Research on Robot Path Planning Technology by Integrating Particle Swarm Optimization Algorithm and DWA Algorithm

Abstract

Path planning technology is one of the key technologies for robots to achieve autonomous navigation and complete transportation tasks. This article mainly analyzes and studies two commonly used intelligent bio-inspired path planning algorithms: Particle Swarm Optimization (PSO) algorithm and Dynamic Window Approach (DWA) algorithm. We have made improvements and optimizations to both algorithms, and designed a fusion algorithm that combines their advantages. The paper focuses on studying the global path of the PSO algorithm, followed by research on the local path using the DWA algorithm. Finally, we tested the improved PSO-DWA fusion algorithm using MATLAB. The test results show that this fusion algorithm can obtain the global optimal path by utilizing known global information while effectively avoiding unknown dynamic obstacles. It can better accomplish path planning tasks in practical situations with superior performance, improve robot safety during task execution, and ensure subsequent execution efficiency.