of 3.17 N, and the soft robot attains a maximum moving speed of 9.29 mm/s. This research offers a non-destructive and patient-friendly approach that holds promise for the detection and treatment of intestinal diseases in practical applications.
      PubDate: 2024-07-08
       
  • Review of vision-based reinforcement learning for drone navigation

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      Abstract: Abstract In recent years, Unmanned aerial vehicles (UAVs) have witnessed a surge in popularity and implementation for both civilian and military usage. UAVs can be utilized for a wide range of applications, including mapping, surveillance, and inspection. For many of these applications, a high level of autonomy is required. Autonomy refers to the ability to complete missions or tasks without human intervention. Autonomous navigation is an essential element of autonomy, especially in GPS-denied environments where GNSS-based navigation is not reliable. Due to size and weight limitations, many UAVs employ vision-based localization and navigation techniques for GPS-denied environments. Reinforcement Learning (RL) is also increasingly being implemented for robotic applications, including obstacle avoidance, battery management, and navigation. Existing reviews typically focus on either vision-based autonomous navigation of drones or RL navigation for drones in general, but none specifically concentrate on the use of vision-based methods and RL for drone navigation. Moreover, previous reviews have highlighted the use of reinforcement learning based on tasks such as takeoff, landing, and navigation, whereas this review categorizes the use of RL based on the navigation problem and image input types for the RL models as these define the needed hardware and processing capabilities of the system. We define the current challenges and limitations for vision based RL navigation to provide direction for future works. Finally we provide an analysis of the favorable conditions for each category and the possibility of combining multiple categories to overcome the disadvantages of each.
      PubDate: 2024-06-28
       
  • A human–robot interaction control strategy for teleoperation robot
           system under multi-scenario applications

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      Abstract: Abstract The teleoperation robot system (TRS) stands as a prominent research frontier within robot control, amalgamating human decision-making capacity with robot operation, thus markedly enhancing safety and precision compared to autonomous operation. This paper selects TRS hardware and designs master–slave interaction software comprising six distinct modules tailored to diverse functionalities. It further derives forward and backward kinematic equations based on master–slave device linkage parameters, proposing a Cartesian workspace-based master–slave mapping algorithm. Additionally, a human–robot interaction (HRI) control framework emphasizing direct force feedback is devised to bolster system HRI performance and operator immersion. To ensure smooth, safe, and agile slave device movement, an innovative impedance controller-based TRS force feedback HRI control framework is introduced. The effectiveness of the TRS HRI control framework is validated via comprehensive experiments conducted across multiple scenarios, including remote robot axle-hole assembly, blackboard erasing, text writing, and auxiliary welding operations, on a constructed experimental platform for robot remote operation system HRIs.
      PubDate: 2024-06-27
       
  • Nonlinear modeling and designing transition flight control scenarios for a
           dual thrust hybrid UAV

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      Abstract: Abstract Researchers have recently focused on studying the flight dynamics and control of multicopters and fixed-wing aerial vehicles. However, investigating the transition phase between multicopter hover and fixed-wing cruise modes for a Dual-thrust Aerial Vehicle (DAV) is still challenging. In this paper, we develop two sets of nonlinear equations of motion for a DAV to create a multi-purpose dynamic model for designing control and transition mode scenarios. The first set considers the multicopter torque as the control input, while the second set considers the elevator torque as the control input. By analyzing three transition scenarios between multicopter hover and fixed-wing cruise flights, we observe that the best performance occurs for the third scenario in which the control system switches from multicopter control torque to elevator control torque when the multicopter thrust equals the wings’ lift. In this case, the vehicle will be protected from critical flight conditions like wing stalls while the transition will go smoothly with minimum height drop. The transition mode strategies are implemented using a model predictive controller in flight simulation. The numerical results show the dynamic behavior of the DAV in different transition scenarios from hover to cruise and vice versa, demonstrating successful altitude control and stable transitions in both phases.
      PubDate: 2024-06-27
       
  • Implementation of extended kalman filter for localization of ambulance
           robot

