Path Planning of Sweeping Robot Based on Improved Particle Swarm Optimization

In order to solve the problems of low efficiency, long searching time and high path cost of the domestic sweeping robots, a method of improved particle swarm optimization (IPSO) algorithm with symmetrically linearly decreasing inertia weight was used to reasonably plan the path. The symmetric model analyzed the inertia weight of the particle swarm optimization algorithm, the appropriate decreasing rate of inertia weight was found by this paper, and reduced the inertia weight of particle swarm optimization algorithm at a symmetric decreasing rate, so that particle swarm optimization had different optimization ability in different stages, and made its search path effect compare with the search path effect of basic particle swarm optimization algorithm. The experimental results showed that the particle algorithm with symmetrically linearly decreasing inertia weight had the advantages of high accuracy, good stability and not easy to fall into local optimization. The algorithm can effectively carry out global path planning for household sweeping robots, thus providing a theoretical and practical basis for the path planning of household sweeping robots.