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Industrial Robot An International Journal
Journal Prestige (SJR): 0.318

Citation Impact (citeScore): 1
Number of Followers: 2

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0143-991X - ISSN (Online) 1758-5791
Published by Emerald

[362 journals]

An effective trajectory scheduling method for a 5-DOF hybrid machining
robot
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  Authors: Haitao Liu, Junfu Zhou, Guangxi Li, Juliang Xiao, Xucang Zheng
  Abstract: This paper aims to present a new trajectory scheduling method to generate a smooth and continuous trajectory for a hybrid machining robot. The trajectory scheduling method includes two steps. First, a G3 continuity local smoothing approach is proposed to smooth the toolpath. Then, considering the tool/joint motion and geometric error constraints, a jerk-continuous feedrate scheduling method is proposed to generate the trajectory. The simulations and experiments are conducted on the hybrid robot TriMule-800. The simulation results demonstrate that this method is effectively applicable to machining trajectory scheduling for various parts and is computationally friendly. Moreover, it improves the robot machining speed and ensures smooth operation under constraints. The results of the S-shaped part machining experiment show that the resulting surface profile error is below 0.12 mm specified in the ISO standard, confirming that the proposed method can ensure the machining accuracy of the hybrid robot. This paper implements an analytical local toolpath smoothing approach to address the non-high-order continuity problem of the toolpath expressed in G code. Meanwhile, the feedrate scheduling method addresses the segmented paths after local smoothing, achieving smooth and continuous trajectory generation to balance machining accuracy and machining efficiency.
  Citation: Industrial Robot
  PubDate: 2024-08-27
  DOI: 10.1108/IR-04-2024-0151
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
High climbing and obstacle-crossing performance intelligent tracked
inspection robot for cable trenches
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  Authors: Linjie Dong, Renfei Zhang, Xiaohan Liu, Jie Li, Xingsong Wang, Tian Mengqian
  Abstract: Regular cable trench inspection is crucial, and robotics automation provides an efficient and safer alternative to manual labor. However, existing robots have limited capabilities in traversing obstacles and lack a mechanical arm for detecting cables and equipment. This study aims to develop an intelligent robot for cable trench inspection, enhancing obstacle-crossing abilities and incorporating a mechanical arm for inspection tasks. This study presents an intelligent robot for cable trench inspection, featuring a six-degree-of-freedom mechanical arm mounted on a six-track chassis with four flippers. The robot's climbing and obstacle-crossing stability, as well as the motion range of the mechanical arm, are analyzed. The positioning, navigation and remote monitoring systems are developed. Experiments, including climbing and obstacle-crossing performance tests, along with navigation and positioning system tests, are conducted. Finally, the robot's practicability is verified through field testing. Equipped with flipper tracks, the cable trench inspection robot can traverse obstacles up to 30 cm high and maintain stable locomotion on 30° slopes. Its navigation system enables autonomous operation, while the mechanical arm performs cable current detection tasks. The remote monitoring system provides comprehensive control of the robot and environmental parameter monitoring in cable trenches. The front and rear flipper tracks enhance the robot's ability to traverse obstacles in cable trenches. The mechanical arm addresses cable current and equipment contact detection issues. The navigation and remote monitoring systems improve the robot's autonomous operation and environmental monitoring capabilities. Implementing this robot can advance the automation and intelligence of cable trench inspections.
  Citation: Industrial Robot
  PubDate: 2024-08-27
  DOI: 10.1108/IR-04-2024-0184
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Developments in robotic teleoperation
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  Authors: Rob Bogue
  Abstract: The aim of this article is to provide details of recent technological developments in robotic teleoperation. Following a short introduction, the two main sections of this article provide examples of recent research involving the application of virtual reality and haptic technologies, respectively, to robotic teleoperation. Brief conclusions are drawn. Teleoperation systems are being developed which incorporate virtual reality and haptic feedback technologies. Those using virtual reality seek to enhance the operator’s feeling of immersion in the scene and improve their situation awareness and trials involving diverse tasks illustrate that the technology can achieve these aims and overcome many limitations of traditional systems. Haptic feedback further enhances the degree of operator involvement and control and is now being adopted in commercial minimally invasive surgical systems. Systems which combine virtual reality with haptic feedback are being developed and have the potential to allow operators to conduct increasingly complex tasks. Through reference to recent research, this illustrates how virtual reality and haptic technologies are enhancing the capabilities of robotic teleoperation.
  Citation: Industrial Robot
  PubDate: 2024-08-27
  DOI: 10.1108/IR-08-2024-0358
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Design and analysis of wheel-tracked composite magnetic adsorption
wall-climbing robot
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  Authors: Minglong Xu, Song Xue, Qionghua Wang, Shaoxiang He, Rui Deng, Zenong Li, Ying Zhang, Qiankun Li, Rongchao Li
  Abstract: This study aims to improve the stability and obstacle surmounting ability of the traditional wall-climbing robot on the surface of the ship, a wheel-track composite magnetic adsorption wall-climbing robot is proposed in this paper. The robot adopts a front and rear obstacle-crossing mechanism to achieve a smooth crossover. The robot is composed of two passive obstacle-crossing mechanisms and a frame, which is composed of two obstacle-crossing magnetic wheels and a set of tracks. The obstacle-crossing is realized by the telescopic expansion of the obstacle-crossing mechanism. Three static failure models are established to determine the minimum adsorption force for the robot to achieve stable motion. The Halbach array is used to construct the track magnetic circuit, and the influence of gap, contact area and magnet thickness on the adsorption force is analyzed by parameter simulation. The prototype was designed and manufactured by the authors for static failure and obstacle crossing tests. The prototype test results show that the robot can cross the obstacle of 10 mm height under the condition of 20 kg load. A new structure of wall-climbing robot is proposed and verified. According to the test results, the wall-climbing robot can stably climb over the obstacle of 10 mm height under the condition of 20 kg load, which provides a new idea for future robot design.
  Citation: Industrial Robot
  PubDate: 2024-08-22
  DOI: 10.1108/IR-04-2024-0173
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Visual SLAM algorithm in dynamic environment based on deep learning
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  Authors: Yingjie Yu, Shuai Chen, Xinpeng Yang, Changzhen Xu, Sen Zhang, Wendong Xiao
  Abstract: This paper proposes a self-supervised monocular depth estimation algorithm under multiple constraints, which can generate the corresponding depth map end-to-end based on RGB images. On this basis, based on the traditional visual simultaneous localisation and mapping (VSLAM) framework, a dynamic object detection framework based on deep learning is introduced, and dynamic objects in the scene are culled during mapping. Typical SLAM algorithms or data sets assume a static environment and do not consider the potential consequences of accidentally adding dynamic objects to a 3D map. This shortcoming limits the applicability of VSLAM in many practical cases, such as long-term mapping. In light of the aforementioned considerations, this paper presents a self-supervised monocular depth estimation algorithm based on deep learning. Furthermore, this paper introduces the YOLOv5 dynamic detection framework into the traditional ORBSLAM2 algorithm for the purpose of removing dynamic objects. Compared with Dyna-SLAM, the algorithm proposed in this paper reduces the error by about 13%, and compared with ORB-SLAM2 by about 54.9%. In addition, the algorithm in this paper can process a single frame of image at a speed of 15–20 FPS on GeForce RTX 2080s, far exceeding Dyna-SLAM in real-time performance. This paper proposes a VSLAM algorithm that can be applied to dynamic environments. The algorithm consists of a self-supervised monocular depth estimation part under multiple constraints and the introduction of a dynamic object detection framework based on YOLOv5.
  Citation: Industrial Robot
  PubDate: 2024-08-06
  DOI: 10.1108/IR-04-2024-0166
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Enhancing dexterous hand control: a distributed architecture for machine
learning integration
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  Authors: Baoxu Tu, Yuanfei Zhang, Wangyang Li, Fenglei Ni, Minghe Jin
  Abstract: The aim of this paper is to enhance the control performance of dexterous hands, enabling them to handle the high data flow from multiple sensors and to meet the deployment requirements of deep learning methods on dexterous hands. A distributed control architecture was designed, comprising embedded motion control subsystems and a host control subsystem built on ROS. The design of embedded controller state machines and clock synchronization algorithms ensured the stable operation of the entire distributed control system. Experiments demonstrate that the entire system can operate stably at 1KHz. Additionally, the host can accomplish learning-based estimates of contact position and force. This distributed architecture provides foundational support for the large-scale application of machine learning algorithms on dexterous hands. Dexterity hands utilizing this architecture can be easily integrated with robotic arms.
  Citation: Industrial Robot
  PubDate: 2024-08-06
  DOI: 10.1108/IR-04-2024-0177
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Research on motion planning system for wall-climbing mobile manipulator
for large steel structures welding operation
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  Authors: Yan Xu, Yaqiu Liu, Xun Liu, Baoyu Wang, Lin Zhang, Zhengwen Nie
  Abstract: The purpose of this study is to address the welding demands within large steel structures by presenting a global spatial motion planning algorithm for a mobile manipulator. This algorithm is based on an independently developed wall-climbing robot, which comprises a four-wheeled climbing mobile platform and a six-degree-of-freedom robotic manipulator, ensuring high mobility and operational flexibility. A convex hull feasible domain constraint is developed for motion planning in the mobile manipulator. For extensive spatial movements, connected sequences of convex polyhedra are established between the composite robot’s initial and target states. The composite robot’s path and obstacle avoidance optimization problem are solved by constraining the control points on B-spline curves. A dynamic spatial constraint rapidlye-xploring random trees-connect (RRTC) motion planning algorithm is proposed for the manipulator, which quickly generates reference paths using spherical spatial constraints at the manipulator’s end, eliminating the need for complex nonconvex constraint modeling. Experimental results show that the proposed motion planning algorithm achieves optimal paths that meet task constraints, significantly reducing computation times in task conditions and shortening operation times in non-task conditions. The algorithm proposed in this paper holds certain application value for the realization of automated welding operations within large steel structures using mobile manipulator.