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      Abstract: Abstract This paper focuses on the implementation of the Extended Kalman Filter for indoor localization of a semi-autonomous Ambulance Robot system named Ambubot. The system is designed to reduce the response time for lay rescuers to locate an Automated External Defibrillator (AED) during sudden cardiac arrest events. To achieve this objective, the robot is equipped with an AED, and the Extended Kalman Filter is utilized for optimal indoor localization. The filter is implemented using data from the robot’s Inertial Measurement Unit, which comprises 9 Degrees of Freedom. The paper provides an explicit description of the performance of the Extended Kalman Filter in estimating the position of Ambubot, and demonstrates that the proposed approach is effective in accurately determining and estimating the robot’s position in unknown indoor environments. The results suggest that the proposed method is a promising solution for improving survival rates in cardiac arrest cases, and may have potential applications in other fields where accurate indoor localization is required.
      PubDate: 2024-06-25
       
  • Example-driven trajectory learner for robots under structured static
           environment

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      Abstract: Abstract With the breakthroughs in machine learning and computing infrastructures that have led to significant performance improvements in cognitive robotics, the challenge of continuous-trajectory task creation persists. This challenge stems from the need to account for inter-joint relationships, which define constraints between different robot joints due to the kinematic structure, and intra-joint relationships, which are constraints within a single joint like limits. Accounting for these coupled, nonlinear inter-joint and intra-joint relationships is crucial for trajectory planning. However, various constraints in the physical capability of robots, environmental changes, and long-time reliance on sequential dependencies between these inter-joint and intra-joint relationships make the work of modifying robot trajectories exceptionally hard. Many robot environments function under structured static work-cell completing extended series of subtasks. The conventional descriptors for robot trajectory rely on symbolic rules with human intelligence, which involves skilled individuals and possesses significant limitations, such as being time-consuming and exhibiting low flexibility even for minor changes, due to the static nature of task descriptions alone. The suggested technique employs a probabilistic network and data-efficient modelling termed generative adversarial networks, which learns the underlying constraints, probability distributions and arbitrations, along with generating trajectory instances at each time of sampling. Integrating prior knowledge into the symbolic trajectory learner as a dataset facilitates the learning process. The model assessment was carried out by utilising a custom-built dataset in a simulation based environment. This research also proposed two GAN inversion methods to compute the generated trajectory and its closest instance in the dataset. Furthermore, GAN Inversion method I and II calculated the robot path accuracy in extrinsic generative models yielded path position accuracy of 9.2 cm and 4.9 cm respectively. In addition to that, the study contributes a probabilistic model for interpolating between various trajectories to generate new trajectories.
      PubDate: 2024-06-21
       
  • Design optimisation and an experimental assessment of soft actuator for
           robotic grasping

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      Abstract: Abstract Many robotic systems face substantial challenges when trying to grasp and manipulate objects. Thought of initially as humanoid automata a century ago, this viewpoint is still influential in modern robot design. Many robotic grippers are inspired by the deftness of the human hand. The perceptual, processing, and control issues that conventional grippers have are also experienced by soft-fingered grippers. Precise finger placement, dictated by the shape and attitude of the object, is necessary to accomplish force closure when using soft fingertips to grasp. Soft robotic end-effectors have several advantages, such as a good interface with humans, the capacity to adapt to different environments, a number of degrees of freedom, and the ability to non-destructively grasp items of various shapes. Adding to earlier research that looked at the soft robot in a theoretical way, this study creates an optimized model based on the deformation in terms of bending of the channel cavity under applied pneumatic pressure. A correlation between pneumatic pressure and the pneumatic soft actuator's bending angle has been demonstrated. This research looks at how different design factors affect the bending of a multi-chambered soft actuator that is pneumatically networked. The finite element approach involves fine-tuned (optimised) actuator construction. Using FEM to evaluate aspects affecting actuator mechanical output, the ideal design parameters were discovered using DoE, resulting in a bending angle of ~ 104 degrees at 30 kPa. This study used ANOVA at a 5% significant level to identify which variables most affected the pneumatic actuator's deformation (bending angle). The significant R-square value of 96.42% supports the study's conclusions that the parameters utilised explain an immense percentage of bending angle deviations. Experimental verification of the optimized finite element model findings was conducted. The verification of the actuators' bending angles and output forces reveals that the discrepancy between the two sets of data stayed below 9%. Also, the average gripping success rate attained in the grasping evaluation, which involved four distinct types of items, was almost 97%.
      PubDate: 2024-06-20
      DOI: 10.1007/s41315-024-00355-w
       
  • Predicting the robot's grip capacity on different objects using
           multi-object grasping

