Path Planning of Mobile Robot Based on Hybrid Multi-Objective Bare Bones Particle Swarm Optimization With Differential Evolution

An improved path planning for mobile robots is proposed based on the hybrid multi-objective bare-bones particle swarm optimization with differential evolution. The mathematical model for robot path planning is firstly devised as a tri-objective optimization with three indices, i.e., the path length,...

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Bibliographic Details
Published in:IEEE access 2018-01, Vol.6, p.44542-44555
Main Authors: Zhang, Jian-Hua, Zhang, Yong, Zhou, Yong
Format: Article
Language:English
Subjects:
Algorithms
Collision avoidance
differential evolution
Evolutionary computation
Heuristic algorithms
Mobile robots
Multiple objective analysis
Mutation
Optimization
Particle swarm optimization
Path planning
Robot
Robots
Smoothness
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Summary:An improved path planning for mobile robots is proposed based on the hybrid multi-objective bare-bones particle swarm optimization with differential evolution. The mathematical model for robot path planning is firstly devised as a tri-objective optimization with three indices, i.e., the path length, the smoothness degree of a path, and the safety degree of a path. Then, a hybrid multi-objective bare bones particle swarm optimization is developed to generate feasible paths by combining infeasible paths blocked by obstacles with feasible paths via improved mutation strategies of differential evolution. In addition, a new Pareto domination with collision constraints is developed to select the personal best position of a particle according to the definition of the collision degree of a path. Simulation results confirm the effectiveness of our algorithm.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2864188