  Citation: Industrial Robot
  PubDate: 2024-07-31
  DOI: 10.1108/IR-05-2024-0224
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Design and application of a vehicle robot to FAST reflector surface
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  Authors: Lichun Zhu, Zhiqian Jiang, Long Qiao, Meng Zou, Guangming Chen
  Abstract: This paper aims to introduce a wheeled vehicle robot for adapting to the surface terrain of the 500-m diameter reflector of the FAST radio telescope in China. By analyzing vehicles applied for different off-road environments, a six-wheeled architecture with a passive “triple-bogie” suspension is selected. A subscale model of the vehicle robot is designed, along with statics modeling and multibody simulations of the dynamics on simulated reflector panel surfaces. The slope- and step-climbing abilities of the subscale vehicle are discussed in accordance with numerical and experimental tests. An engineering scale vehicle is subsequently manufactured and tested on surface terrains of lateral as well as vertical gaps, and is finally validated on the FAST reflector. This model of vehicle robot exhibits strong structure stability under desired payload. It can stably cross lateral gaps for maximum surface slope 28° and can traverse vertical gap for maximum surface slope 23°. The traversing abilities satisfy the mobility requirements subjected to surface terrains of FAST reflector. The engineering vehicle robot negotiates the lateral as well as vertical gaps between triangle panels and has been successfully applied to the FAST reflector serving for inspection and maintenance work.
  Citation: Industrial Robot
  PubDate: 2024-07-29
  DOI: 10.1108/IR-03-2024-0092
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Industry 4.0 in small and medium enterprises: a state-of-the-art science
mapping review
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  Authors: Md Faizal Ahmad, Muhammad Ashraf Fauzi, Mohamad Reeduan Mustapha, Puteri Fadzline Muhamad Tamyez, Amirul Syafiq Sadun, Idris Gautama So, Anderes Gui
  Abstract: This study comprehensively reviews the Fourth Industrial Revolution, which refers to Industry 4.0 (IR 4.0) applications in small and medium enterprises (SMEs). Multinational companies and big corporations have the capacity and resources to implement IR 4.0, but SMEs are limited due to financial constraints, expertise and lack of resources. Even so, IR 4.0 is required as technologies evolve and market demand has changed how firms do business. To uncover the potential of IR 4.0 and critical determinants of SMEs’ adoption of IR 4.0, this study presents a bibliometric analysis to evaluate the current research streams in IR 4.0 adoption among SMEs through bibliographic coupling. Furthermore, this review provides a glimpse of the future by analyzing prospective trends on IR 4.0 in SMEs. Bibliographic coupling produces five clusters: (1) challenges and barriers in IR 4.0 implementation among SMEs, (2) technological adoption of IR 4.0, (3) opportunities and benefits of IR 4.0, (4) business model innovation and (5) implication of IR 4.0 on SMEs technologies. On the contrary, co-word analysis produces three clusters: (1) technologies in IR 4.0, (2) strategy and management of IR 4.0 among SMEs and (3) IR 4.0 model for SMEs. Implications are directly related to business owners, policymakers and technology developers meeting the needs of the industry and SMEs, which are the focus of this review. The findings contribute significantly to the body of knowledge by presenting a state-of-the-art science mapping approach to uncover the knowledge structure and intellectual linkage of IR 4.0 adoption within SMEs.
  Citation: Industrial Robot
  PubDate: 2024-07-22
  DOI: 10.1108/IR-03-2024-0115
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
A dynamic target tracking framework of UGV for UAV recovery under random
disturbances
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  Authors: Bin Li, Shoukun Wang, Jinge Si, Yongkang Xu, Liang Wang, Chencheng Deng, Junzheng Wang, Zhi Liu
  Abstract: Dynamically tracking the target by unmanned ground vehicles (UGVs) plays a critical role in mobile drone recovery. This study aims to solve this challenge under diverse random disturbances, proposing a dynamic target tracking framework for UGVs based on target state estimation, trajectory prediction, and UGV control. To mitigate the adverse effects of noise contamination in target detection, the authors use the extended Kalman filter (EKF) to improve the accuracy of locating unmanned aerial vehicles (UAVs). Furthermore, a robust motion prediction algorithm based on polynomial fitting is developed to reduce the impact of trajectory jitter caused by crosswinds, enhancing the stability of drone trajectory prediction. Regarding UGV control, a dynamic vehicle model featuring independent front and rear wheel steering is derived. Additionally, a linear time-varying model predictive control algorithm is proposed to minimize tracking errors for the UGV. To validate the feasibility of the framework, the algorithms were deployed on the designed UGV. Experimental results demonstrate the effectiveness of the proposed dynamic tracking algorithm of UGV under random disturbances. This paper proposes a tracking framework of UGV based on target state estimation, trajectory prediction and UGV predictive control, enabling the system to achieve dynamic tracking to the UAV under multiple disturbance conditions.
  Citation: Industrial Robot
  PubDate: 2024-07-19
  DOI: 10.1108/IR-01-2024-0004
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Topology-preserved distorted space path planning
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  Authors: Yangmin Xie, Qiaoni Yang, Rui Zhou, Zhiyan Cao, Hang Shi
  Abstract: Fast obstacle avoidance path planning is a challenging task for multijoint robots navigating through cluttered workspaces. This paper aims to address this issue by proposing an improved path-planning method based on the distorted space (DS) method, specifically designed for high-dimensional complex environments. The proposed method, termed topology-preserved distorted space (TP-DS) method, mitigates the limitations of the original DS method by preserving space topology through elastic deformation. By applying distinct spring constants, the TP-DS autonomously shrinks obstacles to microscopic areas within the configuration space, maintaining consistent topology. This enhancement extends the application scope of the DS method to handle complex environments effectively. Comparative analysis demonstrates that the proposed TP-DS method outperforms traditional methods regarding planning efficiency. Successful obstacle avoidance tasks in the cluttered workspace validate its applicability on a physical 6-DOF manipulator, highlighting its potential for industrial implementations. The novel TP-DS method generates a topology-preserved collision-free space by leveraging elastic deformation and shows significant capability and efficiency in planning obstacle-avoidance paths in complex application scenarios.
  Citation: Industrial Robot
  PubDate: 2024-07-19
  DOI: 10.1108/IR-02-2024-0049
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
An automatic robot for ultrasonic partial discharge detection of
gas-insulated switchgear
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  Authors: Run Yang, Jingru Li, Taiyun Zhu, Di Hu, Erbao Dong
  Abstract: Gas-insulated switchgear (GIS) stands as a pivotal component in power systems, susceptible to partial discharge occurrences. Nevertheless, manual inspection proves labor-intensive, exhibits a low defect detection rate. Conventional inspection robots face limitations, unable to perform live line measurements or adapt effectively to diverse environmental conditions. This paper aims to introduce a novel solution: the GIS ultrasonic partial discharge detection robot (GBOT), designed to assume the role of substation personnel in inspection tasks. GBOT is a mobile manipulator system divided into three subsystems: autonomous location and navigation, vision-guided and force-controlled manipulator and data detection and analysis. These subsystems collaborate, incorporating simultaneous localization and mapping, path planning, target recognition and signal processing, admittance control. This paper also introduces a path planning method designed to adapt to the substation environment. In addition, a flexible end effector is designed for full contact between the probe and the device. The robot fulfills the requirements for substation GIS inspections. It can conduct efficient and low-cost path planning with narrow passages in the constructed substation map, realizes a sufficiently stable detection contact and perform high defect detection rate. The robot mitigates the labor intensity of grid maintenance personnel, enhances inspection efficiency and safety and advances the intelligence and digitization of power equipment maintenance and monitoring. This research also provides valuable insights for the broader application of mobile manipulators in diverse fields. The robot is a mobile manipulator system used in GIS detection, offering a viable alternative to grid personnel for equipment inspections. Comparing with the previous robotic systems, this system can work in live electrical detection, demonstrating robust environmental adaptability and superior efficiency.
  Citation: Industrial Robot
  PubDate: 2024-07-17
  DOI: 10.1108/IR-01-2024-0005
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Research on robot tracking force control algorithm based on neural
networks
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  Authors: Liang Du, Meng Xiao
  Abstract: This study aims to propose a force control algorithm based on neural networks, which enables a robot to follow a changing reference force trajectory when in contact with human skin while maintaining a stable tracking force. Aiming at the challenge of robots having difficulty tracking changing force trajectories in skin contact scenarios, a single neuron algorithm adaptive proportional – integral – derivative online compensation is used based on traditional impedance control. At the same time, to better adapt to changes in the skin contact environment, a gated recurrent unit (GRU) network is used to model and predict skin elasticity coefficients, thus adjusting to the uncertainty of skin environments. In two robot–skin interaction experiments, compared with the traditional impedance control and robot force control algorithm based on the radial basis function model and iterative algorithm, the maximum absolute force error, the average absolute force error and the standard deviation of the force error are all decreased. As the training process of the GRU network is currently conducted offline, the focus in the subsequent phase is to refine the network to facilitate real-time computation of the algorithm. This algorithm can be applied to robot massage, robot B-ultrasound and other robot-assisted treatment scenarios. As the proposed approach obtains effective force tracking during robot–skin contact and is verified by the experiment, this approach can be used in robot–skin contact scenarios to enhance the accuracy of force application by a robot.
