Optimal trajectory planning for robotic manipulators using improved teaching-learning-based optimization algorithm

Xueshan Gao, Yu Mu*, Yongzhuo Gao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)

Abstract

Purpose-The purpose of this paper is to propose a method of optimal trajectory planning for robotic manipulators that applies an improved teaching-learning-based optimization (ITLBO) algorithm. Design/methodology/approach-The ITLBO algorithm possesses better ability to escape from the local optimum by integrating the original TLBO with variable neighborhood search. The trajectory of robotic manipulators complying with the kinematical constraints is constructed by fifth-order B-spline curves. The objective function to be minimized is execution time of the trajectory. Findings-Experimental results with a 6-DOF robotic manipulator applied to surface polishing of metallic workpiece verify the effectiveness of the method. Originality/value-The presented ITLBO algorithm is more efficient than the original TLBO algorithm and its variants. It can be applied to any robotic manipulators to generate time-optimal trajectories.

Original languageEnglish
Pages (from-to)308-316
Number of pages9
JournalIndustrial Robot
Volume43
Issue number3
DOIs
Publication statusPublished - 16 May 2016

Keywords

  • B-spline
  • Robotic manipulators
  • Teaching-learning-based optimization
  • Trajectory planning
  • Variable neighbourhood search

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