Research on Path Planning of Soccer Robot Based on Potential Field Improved Ant Colony Algorithm

Abstract

As an important branch of the current robot field, soccer robots have a wide range of application prospects. The robot soccer game is an effective means to test robot technology. In a robot soccer game, the robot is in a complex environment with real-time confrontation, and the real-time cooperation between robots is high. Aiming at the complexity of the traditional robot path planning algorithm, the artificial potential field method and ant colony optimization algorithm are studied in depth, integrating the advantages of the two, combined with the characteristics of the soccer robot system, an improved ant colony algorithm based on artificial potential field is proposed, and through computer simulation analysis and physical robot experiments, the results show that the algorithm can obtain the optimal path, which meets the real-time, feasibility and effectiveness requirements of soccer robot path planning. It is also possible to effectively improve the speed of route planning.