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      Abstract: Abstract This study explores the novel concept of Multi-Object Grasping (MOG) and develops an architecture based on autoencoders and transformers for accurate object prediction in MOG scenarios. The approach employs different deep learning methods and diverse training approaches using the ping pong ball dataset. The parameters obtained from this training enhance the model's performance on the actual system dataset, serving as the final test and validation of the model's reliability in real-world situations. Comparing the model's performance on both datasets facilitates validation and refinement, affirming its effectiveness in practical robotic applications. The study highlights that training various dataset features significantly improves prediction accuracy compared to the Naïve model using dense neural networks. Using five-time steps notably enhances prediction accuracy, especially with the GRU model in time-series data architecture, achieving a peak accuracy of 96%. While MOG has been extensively studied, this study introduces a novel architecture distinct from traditional visual methods. A framework is established that utilizes autoencoder and transformer technologies for managing tactile sensors, hand pose joint angles and force measurements. This approach demonstrates the potential for accurately predicting multiple objects in MOG scenarios.
      PubDate: 2024-06-19
      DOI: 10.1007/s41315-024-00342-1
       
  • ROS-based multi-sensor integrated localization system for cost-effective
           and accurate indoor navigation system

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      Abstract: Abstract Accurate localization is essential for enabling intelligent autonomous navigation in indoor environments. While global navigation satellite systems (GNSS) provide efficient outdoor solutions, applications in indoor environments require alternative approaches to determine the vehicle's global position. This study investigates a ROS-based multi-sensor integrated localization system utilizing wheel odometry, inertial measurement unit (IMU), and 2D light detection and ranging (LiDAR) based simultaneous localization and mapping (SLAM) for cost-effective and accurate indoor autonomous vehicle (AV) navigation. The paper analyzes the limitations of wheel odometry and IMU, highlighting their susceptibility to errors. To address these limitations, the proposed system leverages LiDAR SLAM for real-time map generation and pose correction. The Karto SLAM package from robot operating system (ROS) is chosen due to its superior performance according to the literature. Results indicate that the integration of these technologies reduces localization errors significantly, with the system achieving a high degree of accuracy in pose estimation under various test conditions. The experimental validation shows that the proposed system maintains consistent performance, proving its potential for widespread application in environments where GNSS is unavailable.
      PubDate: 2024-06-05
      DOI: 10.1007/s41315-024-00350-1
       
  • Automated classification of electrical network high-voltage tower
           insulator cleanliness using deep neural networks

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      Abstract: Abstract String insulators are components in high-voltage towers responsible for preventing energy dissipation through the tower structure; that is, they are responsible for isolating the high voltage in the electrical network cables. These string insulators must be clean for best performance and to avoid malfunctions. Verifying the necessity for cleaning/washing is most often performed by human visual observation, which can lead to interpretation errors, in addition to bringing risks to the physical integrity of humans in the vicinity of these electrical systems. Thus, this paper aims to develop an algorithm to detect and classify these insulators. The proposed algorithm uses artificial intelligence techniques and analyzes the image, inferring the state of cleanliness of the analyzed insulator. For the development of this algorithm, it was necessary to build a synthetic database using CAD software such as Inventor and Unity-3D due to image limitations available from dirty insulator strings. In this paper, two distinct neural networks are built using supervised learning techniques, where the first one is for detecting the chain of insulators, and the second is for detecting the type of dirt on the disk surface. In the first stage, techniques that use supervised learning are studied, more aimed explicitly at semantic segmentation networks, and in the second stage, classification deep neural networks were used to detect the type of impurities. In detecting insulator strings, an average dice coefficient of 0.95 was achieved for simulated images and 0.92 for natural images, with learning parameters based on a database with only simulated images. The average accuracy obtained in the dirt classification stage was 0.98.
      PubDate: 2024-06-04
      DOI: 10.1007/s41315-024-00349-8
       
  • Nonlinear modelling and dynamics of spatial multi-link rigid-flexible
           manipulator with moving platform

