Heterogeneous Performance of Swarm Collision Avoidance Strategies

Four prominent collision avoidance methods are Artificial Potential Fields, Artificial Potential Fields expressed as Control Barrier Functions, Control Barrier Functions, and Reciprocal Velocity Obstacles. Prior work often assumes all agents are using the same obstacle avoidance methods. The methods differ in computational scalability, how they react to different types of obstacles, and in how they react to agents with heterogenous collision avoidance methods. This paper explores the scenario robustness and scalability of these methods through three key navigation scenarios: different structures of stationary obstacles, circle-crossing collision avoidance benchmarks, and defense against an antagonistic swarm.