  Citation: Industrial Robot
  PubDate: 2024-07-17
  DOI: 10.1108/IR-04-2024-0176
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Adaptive variable impedance force/position hybrid control for large
surface polishing
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  Authors: Zhixu Zhu, Hualiang Zhang, Guanghui Liu, Dongyang Zhang
  Abstract: This paper aims to propose a hybrid force/position controller based on the adaptive variable impedance. First, the working space is divided into a force control subspace and a position subspace, the force control subspace adopts the position impedance control strategy. At the same time, the contact force model between the robot and the surface is analyzed in this space. Second, based on the traditional position impedance, the model reference adaptive control is introduced to provide an accurate reference position for the impedance controller. Then, the BP neural network is used to adjust the impedance parameters online. The experimental results show that compared with the traditional PI control method, the proposed method has a higher flexibility, the dynamic response accommodation time is reduced by 7.688 s and the steady-state error is reduced by 30.531%. The overshoot of the contact force between the end of robot and the workpiece is reduced by 34.325% comparing with the fixed impedance control method. The proposed control method compares with a hybrid force/position based on PI control method and a position fixed impedance control method by simulation and experiment. The adaptive variable impedance control method improves accuracy of force tracking and solves the problem of the large surfaces with robot grinding often over-polished at the protrusion and under-polished at the concave.
  Citation: Industrial Robot
  PubDate: 2024-07-17
  DOI: 10.1108/IR-10-2023-0237
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
An obstacle avoidance method for robotic arm based on reinforcement
learning
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  Authors: Peng Wu, Heng Su, Hao Dong, Tengfei Liu, Min Li, Zhihao Chen
  Abstract: Robotic arms play a crucial role in various industrial operations, such as sorting, assembly, handling and spraying. However, traditional robotic arm control algorithms often struggle to adapt when faced with the challenge of dynamic obstacles. This paper aims to propose a dynamic obstacle avoidance method based on reinforcement learning to address real-time processing of dynamic obstacles. This paper introduces an innovative method that introduces a feature extraction network that integrates gating mechanisms on the basis of traditional reinforcement learning algorithms. Additionally, an adaptive dynamic reward mechanism is designed to optimize the obstacle avoidance strategy. Validation through the CoppeliaSim simulation environment and on-site testing has demonstrated the method's capability to effectively evade randomly moving obstacles, with a significant improvement in the convergence speed compared to traditional algorithms. The proposed dynamic obstacle avoidance method based on Reinforcement Learning not only accomplishes the task of dynamic obstacle avoidance efficiently but also offers a distinct advantage in terms of convergence speed. This approach provides a novel solution to the obstacle avoidance methods for robotic arms.
  Citation: Industrial Robot
  PubDate: 2024-07-16
  DOI: 10.1108/IR-05-2024-0206
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Visual servoing method of high voltage capacitor tower maintenance robot
in bolt tightening
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  Authors: Yuze Wu, Jianbin Liao, Liangyu Liu, Yu Yan, Yunfei Ai, Yunxiang Li, Wang Wei
  Abstract: This paper aims to address the challenges of the capacitor tower maintenance robot during bolt tightening in high-voltage substations, including difficulties in bolt positioning due to tilted angles and anti-bird cover occlusion and issues with fast and accurate docking of bolts while the base is moving. This paper proposes a visual servoing method for the capacitor tower maintenance robot, including bolt pose estimation and visual servoing control. Bolt pose estimation includes four components: constructing a keypoint detection network to identify the approximate position, precise positioning, rapid prediction and calculation of bolt pose. In visual servoing, an improved position-based visual servoing (PBVS) is proposed, which eliminate steady-state error and enhance response speed during dynamic tracking by incorporating integral and differential components. The bolt detection method exhibits high robustness against varying lighting conditions, partial occlusions, shooting distances and angles. The maximum positioning error at a distance of 250 mm is 2.8 mm. The convergence speed of the improved PBVS is 10% higher than that of the traditional PBVS when the base and target remain relatively stationary. When the base moves at a constant speed, the improved method eliminates steady-state error in dynamic tracking. When the base moves rapidly and intermittently, the maximum error of the improved method in the tracking process is 30% smaller than that of traditional PBVS. This method enables real-time detection and positioning of bolts in an unstructured environment with tilt angles, variable lighting conditions and occlusion by anti-bird covers. An improved PBVS is proposed to enhance its capability in tracking dynamic targets.
  Citation: Industrial Robot
  PubDate: 2024-07-12
  DOI: 10.1108/IR-03-2024-0083
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Mechanoreception of pneumatic soft robotic finger without tactile sensor
based on dual-position feature
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  Authors: Kai Shi, Jun Li, Gang Bao
  Abstract: Mechanoreception is crucial for robotic planning and control applications, and for robotic fingers, mechanoreception is generally obtained through tactile sensors. As a new type of robotic finger, the soft finger also requires mechanoreception, like contact force and object stiffness. Unlike rigid fingers, soft fingers have elastic structures, meaning there is a connection between force and deformation of the soft fingers. It allows soft fingers to achieve mechanoreception without using tactile sensors. This study aims to provide a mechanoreception sensing scheme of the soft finger without any tactile sensors. This research uses bending sensors to measure the actual bending state under force and calculates the virtual bending state under assumed no-load conditions using pressure sensors and statics model. The difference between the virtual and actual finger states is the finger deformation under load, and its product with the finger stiffness can be used to calculate the contact force. There are distinctions between the virtual and actual finger state change rates in the pressing process. The difference caused by the stiffness of different objects is different, which can be used to identify the object stiffness. Contact force perception can achieve a detection accuracy of 0.117 N root mean square error within the range of 0–6 N contact force. The contact object stiffness perception has a detection average deviation of about 15%, and the detection standard deviation is 10% for low-stiffness objects and 20% for high-stiffness objects. It performs better at detecting the stiffness of low-stiffness objects, which is consistent with the sensory ability of human fingers. This paper proposes a universal mechanoreception method for soft fingers that only uses indispensable bending and pressure sensors without tactile sensors. It helps to reduce the hardware complexity of soft robots. Meanwhile, the soft finger no longer needs to deploy the tactile sensor at the fingertip, which can benefit the optimization design of the fingertip structure without considering the complex sensor installation. On the other hand, this approach is no longer confined to adding components needed. It can fully use the soft robot body’s physical elasticity to convert sensor signals. Essentially, It treats the soft actuators as soft sensors.
  Citation: Industrial Robot
  PubDate: 2024-07-11
  DOI: 10.1108/IR-03-2024-0096
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Path optimization of underwater vehicles in multi-obstacle environment
based on energy constraint strategy
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  Authors: Chang Yuan, Xinyu Wu, Donghai Zeng, Baoren Li
  Abstract: To solve the problem that the underwater vehicles is difficult to turn and exit in a small range in the face of complex marine environment such as concave and ring under the limitation of its limitation of its shape and maximum steering angle, this paper aims to propose an improved ant colony algorithm based on trap filling strategy and energy consumption constraint strategy. Firstly, on the basis of searching the global path, the disturbed terrain was pre-filled in the complex marine environments. Based on the energy constraint strategy, the ant colony algorithm was improved to make the search path of the underwater vehicle meet the requirements of the lowest energy consumption and the shortest path in the complex obstacle environment. The simulation results showed that the modified grid environment diagram effectively reduced the redundancy search and improved the optimization efficiency. Aiming at the problem of “the shortest distance is not the lowest energy consumption” in the traditional path optimization algorithm, the energy consumption level was reduced by 26.41% after increasing the energy consumption constraint, although the path length and the number of inflection points were slightly higher than the shortest path constraint, which was more conducive to the navigation of underwater vehicles. The method proposed in this paper is not only suitable for trajectory planning of underwater robots but also suitable for trajectory planning of land robots.
  Citation: Industrial Robot
  PubDate: 2024-07-09
  DOI: 10.1108/IR-03-2024-0119
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Design and application of bidirectional soft actuator with multiangle
chambers
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  Authors: Yehao Wen, Chang Chen, Zhengnan Lyu, Yuandong Liang, Zhongyu Zhang
  Abstract: This study aims to introduce a novel bidirectional soft actuator as an enhancement to conventional pneumatic network actuators. This improvement involves integrating air chambers positioned at specific angles to improve stability, adaptability and grasping efficiency in various environments. The design approach incorporates air chambers positioned at a 45° angle relative to the horizontal direction at the actuator's terminus, along with additional chambers at a 90° angle. Mathematical models are developed for longitudinal and transverse bending, as well as for obliquely connected cavities, based on the assumption of piecewise constant curvature. Analyses are conducted on output forces, bending characteristics and end contact areas for both transverse and longitudinal ends. The proposed soft actuator surpasses traditional pneumatic network actuators in gripping area due to the inclusion of a diagonal air cavity and a transverse pneumatic network structure at the terminus. As a result, it provides torsion and gripping force in both directions. Testing on a dedicated platform with two variants of grippers demonstrates superior gripping force capability and performance in complex environments. Through the design of multiangle chambers, the soft actuator exhibits diverse driving angles and morphological variations, offering innovative design perspectives for industrial grasping. The design of multiangle chambers facilitates personalized configurations of soft actuators by researchers, enabling tailored angles for specific interaction environments to achieve desired functionalities. This approach offers novel insights into soft actuator design, addressing more prevalent industrial grasping challenges. This study introduces a novel soft actuator design that significantly enhances gripping capabilities in comparison to conventional pneumatic network actuators. The incorporation of specific air chamber configurations and mathematical modeling provides valuable insights for the development of adaptable and efficient robotic grippers for industrial and household applications.
