Path Planning of Service Robot Based on Improved Particle Swarm Optimization Algorithm

Abstract

In recent years, people’s lives have become more and more intelligent, and service robots have appeared in all aspects of people’s lives. It brings a lot of convenience for people’s quick life. The service robot must first ensure that it can accurately reach its destination. As one of the core contents of robot technology, path planning has important practical value and research significance. Therefore, the design of efficient algorithm to solve the path planning problem plays a key role in improving the robot technology. In this paper, an improved particle swarm optimization (PSO) algorithm is applied to the path planning of service robots. First of all, the irregular obstacles are handled by using an external circle to avoid the situation that the robot can not walk out of the deadlock area. For the particle swarm optimization (PSO), the linear decline strategy is used to deal with the inertia weight w, which makes the PSO have strong global convergence ability in the early stage and strong local convergence ability in the later stage. The shrinkage factor is introduced to ensure the convergence of the algorithm. At the same time, the selection mechanism and variation mechanism of genetic algorithm are integrated into PSO algorithm, and the PSO algorithm can jump out of the local optimal and accurately find the global optimal.