Dynamic modeling and trajectory tracking control method of segmented linkage cable-driven hyper-redundant robot

被引:41
作者
Peng, Jianqing [1 ,2 ,3 ]
Xu, Wenfu [1 ]
Yang, Taiwei [1 ]
Hu, Zhonghua [1 ]
Liang, Bin [4 ]
机构
[1] Harbin Inst Technol, Sch Mech Engn & Automat, Shenzhen 518055, Peoples R China
[2] Sun Yat Sen Univ Shenzhen, Sch Intelligent Syst Engn, Shenzhen 518055, Peoples R China
[3] Chinese Univ Hong Kong, Dept Mech & Automat Engn, Shatin, Hong Kong, Peoples R China
[4] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
基金
国家重点研发计划; 中国博士后科学基金;
关键词
Cable-driven hyper-redundant robots; Series-parallel coupling; Trajectory tracking; Dynamic feedforward control; Co-simulation system; INVERSE KINEMATICS; SNAKE ROBOTS; MANIPULATOR; ARM; OPTIMIZATION;
D O I
10.1007/s11071-020-05764-7
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The dynamics modeling and trajectory optimization of a segmented linkage cable-driven hyper-redundant robot (SL-CDHRR) become more challenging, since there are multiple couplings between the active cables, passive cables, joints and end-effector. To deal with these problems, this paper proposes a dynamic modeling and trajectory tracking control methods for such type of CDHRR, i.e., SL-CDHRR. First, the multi-coupling kinematics equation (i.e., cable-joint-end) of the hyper-redundant robot is derived. Then, according to the transmission characteristics of the hybrid active/passive segmented linkage, the dynamic equation of series-parallel coupling is derived. It consists of parallel-active dynamics and series-passive dynamics. Furthermore, using the tension of active cables and the pose of the end-effector as optimization indicators, a trajectory tracking framework was constructed by the combination of dynamic feedforward control and PD control. The multi-objective particle swarm optimization method is used to achieve the simultaneous optimization of the energy indicator and control accuracy indicator during the trajectory tracking process. Finally, a MATLAB/SimMechanics co-simulation system is built, and the proposed methods are verified by the built co-simulation system.
引用
收藏
页码:233 / 253
页数:21
相关论文
共 41 条
[1]  
AGRAWAL SK, 1994, IEEE INT CONF ROBOT, P1581, DOI 10.1109/ROBOT.1994.351364
[2]   Real-time Inverse Kinematics of (2n+1) DOF hyper-redundant manipulator arm via a combined numerical and analytical approach [J].
Ananthanarayanan, Hariharan ;
Ordonez, Raul .
MECHANISM AND MACHINE THEORY, 2015, 91 :209-226
[3]   Robust trajectory tracking control of cable-driven parallel robots [J].
Asl, Hamed Jabbari ;
Yoon, Jungwon .
NONLINEAR DYNAMICS, 2017, 89 (04) :2769-2784
[4]   Adaptive robust control of fully constrained cable robots: singular perturbation approach [J].
Babaghasabha, Reza ;
Khosravi, Mohammad A. ;
Taghirad, Hamid D. .
NONLINEAR DYNAMICS, 2016, 85 (01) :607-620
[5]   Solving Two-Dimensional Chemical Engineering Problems Using the Chebyshev Orthogonal Collocation Technique [J].
Binous, Housam ;
Kaddeche, Slim ;
Bellagi, Ahmed .
COMPUTER APPLICATIONS IN ENGINEERING EDUCATION, 2016, 24 (01) :144-155
[6]   Snake robots A review of research, products and applications [J].
Bogue, Robert .
INDUSTRIAL ROBOT-AN INTERNATIONAL JOURNAL, 2014, 41 (03) :253-258
[7]   Nuclear snake-arm robots [J].
Buckingham, Rob ;
Graham, Andrew .
INDUSTRIAL ROBOT-AN INTERNATIONAL JOURNAL, 2012, 39 (01) :6-11
[8]   Reinforcement Learning-Based Adaptive Optimal Exponential Tracking Control of Linear Systems With Unknown Dynamics [J].
Chen, Ci ;
Modares, Hamidreza ;
Xie, Kan ;
Lewis, Frank L. ;
Wan, Yan ;
Xie, Shengli .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2019, 64 (11) :4423-4438
[9]   A MODAL APPROACH TO HYPER-REDUNDANT MANIPULATOR KINEMATICS [J].
CHIRIKJIAN, GS ;
BURDICK, JW .
IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, 1994, 10 (03) :343-354
[10]  
Choi DG, 2007, 2007 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-9, P1821