  Citation: Industrial Robot
  PubDate: 2024-07-04
  DOI: 10.1108/IR-04-2024-0136
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Structural design and control strategy of a cable-driven robot under
high-altitude facade conditions with large span and multiple constraints
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  Authors: Feiyu Hou, Chaofeng Liu, Hongbo Jiang, Zhiren Tang, Pingtan Fang, Shenglan Wang
  Abstract: This paper explores the challenges of using cable-driven parallel robots on high-altitude, large-span facades, where redundancy in multicable systems and the elastic deformation of the cables are significant issues. This study aims to improve the accuracy and stability of the work platform through enhanced control strategies. These strategies address the redundancy in multicable systems and reduce the risks associated with cable deformation and mechanical failures during large-span movements. The paper proposes a dynamic model for a four-rope parallel robot designed explicitly for large-span applications. The study introduces a position–force control strategy incorporating kinematic inverse solutions and a rope dynamics model to account for rope elasticity and its effects. This approach increases the number of system equations to match the unknowns, effectively solving the redundancy problem inherent in multicable systems. In addition, the tension changes of ropes and the stability of the working platform are examined under different motion distances (X = 50 m and X = 100 m) and varying Young’s modulus values (K = 5000 MPa and K = 8000 MPa). This study’s large-span rope force–position control strategy successfully resolves the typical nonlinear characteristics and external disturbances in multicable parallel systems. By continuously monitoring and adjusting cable tension and end positions, this strategy ensures precise control over each cable’s tension, optimizes the distribution of cable tensions and maintains the system’s stability and response speed. The analysis in this paper indicates that this control strategy significantly improves the motion accuracy of robots operating on large-span high-altitude facades. Industry adoption: The design and control strategies developed for the four-cable-driven parallel robot can be adopted by companies specializing in facade maintenance, construction or inspection. This could lead to safer, more efficient and cost-effective operations, especially in challenging environments like high-rise buildings. Innovation in robotic solutions: The research can inspire innovation within the field of robotics, particularly in developing robots for specific applications such as large surface maintenance. It showcases how adaptive control and stability can be achieved in complex operational scenarios. Safety improvements: By demonstrating a more stable and precise control mechanism for navigating large facades, the study could contribute to significant safety improvements, reducing the risk of accidents associated with manual facade maintenance and inspection tasks. This paper combines the force/position hybrid control method with actual robotic applications, offering a novel solution to the complex issue of controlling cable-driven parallel robots in challenging environments. Thus, it contributes to the field. The proposed method significantly enhances the precision and stability of such systems and provides robust technical support for high-precision tasks in complex mechanical settings.
  Citation: Industrial Robot
  PubDate: 2024-07-02
  DOI: 10.1108/IR-03-2024-0097
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
A novel deep learning method for motion assessment in upper limb
rehabilitation grasping test
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  Authors: Lei Yang, Fuhai Zhang, Jingbin Zhu, Yili Fu
  Abstract: The accuracy and reliability of upper limb motion assessment have received great attention in the field of rehabilitation. Grasping test is widely carried out for motion assessment, which requires patients to grasp objects and move them to target place. The traditional assessments test the upper limb motion ability by therapists, which mainly relies on experience and lacks quantitative indicators. This paper aims to propose a deep learning method based on the vision system of our upper limb rehabilitation robot to recognize the motion trajectory of rehabilitation target objects automatically and quantitatively assess the upper limb motion in the grasping test. To begin with, an SRF network is designed to recognize rehabilitation target objects grasped in assessment tests. Moreover, the upper limb motion trajectory is calculated through the motion of objects’ central positions. After that, a GAE network is designed to analyze the motion trajectory which reflects the motion of upper limb. Finally, based on the upper limb rehabilitation exoskeleton platform, the upper limb motion assessment tests are carried out to show the accuracy of both object recognition of SRF network and motion assessment of GAE network. The results including object recognition, trajectory calculation and deviation assessment are given with details. The performance of the proposed networks is validated by experiments that are developed on the upper limb rehabilitation robot. It is implemented by recognizing rehabilitation target objects, calculating the motion trajectory and grading the upper limb motion performance. It illustrates that the networks, including both object recognition and trajectory evaluation, can grade the upper limb motion functionn accurately, where the accuracy is above 95.0% in different grasping tests. A novel assessment method of upper limb motion is proposed and verified. According to the experimental results, the accuracy can be remarkably enhanced, and the stability of the results can be improved, which provide more quantitative indicators for further application of upper limb motion assessment.
  Citation: Industrial Robot
  PubDate: 2024-07-02
  DOI: 10.1108/IR-04-2024-0157
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Human-following task without a prior map
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  Authors: Zhiqiang Zhou, Yong Fu, Wei Wu
  Abstract: The human-following task is a fundamental function in human–robot collaboration. It requires a robot to recognize and locate a target person, plan a path and avoid obstacles. To enhance the applicability of the human-following task in various scenarios, it should not rely on a prior map. This paper aims to introduce a human-following method that meets these requirements. For the identification and localization of the target person (ILTP), this paper proposes an approach that integrates data from a camera, a light detection and ranging (LiDAR) and a ultra-wideband (UWB) anchor. For path planning and obstacle avoidance, a modified timed-elastic-bands (TEB) algorithm is introduced. Compared to the UWB-only method, where only UWB is used to locate the target person, the proposed ILTP method in this paper reduces the localization error by 41.82%. Experimental results demonstrate the effectiveness of the ILTP and the modified TEB method under various challenging conditions. Such as crowded environments, multiple obstacles, the target person being occluded and the target person moving out of the robot’s field of view. The complete experimental videos are available for viewing on https://youtu.be/ZKbrNE1sePM. This paper offers a novel solution for human-following tasks. The proposed ILTP method can recognize the target person among multiple individuals, determine whether the target person is lost and publish the target person’s position at a frequency of 20 Hz. The modified TEB algorithm does not rely on a prior map. It can plan paths and avoid obstacles effectively.
  Citation: Industrial Robot
  PubDate: 2024-07-02
  DOI: 10.1108/IR-12-2023-0319
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Impedance-based null-space control of redundant torque-controlled robot
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  Authors: Leigang Zhang, Hongliu Yu, Xilong Cui
  Abstract: The null-space projection method is commonly adopted for controlling redundant robots, which undoubtedly requires the robot Jacobian matrix inverse. This paper aims to provide a novel control scheme, which enables null-space control of redundant robots without conflict with the main task space. In this paper, an impedance-based null-space control approach for redundant robots is proposed. The null-space degrees of freedom are separated from the primary task space by using the eigenvalue decomposition. Then, a joint impedance controller spans the null space and is reflected into the joint space to manage the redundancy. Finally, several experiments have been conducted to evaluate and validate the performance of the proposed approach in comparison with the null-space projection method under various situations. Experiment results show that no significant differences were observed between the different filling eigenvalues in the proposed approach under different null-space dimensions and motion velocity. Besides, comparative experiment results demonstrate that the proposed method can achieve comparable results to the null-space projection method. Nevertheless, the suggested approach has benefits regarding the quantity of control parameters in addition to not requiring a Jacobian inverse. Notably, the performance of the proposed method will improve as the null-space dimension increases. This study presents a new control method for redundant robots, which has advantages for dealing with the problems of controlling redundant robots compared to the existing methods.
  Citation: Industrial Robot
  PubDate: 2024-06-26
  DOI: 10.1108/IR-01-2024-0038
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Adaptive autonomous navigation system for coal mine inspection robots:
overcoming intersection challenges
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  Authors: Hongwei Wang, Chao Li, Wei Liang, Di Wang, Linhu Yao
  Abstract: In response to the navigation challenges faced by coal mine tunnel inspection robots in semistructured underground intersection environments, many current studies rely on structured map-based planning algorithms and trajectory tracking techniques. However, this approach is highly dependent on the accuracy of the global map, which can lead to deviations from the predetermined route or collisions with obstacles. To improve the environmental adaptability and navigation precision of the robot, this paper aims to propose an adaptive navigation system based on a two-dimensional (2D) LiDAR. Leveraging the geometric features of coal mine tunnel environments, the clustering and fitting algorithms are used to construct a geometric model within the navigation system. This not only reduces the complexity of the navigation system but also optimizes local positioning. By constructing a local potential field, there is no need for path-fitting planning, thus enhancing the robot’s adaptability in intersection environments. The feasibility of the algorithm principles is validated through MATLAB and robot operating system simulations in this paper. The experiments demonstrate that this method enables autonomous driving and optimized positioning capabilities in harsh environments, with high real-time performance and environmental adaptability, achieving a positioning error rate of less than 3%. This paper presents an adaptive navigation system for a coal mine tunnel inspection robot using a 2D LiDAR sensor. The system improves robot attitude estimation and motion control accuracy to ensure safe and reliable navigation, especially at tunnel intersections.
  Citation: Industrial Robot
  PubDate: 2024-06-24
  DOI: 10.1108/IR-11-2023-0295
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
The role of neuromorphic and biomimetic sensors
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  Authors: Rob Bogue
  Abstract: The purpose of this paper is to provide details of biomimetic and neuromorphic sensor research and developments and discuss their applications in robotics. Following a short introduction, this first provides examples of recent biomimetic gripping and sensing skin research and developments. It then considers neuromorphic vision sensing technology and its potential robotic applications. Finally, brief conclusions are drawn. Biomimetics aims to exploit mechanisms, structures and signal processing techniques which occur in the natural world. Biomimetic sensors and control techniques can impart robots with a range of enhanced capabilities such as learning, gripping and multidimensional tactile sensing. Neuromorphic vision sensors offer several key operation benefits over conventional frame-based imaging techniques. Robotic applications are still largely at the research stage but uses are anticipated in enhanced safety systems in autonomous vehicles and in robotic gripping. This illustrates how tactile and imaging sensors based on biological principles can contribute to imparting robots with enhanced capabilities.