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      Abstract: Abstract The demand for developing lighter manipulators, particularly in various long-reach applications, has surged significantly. In many of these applications, inherent structural flexibilities are unavoidable and lead to vibrations. Consequently, these residual vibrations detrimentally affect working efficiency and positioning accuracy. The present work introduces a novel approach by formulating a nonlinear dynamical model of a spatial multi-link manipulator mounted on a mobile platform. This model incorporates both rigid and flexible links, as well as the payload, enabling a comprehensive study of end-point residual vibration characteristics. The dynamic modeling employed in this study accounts for the interplay of coupled geometric and inertial nonlinearities arising from motion interactions among joints, actuators, and elastic link deflections. The manipulator configuration comprises rigid components and two 3D-flexible links actuated by prismatic and revolute joints, respectively. The flexible links are modelled using Euler–Bernoulli beam elements, while time-dependent in-plane motion is imparted to the rigid link. Utilizing Hamilton’s variational principle, a set of nonlinear governing equations of motion is analytically derived. Subsequently, an independent generalized coordinates system is adopted to transform the equations of motion into a nonlinear reduced form. This is achieved through discretization of the spatio-temporal equations, facilitating the analysis of trajectory dynamics for the robotic manipulator. The residual vibration characteristics at the payload end were explored graphically by applying generalized sinusoidal and bang-bang torque profiles to their respective joints. Nonlinear structural flexibility and material properties emerge as pivotal factors influencing these residual end-point vibrations. It has been observed that the bang-bang torque profile extends the settling period in residual vibration due to its intricate transition characteristics, in contrast to the sinusoidal motion profile with a specific torque duty cycle. Numerical simulations highlight that variations in physical and geometric variables significantly impact end-point residual vibrations and joint deflections, potentially leading to positioning errors in the control of spatial flexible manipulators.
      PubDate: 2024-06-02
      DOI: 10.1007/s41315-024-00344-z
       
  • Robust tracking control of a three-degree-of-freedom robot manipulator
           with disturbances using an integral sliding mode controller

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      Abstract: Abstract Robot systems often face highly nonlinear manipulator dynamics and uncertainties such as external disturbances, payload variations, and end effector modeling errors. Therefore, it is of great industrial importance to compute and simulate the dynamic response of these manipulators in a reliable manner. This research investigates a robust control strategy—Integral Sliding Mode Control (ISMC)—applied to a three-degree-of-freedom robot manipulator with external disturbances. The study consists of two stages. The first stage uses Proportional-Derivative (PD) control with dynamically calculated weight values in the absence of the external disturbances. In the second stage, ISMC is employed to address dynamic responses to disturbances. The computation work on the model is implemented in Mathematica software, and a three-joint SCARA-type robot is tested to demonstrate methodology robustness. In the end, stability is ensured through Lypunove function analysis and the sliding surface's phase portrait.
      PubDate: 2024-06-01
      DOI: 10.1007/s41315-023-00312-z
       
  • Investigation on robotic cells design improvement in the welding process
           of body in white

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      Abstract: Abstract Issues about cycle time optimization is of great importance in the field of automotive production, the industrial robots are widely used in the welding process of automobiles, but there is little research on the optimization of intra station rhythm during the design phase. By conducting research on workstation with industrial robot processing as key process, this paper carries out analysis from the selection of equipment layout within the workstation, planning production rhythm, and the facility performance analysis within the workstation. The finding shows the cycle time within the workstation has been reduced by 12 s. This article aims at improving the rhythm of robotic cells in complex production environment, and raising production efficiency of workstation. The robot path is optimized by using intelligent algorithms, the human machine collaborative work has been validated in virtual scenes, some digital design is adopted for modelling and simulating, the designed workstation has been verified from multiple perspectives, and finally achieve the workstation design of applying industrial robots in the production scenario.
      PubDate: 2024-06-01
      DOI: 10.1007/s41315-023-00317-8
       
  • Optimizing IRB1410 industrial robot painting processes through Taguchi
           method and fuzzy logic integration with machine learning

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      Abstract: Abstract Robot-based painting industries optimize operations and enhance product quality by leveraging insights from real and virtual studies, encompassing trajectory patterns, paint film qualities, and machine learning for fault identification. Automation of fault identification procedures is the novel aspect of the study that helps to reduce human error and maintain consistent quality standards in manufacturing. This in-depth investigation examines the analysis of paint paths for robot painting with a focus on three distinctive movement patterns: linear, circular, and zigzag. The investigation includes assessments of smoothness for each route, along with morphological evaluations using Scanning Electron Microscope (SEM) pictures. The surface quality is assessed methodically using Taguchi L9 orthogonal testing, while Analysis of Variance (ANOVA) is utilised to identify the key factors that contribute to variations in paint qualities. In order to enhance quality control, machine learning is included to automate the classification and identification of flaws, utilising sophisticated picture analysis techniques. It is essential to incorporate virtual-environment experiments to ensure the accuracy and applicability of the results in real-world situations. This technique reveals crucial observations on the temporal difference between virtual and real surroundings, providing significant information for enhancing the painting process to better match the actual operational parameters. In addition, the analysis determines that the best combination of roughness is A3B3C2 using the Taguchi method, which results in an outstanding finish with a roughness value of 0.0347 µm. Verifying the efficacy of cutting-edge technology in honing painting techniques and improving end product quality, the machine learning model demonstrates a remarkable 94% accuracy in real-time flaw detection.
      PubDate: 2024-06-01
      DOI: 10.1007/s41315-024-00325-2
       
