Collision free force closure workspace determination of reconfigurable planar cable driven parallel robot

Bingyao Wang, Bin Zi, Sen Qian, Dan Zhang

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

9 Citations (Scopus)

Abstract

This paper considers the problem of Collision Free Force Closure Workspace (CFFCW) determination for Reconfigurable Planar Cable-Driven Parallel Robots (RPCDPRs). The cluttered obstacles in environment and the radiate cable structure make this problem highly nontrivial. Firstly, the simplified model of general RPCDPR that with cluttered environment is proposed. Then, the critical support lines of obstacles together with the topological constraint of RPCDPRs are adopted to find the Collision-Free Area (CFA) from multi-obstacle environment. And inspired by grasps with friction, an algorithm that based on convexhull and convex hull mapping method is used to deal with the motion ranges of cable and CFFCW of RPCDPRs. Finally, the algorithm is demonstrated on several types of RPCDPRs and environments. The simulation results show that the proposed approach can effectively detect the CFFCW of RPCDPRs.

Original languageEnglish
Title of host publicationProceedings of 2016 Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages26-30
Number of pages5
ISBN (Electronic)9781509013623
DOIs
Publication statusPublished - 29 Aug 2016
Externally publishedYes
Event2016 Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2016 - Tokyo, Japan
Duration: 20 Jul 201622 Jul 2016

Publication series

NameProceedings of 2016 Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2016

Conference

Conference2016 Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2016
Country/TerritoryJapan
CityTokyo
Period20/07/1622/07/16

Keywords

  • collision free force closure workspace
  • grasp
  • reconfigurable cable-driven robots

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering
  • Control and Optimization

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