Inverse Kinematic Parameters Calibration of 3-RPS Parallel Robot Based on Modified Differential Evolution

NAVIGATE

Table of Contents

STATISTICS

Viewed1363

Downloads946

Inverse Kinematic Parameters Calibration of 3-RPS Parallel Robot Based on Modified Differential Evolution

[HTML] PDF下载 (946)

[1]PENG Jinzhu,ZHANG Jianxin,ZENG Qingshan.Inverse Kinematic Parameters Calibration of 3-RPS Parallel Robot Based on Modified Differential Evolution[J].Journal of Zhengzhou University (Engineering Science),2022,43(05):1-7.[doi:10.13705/j.issn.1671-6833.2022.05.008]

Copy

Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 43卷 Number of periods: 2022 05 Page number: 1-7 Column: Public date: 2022-08-22

Title:: Inverse Kinematic Parameters Calibration of 3-RPS Parallel Robot Based on Modified Differential Evolution

Author(s):: PENG Jinzhu; ZHANG Jianxin; ZENG Qingshan; School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China

Keywords:: parallel robot; CMDE; parameter calibration; inverse kinematics

CLC:: N945. 12；TP242

DOI:: 10.13705/j.issn.1671-6833.2022.05.008

Abstract:: Due to the complex structure of parallel robot, the joint torque solved by the design parameters cannot drive the parallel robot to achieve the ideal position and pose. However, the pose accuracy of parallel robot directly affects the work quality. To improve the model accuracy of the parallel robot, the kinematic error model was established for the designed 3-RPS parallel robot. In addition, on the basis of the traditional differential evolution (DE), a competitive multi-mutation differential evolution (CMDE) algorithm was proposed to calibrate the model parameters. In this algorithm, two populations were designed for the local exploitation and global exploration, where each population contained three mutation strategies. Moreover, a competitive system was developed in each population to select the better strategy in the calibration process, which could obtain the best optimal parameters. The kinematic parameters by calibration were used to modify the inverse kinematics model, and the accuracy of the modified model was verified by Adams software. The simulation results show that the proposed CMDE could achieve 50% faster convergence speed and smaller final convergence value in comparison to DE method. Also, compared with PSO and DE algorithms, the proposed CMDE had the strongest anti-interference ability in the evolution process. Moreover, compared with calibration before, the improvements of 3-RPS parallel robot with three degrees of freedom were 73.5%, 88.7% and 95.2%, respectively.

