Application of Robot Obstacle Avoidance Algorithm and Attack Strategy on ROS

Abstract

China Robot Competition, which integrates the theory and practice of multi-disciplinary intelligent robot system, is one of the most influential robot competitions in China. In this paper, we apply RRT * and APF to the Middle Size Simulation League of soccer on ROS and propose an attack strategy based on extremum. Our experiments showed that the implementation of RRT* and APF optimizes the multiple iterations existing in original obstacle avoidance algorithm and greatly improves the performance of robots when there are fewer obstacles and the maximum speed of obstacle avoidance is limited. Besides, our attack strategy has proved effective on boosting the chances of goal and helped the Central South University to win the championship of China Robot Competition Middle Size Simulation League in 2021.