Orientation Tracking Incorporated Multicriteria Control for Redundant Manipulators With Dynamic Neural Network

被引:6
作者
Liu, Mei [1 ,2 ]
Shang, Mingsheng [1 ,2 ]
机构
[1] Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing Key Lab Big Data & Intelligent Comp, Chongqing 400714, Peoples R China
[2] Univ Chinese Acad Sci, Chongqing Sch, Beijing 100000, Peoples R China
基金
中国国家自然科学基金;
关键词
Computational complexity; dynamic neural network (DNN); kinematic control; multicriteria control scheme; orientation tracking; KINEMATIC REDUNDANCY; OBSTACLE AVOIDANCE; ROBOT; STABILITY; SCHEME; RNN;
D O I
10.1109/TIE.2023.3273253
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Existing neural-network-based solutions for controlling a redundant robot are trapped by the relatively high computational complexity and the lack of the incorporation of orientation tracking. In order to remedy these two weaknesses, this article proposes a new multicriteria control scheme aided with a training-free dynamic neural network (DNN), which simultaneously considers the orientation-tracking constraint and physical constraints. Meanwhile, compared with existing methods for handling the same task, the proposed DNN solver is of low computational complexity. Theoretical analyses confirm that the proposed scheme based on the DNN solver globally and exponentially converges to the theoretical solution of the robotic motion generation. Besides, illustrative simulations and physical experiments based on a Franka Emika Panda manipulator demonstrate the validity and feasibility of the proposed scheme with the DNN solver.
引用
收藏
页码:3801 / 3810
页数:10
相关论文
共 36 条
  • [1] Boyd S., 2004, CONVEX OPTIMIZATION, DOI DOI 10.1017/CBO9780511804441
  • [2] Six-DOF Impedance Control of Dual-Arm Cooperative Manipulators
    Caccavale, Fabrizio
    Chiacchio, Pasquale
    Marino, Alessandro
    Villani, Luigi
    [J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2008, 13 (05) : 576 - 586
  • [3] Exponential stability of globally projected dynamic systems
    Gao, XB
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2003, 14 (02): : 426 - 431
  • [4] On the structure of minimum effort solutions with application to kinematic redundancy resolution
    Gravagne, IA
    Walker, ID
    [J]. IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, 2000, 16 (06): : 855 - 863
  • [5] Saturation-Allowed Neural Dynamics Applied to Perturbed Time-Dependent System of Linear Equations and Robots
    Jin, Long
    Liufu, Ying
    Lu, Huiyan
    Zhang, Zhijun
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2021, 68 (10) : 9844 - 9854
  • [6] Perturbed Manipulability Optimization in a Distributed Network of Redundant Robots
    Jin, Long
    Zhang, Jiazheng
    Luo, Xin
    Liu, Mei
    Li, Shuai
    Xiao, Lin
    Yang, Zihao
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2021, 68 (08) : 7209 - 7220
  • [7] Novel Joint-Drift-Free Scheme at Acceleration Level for Robotic Redundancy Resolution With Tracking Error Theoretically Eliminated
    Jin, Long
    Xie, Zhengtai
    Liu, Mei
    Chen, Ke
    Li, Chunxu
    Yang, Chenguang
    [J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2021, 26 (01) : 90 - 101
  • [8] G2-Type SRMPC Scheme for Synchronous Manipulation of Two Redundant Robot Arms
    Jin, Long
    Zhang, Yunong
    [J]. IEEE TRANSACTIONS ON CYBERNETICS, 2015, 45 (02) : 153 - 164
  • [9] Zeroing Neural Network With Fuzzy Parameter for Computing Pseudoinverse of Arbitrary Matrix
    Katsikis, Vasilios N.
    Stanimirovic, Predrag S.
    Mourtas, Spyridon D.
    Xiao, Lin
    Karabasevic, Darjan
    Stanujkic, Dragisa
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2022, 30 (09) : 3426 - 3435
  • [10] Modified Configuration Control With Potential Field for Inverse Kinematic Solution of Redundant Manipulator
    Kim, Jaehyung
    Jie, Wang
    Kim, Hyun Hee
    Lee, Min Cheol
    [J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2021, 26 (04) : 1782 - 1790