  Citation: Industrial Robot
  PubDate: 2024-06-21
  DOI: 10.1108/IR-05-2024-0203
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Force manipulability-oriented manipulation planning for collaborative
robot
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  Authors: Tianyu Zhang, Hongguang Wang, Peng LV, Xin’an Pan, Huiyang Yu
  Abstract: Collaborative robots (cobots) are widely used in various manipulation tasks within complex industrial environments. However, the manipulation capabilities of cobot manipulation planning are reduced by task, environment and joint physical constraints, especially in terms of force performance. Existing motion planning methods need to be more effective in addressing these issues. To overcome these challenges, the authors propose a novel method named force manipulability-oriented manipulation planning (FMMP) for cobots. This method integrates force manipulability into a bidirectional sampling algorithm, thus planning a series of paths with high force manipulability while satisfying constraints. In this paper, the authors use the geometric properties of the force manipulability ellipsoid (FME) to determine appropriate manipulation configurations. First, the authors match the principal axes of FME with the task constraints at the robot’s end effector to determine manipulation poses, ensuring enhanced force generation in the desired direction. Next, the authors use the volume of FME as the cost function for the sampling algorithm, increasing force manipulability and avoiding kinematic singularities. Through experimental comparisons with existing algorithms, the authors validate the effectiveness and superiority of the proposed method. The results demonstrate that the FMMP significantly improves the force performance of cobots under task, environmental and joint physical constraints. To improve the force performance of manipulation planning, the FMMP introduces the FME into sampling-based path planning and comprehensively considers task, environment and joint physical constraints. The proposed method performs satisfactorily in experiments, including assembly and in situ measurement.
  Citation: Industrial Robot
  PubDate: 2024-06-18
  DOI: 10.1108/IR-01-2024-0037
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Design and control of variable stiffness joint based on magnetic flux
adjustment mechanism
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  Authors: Ming Zhang, Lei Hou, Huaichao Guo, Hongyu Li, Feng Sun, Lijin Fang
  Abstract: This study aims to improve the robot’s performance during interactions with human and uncertain environments. A joint stiffness model was established according to the molecular current method and the virtual displacement method. The position and stiffness coordination controller and fuzzy adaptive controller of variable stiffness joint are designed, and the principle prototype of variable stiffness joint is built. The position step and trajectory tracking performance of the variable stiffness joint are verified through experiments. Experimental test shows that the joint stiffness can be quickly adjusted. The accuracy of position and trajectory tracking of the joint increases with higher stiffness and decreases with increasing frequency. The fuzzy adaptive controller performed better than the position and stiffness coordination controller in controlling the position step and trajectory tracking of the variable stiffness joint. A hybrid flux adjustment mechanism is proposed for the components of variable stiffness robot joints, which reduces the mass of the output end of variable stiffness joints and the speed of joint stiffness adjustment. Aiming at the change of system controller performance caused by the change of joint stiffness, a fuzzy adaptive controller is proposed to improve the position step and trajectory tracking characteristics of variable stiffness joints.
  Citation: Industrial Robot
  PubDate: 2024-06-17
  DOI: 10.1108/IR-12-2023-0317
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Nonlinear observer-based impedance control of a fully-actuated hexarotor
for accurate aerial physical interaction
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  Authors: Chang Wang, Ran Jiao, Jianhua Zhang
  Abstract: Fully-actuated unmanned aerial vehicles (UAVs) are a growing and promising field of research, which shows advantages for aerial physical interaction. The purpose of this paper is to construct a force sensor-denied control method for a fully-actuated hexarotor to conduct aerial interaction with accurate force exerted outward. First, by extending single-dimension impedance model to the fully-actuated UAV model, an impedance controller is designed for compliant UAV pose/force control. Then, to estimate the interaction force between UAV end-effector and external environment accurately, combined with super-twisting theory, a nonlinear force observer is constructed. Finally, based on impedance controller and estimated force from observer, an interaction force regulation method is proposed. The presented nonlinear observer-based impedance control approach is validated in both simulation and environments, in which the authors try to use a fully-actuated hexarotor to accomplish the task of aerial physical interaction finding that a specified force is able to be exerted to environment without any information from force sensors. A solution of aerial physical interaction for UAV system enabling accurate force exerted outward without any force sensors is proposed in this paper.
  Citation: Industrial Robot
  PubDate: 2024-06-13
  DOI: 10.1108/IR-11-2023-0268
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Coordinated torque control for enhanced steering and stability of
independently driven mobile robots
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  Authors: Liang Wang, Shoukun Wang, Junzheng Wang
  Abstract: Mobile robots with independent wheel control face challenges in steering precision, motion stability and robustness across various wheel and steering system types. This paper aims to propose a coordinated torque distribution control approach that compensates for tracking deviations using the longitudinal moment generated by active steering. Building upon a two-degree-of-freedom robot model, an adaptive robust controller is used to compute the total longitudinal moment, while the robot actuator is regulated based on the difference between autonomous steering and the longitudinal moment. An adaptive robust control scheme is developed to achieve accurate and stable generation of the desired total moment value. Furthermore, quadratic programming is used for torque allocation, optimizing maneuverability and tracking precision by considering the robot’s dynamic model, tire load rate and maximum motor torque output. Comparative evaluations with autonomous steering Ackermann speed control and the average torque method validate the superior performance of the proposed control strategy, demonstrating improved tracking accuracy and robot stability under diverse driving conditions. When designing adaptive algorithms, using models with higher degrees of freedom can enhance accuracy. Furthermore, incorporating additional objective functions in moment distribution can be explored to enhance adaptability, particularly in extreme environments. By combining this method with the path-tracking algorithm, the robot’s structural path-tracking capabilities and ability to navigate a variety of difficult terrains can be optimized and improved.
  Citation: Industrial Robot
  PubDate: 2024-05-30
  DOI: 10.1108/IR-12-2023-0344
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Thermal error modeling method of truss robot based on GA-LSTM
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  Authors: Long Li, Binyang Chen, Jiangli Yu
  Abstract: The selection of sensitive temperature measurement points is the premise of thermal error modeling and compensation. However, most of the sensitive temperature measurement point selection methods do not consider the influence of the variability of thermal sensitive points on thermal error modeling and compensation. This paper considers the variability of thermal sensitive points, and aims to propose a sensitive temperature measurement point selection method and thermal error modeling method that can reduce the influence of thermal sensitive point variability. Taking the truss robot as the experimental object, the finite element method is used to construct the simulation model of the truss robot, and the temperature measurement point layout scheme is designed based on the simulation model to collect the temperature and thermal error data. After the clustering of the temperature measurement point data is completed, the improved attention mechanism is used to extract the temperature data of the key time steps of the temperature measurement points in each category for thermal error modeling. By comparing with the thermal error modeling method of the conventional fixed sensitive temperature measurement points, it is proved that the method proposed in this paper is more flexible in the processing of sensitive temperature measurement points and more stable in prediction accuracy. The Grey Attention-Long Short Term Memory (GA-LSTM) thermal error prediction model proposed in this paper can reduce the influence of the variability of thermal sensitive points on the accuracy of thermal error modeling in long-term processing, and improve the accuracy of thermal error prediction model, which has certain application value. It has guiding significance for thermal error compensation prediction.
  Citation: Industrial Robot
  PubDate: 2024-05-24
  DOI: 10.1108/IR-11-2023-0283
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Pose detection and docking control for autonomous dynamic docking
mechanism with non-cooperative targets
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  Authors: Gan Zhan, Zhihua Chen, Zhenyu Zhang, Jigang Zhan, Wentao Yu, Jiehao Li
  Abstract: This study aims to address the issue of random movement and non coordination between docking mechanisms and locking mechanisms, and proposes a comprehensive dynamic docking control architecture that integrates perception, planning, and motion control. Firstly, the proposed dynamic docking control architecture uses laser sensors and a charge-coupled device camera to perceive the pose of the target. The sensor data are mapped to a high-dimensional potential field space and fused to reduce interference caused by detection noise. Next, a new potential function based on multi-dimensional space is developed for docking path planning, which enables the docking mechanism based on Stewart platform to rapidly converge to the target axis of the locking mechanism, which improves the adaptability and terminal docking accuracy of the docking state. Finally, to achieve precise tracking and flexible docking in the final stage, the system combines a self-impedance controller and an impedance control algorithm based on the planned trajectory. Extensive simulations and experiments have been conducted to validate the effectiveness of the dynamic docking system and its control architecture. The results indicate that even if the target moves randomly, the system can successfully achieve accurate, stable and flexible dynamic docking. This research can provide technical guidance and reference for docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.
  Citation: Industrial Robot
  PubDate: 2024-05-21
  DOI: 10.1108/IR-11-2023-0287
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Model-free visual servoing based on active disturbance rejection control
and adaptive estimator for robotic manipulation without calibration
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  Authors: Jun Tian, Xungao Zhong, Xiafu Peng, Huosheng Hu, Qiang Liu
  Abstract: Visual feedback control is a promising solution for robots work in unstructured environments, and this is accomplished by estimation of the time derivative relationship between the image features and the robot moving. While some of the drawbacks associated with most visual servoing (VS) approaches include the vision–motor mapping computation and the robots’ dynamic performance, the problem of designing optimal and more effective VS systems still remains challenging. Thus, the purpose of this paper is to propose and evaluate the VS method for robots in an unstructured environment. This paper presents a new model-free VS control of a robotic manipulator, for which an adaptive estimator aid by network learning is proposed using online estimation of the vision–motor mapping relationship in an environment without the knowledge of statistical noise. Based on the adaptive estimator, a model-free VS schema was constructed by introducing an active disturbance rejection control (ADRC). In our schema, the VS system was designed independently of the robot kinematic model. The various simulations and experiments were conducted to verify the proposed approach by using an eye-in-hand robot manipulator without calibration and vision depth information, which can improve the autonomous maneuverability of the robot and also allow the robot to adapt its motion according to the image feature changes in real time. In the current method, the image feature trajectory was stable in the camera field range, and the robot’s end motion trajectory did not exhibit shock retreat. The results showed that the steady-state errors of image features was within 19.74 pixels, the robot positioning was stable within 1.53 mm and 0.0373 rad and the convergence rate of the control system was less than 7.21 s in real grasping tasks. Compared with traditional Kalman filtering for image-based VS and position-based VS methods, this paper adopts the model-free VS method based on the adaptive mapping estimator combination with the ADRC controller, which is effective for improving the dynamic performance of robot systems. The proposed model-free VS schema is suitable for robots’ grasping manipulation in unstructured environments.
