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An Obstacle Avoidance Control Strategy for DELTA Parallel Manipulator via Improved Genetic Algorithm

  • Hao Zheng
  • , Yihang Xu*
  • , Yuantao Li
  • , Guangtao Ran
  • , Jian Liu
  • *Corresponding author for this work
  • Southeast University, Nanjing

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Aiming at the requirement of the DELTA parallel manipulator for performing grasping operations, a method for obstacle avoidance based on a genetic algorithm is proposed. Firstly, the classical DELTA parallel manipulator is analyzed mathematically, and its model is simplified. Then, the motion space and inverse kinematics solutions of the DELTA parallel manipulator are solved by using the spatial geometry method. Secondly, a cylindrical envelope surface is added to the manipulator's end for distance calculation. This envelope surface ensures that obstacles do not collide with the manipulator during obstacle avoidance. Thirdly, an improved genetic algorithm is proposed for obstacle avoidance. Finally, the simulation results are given to verify the effectiveness and reliability of the proposed algorithm.

Original languageEnglish
Title of host publicationProceedings - 2022 37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1342-1346
Number of pages5
ISBN (Electronic)9781665465366
DOIs
StatePublished - 2022
Event37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022 - Beijing, China
Duration: 19 Nov 202220 Nov 2022

Publication series

NameProceedings - 2022 37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022

Conference

Conference37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022
Country/TerritoryChina
CityBeijing
Period19/11/2220/11/22

Keywords

  • DELTA parallel manipulator
  • Genetic algorithm
  • Inverse kinematics solution

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