Pursuit-Evasion Tracking Control Grounded in Intelligent Computing

This paper takes the currently popular quadruped robot as the research object and proposes an intelligent-algorithm-based encirclement strategy to deal with the Traveling Salesman Problem (TSP) caused by complex indoor structures. This strategy can effectively plan the optimal path in multi-obstacle and narrow-space environments, ensuring that the quadruped robot can complete tasks quickly and accurately. Moreover, to solve the problem of precise pursuit and evasion control in indoor enclosed spaces, this paper introduces image analysis, machine learning algorithms, uncertain reasoning, and traditional search-solving strategies. As a result, the quadruped robot can adjust its path in complex dynamic environments, avoid obstacles, and maintain effective tracking of the target.