Probabilistic pursuit-evasion games: theory, implementation, and experimental evaluation

We consider the problem of having a team of Unmanned Aerial Vehicles (UAV) and Unmanned Ground Vehicles (UGV) pursue a second team of evaders while concurrently building a map in an unknown environment. We cast the problem in a probabilistic game theoretic framework and consider two computationally feasible greedy pursuit policies: local-max and global-max. To implement this scenario on real UAVs and UGVs, we propose a distributed hierarchical hybrid system architecture which emphasizes the autonomy of each agent yet allows for coordinated team efforts. We describe the implementation of the architecture on a fleet of UAVs and UGVs, detailing components such as high-level pursuit policy computation, map building and inter-agent communication, and low-level navigation, sensing, and control. We present both simulation and experimental results of real pursuit-evasion games involving our fleet of UAVs and UGVs and evaluate the pursuit policies relating expected capture times to the speed an...

• Type: Journal
• Year: 2002
• Where: TROB
• Authors: René Vidal, Omid Shakernia, H. Jin Kim, David Hyunchul Shim, Shankar Sastry
• Keywords: Feasible Greedy Pursuit, Pursuit Policies, TROB 2002, Unmanned Aerial Vehicles