Research on real-time path planning and obstacle avoiding for mobile robot swarms based on an advanced artificial potential field method
Binglong Bao · 2023
Unmanned mobile robots have broad application prospects in space exploration. In order to meet the increasing technical requirements, it is of great practical significance to study robot cluster work, path planning, and obstacle avoidance. A method is proposed in this paper to achieve the functions mentioned above built on an improved artificial potential field (APF). By introducing a dynamic attractive factor based on the number of obstacles and setting different goal point information for leader and follower robots, obstacle avoidance navigation and cooperative following function can be achieved under the force of the potential field. Finally, using webots to build an environment and robots for simulation. The results and planned path map testify to the feasibility and effectiveness of this method.