Self-adaptive MRPBIL-DE for 6D robot multiobjective trajectory planning

作者：

Highlights：

• Efficient self-adaptive multiobjective meta-heuristic (MOMH) algorithm.

• Use of success-history based parameter adaptation for optimisation parameters.

• Comparative results of a robot path planning problem with well-established MOMHs.

• New design results set as the baseline for further studies.

摘要

•Efficient self-adaptive multiobjective meta-heuristic (MOMH) algorithm.•Use of success-history based parameter adaptation for optimisation parameters.•Comparative results of a robot path planning problem with well-established MOMHs.•New design results set as the baseline for further studies.

论文关键词：Multiobjective meta-heuristic algorithm,Robot trajectory planning multiobjective,Optimisation,Self-adaptive algorithm,Time-jerk minimisation

论文评审过程：Received 18 September 2018, Revised 29 April 2019, Accepted 16 June 2019, Available online 18 June 2019, Version of Record 24 June 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.06.033