Comparisons among Six Numerical Methods for Solving Repetitive Motion Planning of Redundant Robot Manipulators

Zhijun Zhang, Lingdong Kong, Ziyi Yan, Ke Chen, Shuai Li, Xilong Qu, Ning Tan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

To ensure that each joint of redundant robot manipulators can return to its initial state when completes a closed-path tracking task, a repetitive motion planning (RMP) scheme is presented. On the basis of a quadratic programming (QP) framework, this RMP can be equivalently converted into a linear-variational-inequality (LVI) problem, and then into a piecewise linear projection equation (PLPE). In this paper, three novel numerical methods (i.e., M3, M5 and M6) and three traditional numerical methods (i.e., 94LVI, E47 and M4) are exploited, analyzed, and compared to solve PLPE, as well as RMP. The convergence of M5 method is theoretically proved, and that of M3 and M6 methods is analyzed by simulations. Moreover, comparative simulations of two complex path tracking tasks performed on a PUMA560 robot manipulator further verify the feasibility and effectiveness of the proposed numerical methods.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1645-1652
Number of pages8
ISBN (Electronic)9781728103761
DOIs
Publication statusPublished - 2 Jul 2018
Event2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018 - Kuala Lumpur, Malaysia
Duration: 12 Dec 201815 Dec 2018

Publication series

Name2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018

Conference

Conference2018 IEEE International Conference on Robotics and Biomimetics, ROBIO 2018
CountryMalaysia
CityKuala Lumpur
Period12/12/1815/12/18

Keywords

  • Complex path tracking
  • Motion planning
  • Quadratic programming
  • Robot kinematics

ASJC Scopus subject areas

  • Biotechnology
  • Artificial Intelligence
  • Human-Computer Interaction

Cite this