References:: [1] NGUYEN H N, ZHOU J, KANG H J. A calibration method for enhancing robot accuracy through integration of an extended Kalman filter algorithm and an artificial neural network [ J ] . Neurocomputing, 2015, 151: 996-1005.
[2] 赵磊, 赵新华, 周海波, 等. 并联测量机柔性动力学建模与误差耦合[ J] . 光学精密工程, 2016, 24 (10) : 2471-2479.
ZHAO L, ZHAO X H, ZHOU H B, et al. Flexible dynamic modeling and error coupling of parallel measuring machine[ J] . Optics and precision engineering, 2016, 24(10) : 2471-2479.
[3] 王海芳, 李新庆, 乔湘洋, 等. 3-SPS / S 踝关节并联康复机构控制系统仿真[ J] . 东北大学学报( 自然科学版) , 2019, 40(3) : 310-314, 333.
WANG H F, LI X Q, QIAO X Y, et al. Simulation of 3-SPS / S parallel manipulator control system for ankle rehabilitation [ J ]. Journal of northeastern university (natural science), 2019, 40(3): 310-314, 333.
[4] 胡磊, 胡宁, 王立权, 等. 3SPS-1S 并联机构的仿人机械臂系统设计[ J] . 哈尔滨工程大学学报, 2015, 36(11) : 1515-1521, 1531.
HU L, HU N, WANG L Q, et al. 3SPS-1S parallel mechanism based humanoid manipulator system [ J ] . Journal of Harbin engineering university, 2015, 36 (11) : 1515-1521, 1531.
[5] ZHANG D S, XU Y D, YAO J T, et al. Analysis and optimization of a spatial parallel mechanism for a new 5-DOF hybrid serial-parallel manipulator[ J] . Chinese journal of mechanical engineering, 2018, 31: 54.
[6] 高建设, 王玉闯, 刘德平, 等. 新型四足步行机器人串并混联腿的轨迹规划与仿真研究[ J] . 郑州大学学报(工学版) , 2018, 39(2) : 23-27, 38.
GAO J S, WANG Y C, LIU D P, et al. Research on trajectory planning and simulation on the serial-parallel leg of a novel quadruped walking robot[ J] . Journal of Zhengzhou university ( engineering science ) , 2018,39(2) : 23-27, 38.
[7] ROTH Z, MOORING B, RAVANI B. An overview of robot calibration[ J] . IEEE journal on robotics and automation, 1987, 3(5) : 377-385.
[8] JUDD R P, KNASINSKI A B. A technique to calibrate industrial robots with experimental verification [ J] . IEEE transactions on robotics and automation, 1990,6(1) : 20-30.
[9] 刘宇哲, 吴军, 王立平, 等. 5 轴混联机床运动学标定的测量轨迹评价及误差补偿[ J] . 清华大学学报(自然科学版) , 2016, 56(10) : 1047-1054.
LIU Y Z, WU J, WANG L P, et al. Measurement trajectory evaluation and error compensation for kinematic calibration of a 5-axis hybrid machine tool[ J] . Journal of Tsinghua university ( science and technology) , 2016, 56(10) : 1047-1054.
[10] 高岳林, 武少华. 基于自适应粒子群算法的机器人路径规划[ J] . 郑州大学学报( 工学版) , 2020, 41 (4) : 46-51.
GAO Y L, WU S H. Robot path planning based on adaptive particle swarm optimization [ J ] . Journal of Zhengzhou university ( engineering science ) , 2020, 41(4) : 46-51.
[11] 张方方, 张文丽, 王婷婷. 基于速度补偿算法的多机器人编队控制研究 [ J] . 郑州大学学报 ( 工学版) , 2022, 43(2) : 1-6, 14.
ZHANG F F, ZHANG W L, WANG T T. Research on multi-robot formation control based on speed compensation algorithm [ J] . Journal of Zhengzhou university ( engineering science ) , 2022, 43 ( 2 ) : 1 - 6, 14.
[12] 赵磊, 闫照方, 栾倩倩, 等. 大空间运动 3-RRRU 并联机器人运动学标定与误差分析[ J] . 农业机械学报, 2021, 52(11) : 411-420.
ZHAO L, YAN Z F, LUAN Q Q, et al. Kinematic calibration and error analysis of 3-RRRU parallel robot in large overall motion [ J] . Transactions of the Chinese society for agricultural machinery, 2021, 52 (11) : 411-420.
[13] WANG W D, SONG H J, YAN Z Y, et al. A universal index and an improved PSO algorithm for optimal pose selection in kinematic calibration of a novel surgical robot[ J] . Robotics and computer-integrated manufacturing, 2018, 50: 90-101.
[14] 姜一舟, 于连栋, 常雅琪, 等. 基于改进差分进化算法的机器人运动学参数标定 [ J] . 光学精密工程, 2021, 29(7) : 1580-1588.
JIANG Y Z, YU L D, CHANG Y Q, et al. Robot calibration based on modified differential evolution algorithm[ J] . Optics and precision engineering, 2021, 29 (7) : 1580-1588.
[15] 寇斌, 郭士杰, 任东城. 改进粒子群算法的工业机器人几何参数标定 [ J] . 哈尔滨工业大学学报, 2022, 54(1) : 9-13.
KOU B, GUO S J, REN D C. Geometric parameter calibration of industrial robot based on improved particle swarm optimization[ J] . Journal of Harbin institute of technology, 2022, 54(1) : 9-13.
[16] LUO G Y, ZOU L, WANG Z L, et al. A novel kinematic parameters calibration method for industrial robot based on Levenberg-Marquardt and differential evolution hybrid algorithm[ J] . Robotics and computer-integrated manufacturing, 2021, 71: 102165.
[17] WANG Y, YU J J, PEI X. Fast forward kinematics algorithm for real-time and high-precision control of the 3-RPS parallel mechanism [ J] . Frontiers of mechanical engineering, 2018, 13(3) : 368-375.
[18] JOUBAIR A, SLAMANI M, BONEV I A. Kinematic calibration of a 3-DOF planar parallel robot [ J] . Industrial robot: an international journal, 2012, 39(4) : 392-400.
[19] 张宪民, 曾磊. 考虑减速机背隙的 3-RRR 并联机构的运动学标定[ J] . 华南理工大学学报( 自然科学版) , 2016, 44(7) : 47-54.
ZHANG X M, ZENG L. Kinematic calibration of 3- RRR parallel mechanism considering reducer backlash [ J] . Journal of South China university of technology ( natural science edition) , 2016, 44(7) : 47-54.
[20] STORN R, PRICE K. Differential evolution — a simple and efficient heuristic for global optimization over continuous spaces[ J] . Journal of global optimization, 1997, 11: 341-359.
[21] WANG Y, CAI Z X, ZHANG Q F. Differential evolution with composite trial vector generation strategies and control parameters[ J] . IEEE transactions on evolutionary computation, 2011, 15(1) : 55-66.
[22] 周雅兰, 徐志. 多变异策略的自适应差分演化算法 [ J] . 计算机科学, 2015, 42(6) : 247-250, 255.
ZHOU Y L, XU Z. Self-adaptive differential evolution with multi-mutation strategies[ J] . Computer science, 2015, 42(6) : 247-250, 255.
[23] GUI L, XIA X W, YU F, et al. A multi-role based differential evolution [ J ] . Swarm and evolutionary computation, 2019, 50: 100508.
[24] LIANG J, QIAO K J, YU K J, et al. Parameters estimation of solar photovoltaic models via a self-adaptive ensemble-based differential evolution [ J] . Solar energy, 2020, 207: 336-346.

Similar References:

Memo

Last Update: 2022-08-20