  • References tracking and perturbations reconstruction in a Cartesian robot

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      Abstract: Abstract An exosystem needs to be nonlinear when it generates the perturbations to be reconstructed; however, an exosystem does not need to be nonlinear when it generates the references to be tracked. Resulting that the tracking of the references generated by an exosystem is an easier task. Hence, some studies on the references tracking should be made. Furthermore, to solve the references tracking, the perturbations are needed. In this research, the references tracking and the perturbations reconstruction in a Cartesian robot are discussed. For the perturbations reconstruction, an estimator is defined to force the reconstructed perturbations to track the perturbations of a Cartesian robot model. For the references tracking, a controller is defined to force a Cartesian robot model to track an exosystem. A theorem is addressed to prove the perturbations reconstruction. A theorem is addressed to prove the references tracking. A simulation in a Cartesian robot is used to confirm the validity and effectiveness of our controller with estimator in comparison with a feedback controller.
      PubDate: 2024-06-01
      DOI: 10.1007/s41315-023-00315-w
       
  • Focused section on new trends on intelligent automation by industrial
           robots

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      Abstract: Abstract Industrial robots have been widely used in manufacturing automobiles and consumable electronics, logistics, biomedical engineering, and many other industrial sectors. However, the need to enhance their adaptability, accuracy, and autonomy remains high, enabling them to be competent in advanced application scenarios, such as human–robot collaboration, flexible manufacturing, precision engineering, and large-scale automation. This focused section competitively selects the 10 research papers to disseminate new design, planning, and control methodologies of industrial robots toward intelligent automation.
      PubDate: 2024-05-31
      DOI: 10.1007/s41315-024-00348-9
       
  • A state-of-the-art review on topology and differential geometry-based
           robotic path planning—part II: planning under dynamic constraints

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      Abstract: Abstract Path planning is an intrinsic component of autonomous robotics, be it industrial, research or consumer robotics. Such avenues experience constraints around which paths must be planned. While the choice of an appropriate algorithm is application-dependent, the starting point of an ideal path planning algorithm is the review of past work. Historically, algorithms were classified based on the three tenets of autonomous robotics which are the ability to avoid different constraints (static/dynamic), knowledge of the environment (known/unknown) and knowledge of the robot (general/model specific). This division in literature however, is not comprehensive, especially with respect to dynamics constraints. Therefore, to remedy this issue, we propose a new taxonomy, based on the fundamental tenet of characterizing space, i.e., as a set of distinct, unrelated points or as a set of points that share a relationship. We show that this taxonomy is effective in addressing important parameters of path planning such as connectivity and partitioning of spaces. Therefore, path planning spaces may now be viewed either as a set of points or, as a space with structure. The former relies heavily on robot models, since the mathematical structure of the environment is not considered. Thus, the approaches used are variants of optimization algorithms and specific variants of model-based methods that are tailored to counteract effects of dynamic constraints. The latter depicts spaces as points with inter-connecting relationships, such as surfaces or manifolds. These structures allow for unique characterizations of paths using homotopy-based methods. The goals of this work, viewed specifically in light with dynamic constraints, are therefore as follows: First, we propose an all-encompassing taxonomy for robotic path planning literature that considers an underlying structure of the space. Second, we provide a detailed accumulation of works that do focus on the characterization of paths in spaces formulated to show underlying structure. This work accomplishes the goals by doing the following: It highlights existing classifications of path planning literature, identifies gaps in common classifications, proposes a new taxonomy based on the mathematical nature of the path planning space (topological properties), and provides an extensive conglomeration of literature that is encompassed by this new proposed taxonomy.
      PubDate: 2024-03-25
      DOI: 10.1007/s41315-024-00331-4
       
 
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  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 - 103 of 103 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: 28)
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 Biomechanical Engineering     Full-text available via subscription   (Followers: 12)
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)
Soft Robotics     Hybrid Journal   (Followers: 5)
Unmanned Systems     Hybrid Journal   (Followers: 4)
Wearable Technologies     Open Access   (Followers: 4)

           

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JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


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