Multi-objective Robot Path Planning based on Bare Bones Particle Swarm Optimization with Crossover Operation

摘要

This paper proposes an improved multi-objective robot path planning based on bare bones particle swarm optimization and crossover operation of Genetic algorithm. First, the path planning is mathematically formulated as a constrained multiobjective optimization problem with two indices, i.e. the path length and the safety degree of a path. Then, a multi-objective bare bones particle swarm optimization combined with crossover operation is developed to solve the above model. Aiming at the infeasible paths blocked by obstacles in evolution, three modified crossover operations, i.e. multi-point crossover, uniform crossover and arithmetic crossover, are designed to improve the feasibility of an infeasible path. Finally, simulation results confirm the effectiveness of our algorithm.