  Citation: Industrial Robot
  PubDate: 2024-05-21
  DOI: 10.1108/IR-12-2023-0347
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Real-time collision detection based on external torque mutation
suppression and time series analysis
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  Authors: Tianyi Zhang, Haowu Luo, Ning Liu, Feiyan Min, Zhixin Liang, Gao Wang
  Abstract: As the demand for human–robot collaboration in manufacturing applications grows, the necessity for collision detection functions in robots becomes increasingly paramount for safety. Hence, this paper aims to improve the existing method to achieve efficient, accurate and sensitive robot collision detection. The external torque is estimated by momentum observers based on the robot dynamics model. Because the state of the joints is more accessible to distinguish under the action of the suppression operator proposed in this paper, the mutated external torque caused by joint reversal can be accurately attenuated. Finally, time series analysis (TSA) methods can continuously generate dynamic thresholds based on external torques. Compared with the collision detection method based only on TSA, the invalid time of the proposed method is less during joint reversal. Although the soft-collision detection accuracy of this method is lower than that of the symmetric threshold method, it is superior in terms of detection delay and has a higher hard-collision detection accuracy. Owing to the mutated external torque caused by joint reversal, which seriously affects the stability of time series models, the collision detection method based only on TSA cannot detect continuously. The consequences are disastrous if the robot collides with people or the environment during joint reversal. After multiple experimental verifications, the proposed method still exhibits detection capabilities during joint reversal and can implement real-time collision detection. Therefore, it is suitable for various engineering applications.
  Citation: Industrial Robot
  PubDate: 2024-05-17
  DOI: 10.1108/IR-12-2023-0338
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Path planning for robotic fish based on improved RRT* algorithm and
dynamic window approach
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  Authors: Yong Fu, Kun Chen, Li He, Hui Tan Wang
  Abstract: The purpose of this paper is to address two major challenges faced by robotic fish when operating in underwater environments: insufficient path planning capabilities and difficulties in avoiding dynamic obstacles. To achieve this, a method is proposed that combines the Improved Rapid Randomized Tree Star (IRRT*) with the dynamic window approach (DWA). The RRT-connect algorithm is used to determine an initial feasible path quickly. The quality of sampling points is then improved by dividing the regions and selecting each region’s probability based on its fitness value. The fitness function and roulette wheel method are introduced for region selection. Subtarget points of the DWA algorithm are extracted from the IRRT* algorithm to achieve real-time dynamic path planning. In various maps, the iteration count for the IRRT* algorithm decreased by 61%, 35% and 51% respectively, compared to the RRT* algorithm, whereas the iteration time was reduced by 75%, 34% and 57%, respectively. In addition, the IRRT*-DWA algorithm can successfully navigate through multiple dynamic obstacles, and the average time, path length, etc. do not change much when parameters change, and the stability is high. A novel IRRT*-DWA algorithm is proposed, which, by refining the sampling strategy and updating sub-target points in real time, not only addresses the limitations of existing algorithms in terms of path planning efficiency in complex environments but also enhances their capability to avoid dynamic obstacles. Ultimately, experimental results indicate a high level of similarity between the actual and ideal paths.
  Citation: Industrial Robot
  PubDate: 2024-05-17
  DOI: 10.1108/IR-12-2023-0349
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Research on improved active disturbance rejection control strategy for
hydraulic-driven Stewart stabilization platform
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  Authors: Xingyu Qu, Zhenyang Li, Qilong Chen, Chengkun Peng, Qinghe Wang
  Abstract: In response to the severe lag in tracking the response of the Stewart stability platform after adding overload, as well as the impact of nonlinear factors such as load and friction on stability accuracy, a new error attenuation function and a parallel stable platform active disturbance rejection control (ADRC) strategy combining cascade extended state observer (ESO) are proposed. First, through kinematic modeling of the Stewart platform, the relationship between the desired pose and the control quantities of the six hydraulic cylinders is obtained. Then, a linear nonlinear disturbance observer was established to observe noise and load, to enhance the system’s anti-interference ability. Finally, verification was conducted through simulation. Finally, stability analysis was conducted on the cascaded observer. Experiments were carried out on a parallel stable platform with six degrees of freedom involving rotation and translation. In comparison to traditional PID and ADRC control methods, the proposed control strategy not only endows the stable platform with strong antiload disturbance capability but also exhibits faster response speed and higher stability accuracy. A new error attenuation function is designed to address the lack of smoothness at d in the error attenuation function of the ADRC controller, reducing the system ripple caused by it. Finally, a combination of linear and nonlinear ESOs is introduced to enhance the system's response speed and its ability to observe noise and load disturbances. Stability analysis of the cascade observer is carried out, and experiments are conducted on a six-degree-of-freedom parallel stable platform with both rotational and translational motion.
  Citation: Industrial Robot
  PubDate: 2024-05-16
  DOI: 10.1108/IR-03-2024-0086
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Structural design and coupling analysis of multimode variable coupling
parallel mobile robots
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  Authors: Yiwen Jiang, Chunyan Zhang
  Abstract: There is coupling between the branches of mobile parallel robots, similar to traditional parallel mechanisms, but there is currently relatively little research on the coupling problem between the branches of mobile parallel robots. This study optimizes the coupling analysis method of traditional parallel mechanisms, treats the mobile parallel mechanism as a whole, takes the motion of the active pair as input and the overall motion of the mobile parallel mechanism as output and analyzes the input–output characteristics of the mobile parallel mechanism. Moreover, this study applies this theory to a mobile parallel mechanism, designs control logic and finally conducts simulation and physical verification. This study proposes a coupling analysis method suitable for parallel mobile robots and designs the control logic of their active pair based on the results of their coupling analysis. This study designs a multimode variable coupling parallel mobile robot, which can change the coupling of the mechanism by changing its own branch chain structure, so that it can switch between different coupling configurations to meet the different needs brought by different terrains. The work presented in this paper propose a method for analyzing the coupling of mobile parallel robots and simplify their control logic by applying coupling theory to the design of mobile parallel robots. This study conducts simulation and physical experiments, thereby filling the gap in the coupling analysis of parallel mobile robots and laying the foundation for the research of uncoupled parallel mobile robots.
  Citation: Industrial Robot
  PubDate: 2024-05-14
  DOI: 10.1108/IR-01-2024-0011
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
A trajectory planning method for robotic arms based on improved dynamic
motion primitives
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  Authors: Xiaohui Jia, Bin Zhao, Jinyue Liu, Shaolong Zhang
  Abstract: Traditional robot arm trajectory planning methods have problems such as insufficient generalization performance and low adaptability. This paper aims to propose a method to plan the robot arm’s trajectory using the trajectory learning and generalization characteristics of dynamic motion primitives (DMPs). This study aligns multiple demonstration motion primitives using dynamic time warping; use the Gaussian mixture model and Gaussian mixture regression methods to obtain the ideal primitive trajectory actions. By establishing a system model that improves DMPs, the parameters of the nonlinear function are learned based on the ideal primitive trajectory actions of the robotic arm, and the robotic arm motion trajectory is reproduced and generalized. Experiments have proven that the robot arm motion trajectory learned by the method proposed in this article can not only learn to generalize and demonstrate the movement trend of the primitive trajectory, but also can better generate ideal motion trajectories and avoid obstacles when there are obstacles. The maximum Euclidean distance between the generated trajectory and the demonstration primitive trajectory is reduced by 29.9%, and the average Euclidean distance is reduced by 54.2%. This illustrates the feasibility of this method for robot arm trajectory planning. It provides a new method for the trajectory planning of robotic arms in unstructured environments while improving the adaptability and generalization performance of robotic arms in trajectory planning.
  Citation: Industrial Robot
  PubDate: 2024-05-13
  DOI: 10.1108/IR-12-2023-0322
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Design and optimization of lower limb exoskeleton based on multi-axis knee
joint
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  Authors: Jintian Yun, Deqiang Zhang, Weisheng Cui, Shuai Li, Guan Miao
  Abstract: The purpose of this paper is to improve the problem of kinematics incompatibility of human–exoskeleton in the existing rigid lower-limb exoskeleton (LLE). In this paper, following an introduction, the motion characteristics of the human knee joint and the design method of the exoskeleton were introduced. A kinematics model of the LLE based on cross-four-bar linkage was obtained. The structural parameters of the LLE mechanism were optimized by the particle swarm optimization algorithm. The predefined trajectories used in the optimization process were derived from the ankle joint, not the instantaneous center of rotation of the knee joint. Finally, the motion deviation of the optimization result was simulated, and the human–exoskeleton coordination experiment was designed to compare with the traditional single-axis knee joint in terms of comfort and coordination. The lower limb exoskeleton mechanism obtained in this paper has a good tracking effect on human movement and has been improved in terms of comfort and coordination compared with the traditional single-axis knee joint. The customized exoskeleton design method introduced in this paper is relatively simple, and the obtained exoskeleton has better movement coordination than the traditional exoskeleton. It can provide a reference for the design of lower limb exoskeleton and lower limb orthosis.
