Optimal path finding in stochastic quasi-dynamic environments using particle swarm optimization
作者：
Highlights：
• Develop a stochastic mathematical model to handle variable obstacle areas problem.
• We introduce a parameter that captures the degrees of freedom of the search space.
• Continuous space was used, and line integral was used to determine the path length.
• The proposed approach can be applied to regular and irregular obstacles as well.
• The proposed objective function does not produce infeasible paths.
摘要
•Develop a stochastic mathematical model to handle variable obstacle areas problem.•We introduce a parameter that captures the degrees of freedom of the search space.•Continuous space was used, and line integral was used to determine the path length.•The proposed approach can be applied to regular and irregular obstacles as well.•The proposed objective function does not produce infeasible paths.
论文关键词：Particle swarm optimization,PSO,Path planning,Risk factor,Stochastic environments
论文评审过程：Received 12 March 2021, Revised 12 June 2021, Accepted 31 July 2021, Available online 8 August 2021, Version of Record 16 August 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115706