  Citation: Industrial Robot
  PubDate: 2024-05-10
  DOI: 10.1108/IR-09-2023-0198
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Accurate kinematic calibration of a six-DoF serial robot by using hybrid
models with reduced dimension and minimized linearization errors
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  Authors: Zhouxiang Jiang, Shiyuan Chen, Yuchen Zhao, Zhongjie Long, Bao Song, Xiaoqi Tang
  Abstract: In typical model-based calibration, linearization errors are derived inevitably, and non-negligible negative impact will be induced on the identification results if the rotational kinematic errors are not small enough or the lengths of links are too long, which is common in the industrial cases. Thus, an accurate two-step kinematic calibration method minimizing the linearization errors is presented for a six-DoF serial robot to improve the calibration accuracy. The negative impact of linearization on identification accuracy is minimized by removing the responsible linearized kinematic errors from the complete kinematic error model. Accordingly, the identification results of the dimension-reduced new model are accurate but not complete, so the complete kinematic error model, which achieves high identification accuracy of the rest of the error parameters, is combined with this new model to create a two-step calibration procedure capable of highly accurate identification of all the kinematic errors. The proportions of linearization errors in measured pose errors are quantified and found to be non-negligible with the increase of rotational kinematic errors. Thus, negative impacts of linearization errors are analyzed quantitatively in different cases, providing the basis for allowed kinematic errors in the new model. Much more accurate results were obtained by using the new two-step calibration method, according to a comparison with the typical methods. This new method achieves high accuracy with no compromise on completeness, is easy to operate and is consistent with the typical method because the second step with the new model is conveniently combined without changing the sensors or measurement instrument setup.
  Citation: Industrial Robot
  PubDate: 2024-05-07
  DOI: 10.1108/IR-01-2024-0029
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
3D-AMM: a 3D artificial moment method for path planning of manipulator in
multiple obstacles scenario
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  Authors: Andong Liu, Yawen Zhang, Jiayun Fu, Yuankun Yan, Wen-An Zhang
  Abstract: In response to the issue of traditional algorithms often falling into local minima or failing to find feasible solutions in manipulator path planning. The purpose of this paper is to propose a 3D artificial moment method (3D-AMM) for obstacle avoidance for the robotic arm's end-effector. A new method for constructing temporary attractive points in 3D has been introduced using the vector triple product approach, which generates the attractive moments that attract the end-effector to move toward it. Second, distance weight factorization and spatial projection methods are introduced to improve the solution of repulsive moments in multiobstacle scenarios. Third, a novel motion vector-solving mechanism is proposed to provide nonzero velocity for the end-effector to solve the problem of limiting the solution of the motion vector to a fixed coordinate plane due to dimensionality constraints. A comparative analysis was conducted between the proposed algorithm and the existing methods, the improved artificial potential field method and the rapidly-random tree method under identical simulation conditions. The results indicate that the 3D-AMM method successfully plans paths with smoother trajectories and reduces the path length by 20.03% to 36.9%. Additionally, the experimental comparison outcomes affirm the feasibility and effectiveness of this method for obstacle avoidance in industrial scenarios. This paper proposes a 3D-AMM algorithm for manipulator path planning in Cartesian space with multiple obstacles. This method effectively solves the problem of the artificial potential field method easily falling into local minimum points and the low path planning success rate of the rapidly-exploring random tree method.
  Citation: Industrial Robot
  PubDate: 2024-05-07
  DOI: 10.1108/IR-11-2023-0307
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Movement and binding control strategy based on a new type of rebar-binding
robot
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  Authors: Dong Huan Shen, Shuai Guo, Hao Duan, Kehao Ji, Haili Jiang
  Abstract: The paper focuses on the issue of manual rebar-binding tasks in the construction industry, which are marked by high labor intensity, high costs and inefficient operations. The rebar-binding robots that are currently available are not fully mature. Most of them can only bind one or two nodes in one position, which leads to significant time wastage in movement. Based on a new type of rebar-binding robot, this paper aims to propose a new movement and binding control that reduces manpower and enhances efficiency. The robot is combined with photoelectric sensors, travel switches and other sensors. It is supposed to move accurately and run in a limited area on the rebar mesh through logical judgment, speed control and position control. Machine vision is used by the robot to locate the rebar nodes and then adjusts the binding-gun position to ensure that multiple rebar nodes are bound sequentially. By moving on the rebar mesh with accuracy, the robot meets the positioning accuracy requirements of the binding module, with experimental testing accuracy within 5 mm. Furthermore, its ability to bind four rebar nodes in one place results in a high efficiency and a binding effect that meets building standards. The innovative design of the robot can adapt itself to the rebar mesh, move accurately to the target position and bind four nodes at that position, which reduces the number of movements on the mesh. Repetitive and heavy rebar-binding tasks can be efficiently completed by the robot, which saves human resources, reduces worker labor intensity and reduces construction overhead. It provides a more feasible and practical solution for using robots to bind rebar nodes.
  Citation: Industrial Robot
  PubDate: 2024-05-03
  DOI: 10.1108/IR-12-2023-0326
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Contact localization from soft tactile array sensor using tactile image
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  Authors: Baoxu Tu, Yuanfei Zhang, Kang Min, Fenglei Ni, Minghe Jin
  Abstract: This paper aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image. The authors used three feature extraction methods: handcrafted features, convolutional features and autoencoder features. Subsequently, these features were mapped to contact locations through a contact location regression network. Finally, the network performance was evaluated using spherical fittings of three different radii to further determine the optimal feature extraction method. This paper aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image. This research indicates that data collected by probes can be used for contact localization. Introducing a batch normalization layer after the feature extraction stage significantly enhances the model’s generalization performance. Through qualitative and quantitative analyses, the authors conclude that convolutional methods can more accurately estimate contact locations. The paper provides both qualitative and quantitative analyses of the performance of three contact localization methods across different datasets. To address the challenge of obtaining accurate contact locations in quantitative analysis, an indirect measurement metric is proposed.
  Citation: Industrial Robot
  PubDate: 2024-04-30
  DOI: 10.1108/IR-01-2024-0008
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Simplified model to study the kinematics of manipulators with
parallelogram linkages
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  Authors: Omar Malla, Madhavan Shanmugavel
  Abstract: Parallelogram linkages are used to increase the stiffness of manipulators and allow precise control of end-effectors. They help maintain the orientation of connected links when the manipulator changes its position. They are implemented in many palletizing robots connected with binary, ternary and quaternary links through both active and passive joints. This limits the motion of some joints and hence results in relative and negative joint angles when assigning coordinate axes. This study aims to provide a simplified accurate model for manipulators built with parllelogram linkages to ease the kinematics calculations. This study introduces a simplified model, replacing each parallelogram linkage with a single (binary) link with an active and a passive joint at the ends. This replacement facilitates countering motion while preserving subsequent link orientations. Validation of kinematics is performed on palletizing manipulators from five different OEMs. The validation of Dobot Magician and ABB IRB1410 was carried out in real time and in their control software. Other robots from ABB, Yaskawa, Kuka and Fanuc were validated using control environments and simulators. The proposed model enables the straightforward derivation of forward kinematics and transforms hybrid robots into equivalent serial-link robots. The model demonstrates high accuracy streamlining the derivation of kinematics. The proposed model facilitates the use of classical methods like the Denavit–Hartenberg procedure with ease. It not only simplifies kinematics derivation but it also helps in robot control and motion planning within the workspace. The approach can also be implemented to simplify the parallelogram linkages of robots with higher degrees of freedom such as the IRB1410.
  Citation: Industrial Robot
  PubDate: 2024-04-30
  DOI: 10.1108/IR-01-2024-0046
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Prototyping of compliant grippers using FFF and TPU
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  Authors: Hesham Mohsen Hussein Omar, Mohamed Fawzy Aly Mohamed, Said Megahed
  Abstract: The purpose of this paper is to investigate the process of fused filament fabrication (FFF) of a compliant gripper (CG) using thermoplastic polyurethane (TPU) material. The paper studies the applicability of different CG designs and the efficiency of some design parameters. After reviewing a number of different papers, two designs were selected for a number of exploratory experiments. Using design of experiments (DOE) techniques to identify important design parameters. Finally, the efficiency of the parts was investigated. The research finds that a simpler design sacrifices some effectiveness in exchange for a remarkable decrease in production cost. Decreasing infill percentage of previous designs and 3D printing them, out of TPU, experimenting with different parameters yields functional products. Moreover, the paper identified some key parameters for further optimization attempts of such prototypes. The cost of conducting FFF experiments for TPU increases dramatically with product size, number of parameters studied and the number of experiments. Therefore, all three of these factors had to be kept at a minimum. Further confirmatory experiments encouraged. This paper addresses an identified need to investigate applications of FFF and TPU in manufacturing functional efficient flexible mechanisms, grippers specifically. While most research focused on designing for increased performance, some research lacks discussion on design philosophy, as well as manufacturing issues. As the needs for flexible grippers vary from high-performance grippers to lower performance grippers created for specific functions/conditions, some effectiveness can be sacrificed to reduce cost, reduce complexity and improve applicability in different robotic assemblies and environments.
  Citation: Industrial Robot
  PubDate: 2024-04-22
  DOI: 10.1108/IR-11-2023-0311
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
LIDAR-based SLAM system for autonomous vehicles in degraded point cloud
scenarios: dynamic obstacle removal
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  Authors: Qihua Ma, Qilin Li, Wenchao Wang, Meng Zhu
  Abstract: This study aims to achieve superior localization and mapping performance in point cloud degradation scenarios through the effective removal of dynamic obstacles. With the continuous development of various technologies for autonomous vehicles, the LIDAR-based Simultaneous localization and mapping (SLAM) system is becoming increasingly important. However, in SLAM systems, effectively addressing the challenges of point cloud degradation scenarios is essential for accurate localization and mapping, with dynamic obstacle removal being a key component. This paper proposes a method that combines adaptive feature extraction and loop closure detection algorithms to address this challenge. In the SLAM system, the ground point cloud and non-ground point cloud are separated to reduce the impact of noise. And based on the cylindrical projection image of the point cloud, the intensity features are adaptively extracted, the degradation direction is determined by the degradation factor and the intensity features are matched with the map to correct the degraded pose. Moreover, through the difference in raster distribution of the point clouds before and after two frames in the loop process, the dynamic point clouds are identified and removed, and the map is updated. Experimental results show that the method has good performance. The absolute displacement accuracy of the laser odometer is improved by 27.1%, the relative displacement accuracy is improved by 33.5% and the relative angle accuracy is improved by 23.8% after using the adaptive intensity feature extraction method. The position error is reduced by 30% after removing the dynamic target. Compared with LiDAR odometry and mapping algorithm, the method has greater robustness and accuracy in mapping and localization.
  Citation: Industrial Robot
  PubDate: 2024-04-10
  DOI: 10.1108/IR-01-2024-0001
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Attitude oscillation suppression control of a XK-I spherical robot
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  Authors: Rui Lin, Qiguan Wang, Xin Yang, Jianwen Huo
  Abstract: In complex environments, a spherical robot has great application value. When the pendulum spherical robot is stopped or disturbed, there will be a periodic oscillation. This situation will seriously affect the stability of the spherical robot. Therefore, this paper aims to propose a control method based on backstepping and disturbance observers for oscillation suppression. This paper analyzes the mechanism of oscillation. The oscillation model of the spherical robot is constructed and the relationship between the oscillation and the internal structure of the sphere is analyzed. Based on the oscillation model, the authors design the oscillation suppression control of the spherical robot using the backstepping method. At the same time, a disturbance observer is added to suppress the disturbance. It is found that the control system based on backstepping and disturbance observer is simple and efficient for nonlinear models. Compared with the PID controller commonly used in engineering, this control method has a better control effect. The proposed method can provide a reliable and effective stability scheme for spherical robots. The problem of instability in real motion is solved. In this paper, the oscillation model of a spherical robot is innovatively constructed. Second, a new backstepping control method combined with a disturbance observer for the spherical robot is proposed to suppress the oscillation.
  Citation: Industrial Robot
  PubDate: 2024-04-10
  DOI: 10.1108/IR-11-2023-0294
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Localization of asparagus spears using time-of-flight imaging for robotic
harvesting
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  Authors: Matthew Peebles, Shen Hin Lim, Mike Duke, Benjamin Mcguinness, Chi Kit Au
  Abstract: Time of flight (ToF) imaging is a promising emerging technology for the purposes of crop identification. This paper aim to presents localization system for identifying and localizing asparagus in the field based on point clouds from ToF imaging. Since the semantics are not included in the point cloud, it contains the geometric information of other objects such as stones and weeds other than asparagus spears. An approach is required for extracting the spear information so that a robotic system can be used for harvesting. A real-time convolutional neural network (CNN)-based method is used for filtering the point cloud generated by a ToF camera, allowing subsequent processing methods to operate over smaller and more information-dense data sets, resulting in reduced processing time. The segmented point cloud can then be split into clusters of points representing each individual spear. Geometric filters are developed to eliminate the non-asparagus points in each cluster so that each spear can be modelled and localized. The spear information can then be used for harvesting decisions. The localization system is integrated into a robotic harvesting prototype system. Several field trials have been conducted with satisfactory performance. The identification of a spear from the point cloud is the key to successful localization. Segmentation and clustering points into individual spears are two major failures for future improvements. Most crop localizations in agricultural robotic applications using ToF imaging technology are implemented in a very controlled environment, such as a greenhouse. The target crop and the robotic system are stationary during the localization process. The novel proposed method for asparagus localization has been tested in outdoor farms and integrated with a robotic harvesting platform. Asparagus detection and localization are achieved in real time on a continuously moving robotic platform in a cluttered and unstructured environment.
  Citation: Industrial Robot
  PubDate: 2024-04-08
  DOI: 10.1108/IR-01-2024-0009
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Multi-robot navigation based on velocity obstacle prediction in dynamic
crowded environments
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  Authors: Yimei Chen, Yixin Wang, Baoquan Li, Tohru Kamiya
  Abstract: The purpose of this paper is to propose a new velocity prediction navigation algorithm to develop a conflict-free path for robots in dynamic crowded environments. The algorithm BP-prediction and reciprocal velocity obstacle (PRVO) combines the BP neural network for velocity PRVO to accomplish dynamic collision avoidance. This presented method exhibits innovation by anticipating ahead velocities using BP neural networks to reconstruct the velocity obstacle region; determining the optimized velocity corresponding to the robot’s scalable radius range from the error generated by the non-holonomic robot tracking the desired trajectory; and considering acceleration constraints, determining the set of multi-step reachable velocities of non-holonomic robot in the space of velocity variations. The method is validated using three commonly used metrics of collision rate, travel time and average distance in a comparison between simulation experiments including multiple differential drive robots and physical experiments using the Turtkebot3 robot. The experimental results show that our method outperforms other RVO extension methods on the three metrics. In this paper, the authors propose navigation algorithms capable of adaptively selecting the optimal speed for a multi-robot system to avoid robot collisions during dynamic crowded interactions.
  Citation: Industrial Robot
  PubDate: 2024-04-08
  DOI: 10.1108/IR-12-2023-0337
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Calibration strategies for enhancing accuracy in serial industrial robots
for orbital milling applications
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  Authors: Mohamed Slamani, Hocine Makri, Aissa Boudilmi, Ilian A. Bonev, Jean-Francois Chatelain
  Abstract: This research paper aims to optimize the calibration process for an ABB IRB 120 robot, specifically for robotic orbital milling applications, by introducing and validating the use of the observability index and telescopic ballbar for accuracy enhancement. The study uses the telescopic ballbar and an observability index for the calibration of an ABB IRB 120 robot, focusing on robotic orbital milling. Comparative simulation analysis selects the O3 index. Experimental tests, both static and dynamic, evaluate the proposed calibration approach within the robot’s workspace. The proposed calibration approach significantly reduces circularity errors, particularly in robotic orbital milling, showcasing effectiveness in both static and dynamic modes at various tool center point speeds. The study focuses on a specific robot model and application (robotic orbital milling), limiting generalizability. Further research could explore diverse robot models and applications. The findings offer practical benefits by enhancing the accuracy of robotic systems, particularly in precision tasks like orbital milling, providing a valuable calibration method. While primarily technological, improved robotic precision can have social implications, potentially influencing fields where robotic applications are crucial, such as manufacturing and automation. This study’s distinctiveness lies in advancing the accuracy and precision of industrial robots during circular motions, specifically tailored for orbital milling applications. The innovative approach synergistically uses the observability index and telescopic ballbar to achieve these objectives.
  Citation: Industrial Robot
  PubDate: 2024-03-15
  DOI: 10.1108/IR-12-2023-0334
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Piston-like particle jamming for enhanced stiffness adjustment of soft
robotic arm
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  Authors: Tianlei Wang, Fei Ding, Zhenxing Sun
  Abstract: Stiffness adjusting ability is essential for soft robotic arms to perform complex tasks. A soft state enables dexterous operation and safe interaction, while a rigid state enables large force output or heavy weight carrying. However, making a compact integration of soft actuators with powerful stiffness adjusting mechanisms is challenging. This study aims to develop a piston-like particle jamming mechanism for enhanced stiffness adjustment of a soft robotic arm. The arm has two pairs of differential tendons for spatial bending, and a jamming core consists of four jamming units with particles sealed inside braided tubes for stiffness adjustment. The jamming core is pushed and pulled smoothly along the tendons by a piston, which is then driven by a motor and a ball screw mechanism. The tip displacement of the arm under 150 N jamming force and no more than 0.3 kg load is minimal. The maximum stiffening ratio measured in the experiment under 150 N jamming force is up to 6–25 depends on the bending direction and added load of the arm, which is superior to most of the vacuum powered jamming method. The proposed robotic arm makes an innovative compact integration of tendon-driven robotic arm and motor-driven piston-like particle jamming mechanism. The jamming force is much larger compared to conventional vacuum-powered systems and results in a superior stiffening ability.
  Citation: Industrial Robot
  PubDate: 2024-03-04
  DOI: 10.1108/IR-11-2023-0305
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)
Fuzzy logic system-based force tracking control of robot in highly dynamic
environments
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  Authors: Chengguo Liu, Junyang Li, Zeyu Li, Xiutao Chen
  Abstract: The study aims to equip robots with the ability to precisely maintain interaction forces, which is crucial for tasks such as polishing in highly dynamic environments with unknown and varying stiffness and geometry, including those found in airplane wings or thin, soft materials. The purpose of this study is to develop a novel adaptive force-tracking admittance control scheme aimed at achieving a faster response rate with higher tracking accuracy for robot force control. In the proposed method, the traditional admittance model is improved by introducing a pre-proportional-derivative controller to accelerate parameter convergence. Subsequently, the authors design an adaptive law based on fuzzy logic systems (FLS) to compensate for uncertainties in the unknown environment. Stability conditions are established for the proposed method through Lyapunov analysis, which ensures the force tracking accuracy and the stability of the coupled system consisting of the robot and the interaction environment. Furthermore, the effectiveness and robustness of the proposed control algorithm are demonstrated by simulation and experiment. A variety of unstructured simulations and experimental scenarios are designed to validate the effectiveness of the proposed algorithm in force control. The outcomes demonstrate that this control strategy excels in providing fast response, precise tracking accuracy and robust performance. In real-world applications spanning industrial, service and medical fields where accurate force control by robots is essential, the proposed method stands out as both practical and straightforward, delivering consistently satisfactory performance across various scenarios. This research introduces a novel adaptive force-tracking admittance controller based on FLS and validated through both simulations and experiments. The proposed controller demonstrates exceptional performance in force control within environments characterized by unknown and varying.
  Citation: Industrial Robot
  PubDate: 2024-02-15
  DOI: 10.1108/IR-12-2023-0312
  Issue No: Vol. ahead-of-print, No. ahead-of-print (2024)

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