Scalable and practical pursuit-evasion with networked robots

In this paper, we consider the design and implementation of practical pursuit-evasion games with networked robots, where a communication network provides sensing-at-a-distance as well as a communication backbone that enables tighter coordination between pursuers. We first develop, using the theory of zero-sum This material is based in part upon work supported by the National Science Foundation under Grants No. CCF-0820230, CNS0540420, CNS-0325875 and CCR-0120778 and a gift from the Okawa Foundation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author (s) and do not necessarily reflect the views of the National Science Foundation. Marcos Vieira was supported in part by Grant 2229/03–0 from CAPES, Brazil. Marcos A. M. Vieira University of Southern California 3710 S. McClintock Avenue Ronald Tutor Hall (RTH) 418 Los Angeles, CA 90089 Tel.: +1-213-8215627 Fax: +1-213-7407285 E-mail: [email protected] Ramesh Govindan University of Southern California MC 2905 Ronald Tutor Hall (RTH412) 3710 S. McClintock Ave Los Angeles, CA 90089-2905 Tel: +1-213-7404509 Fax: +1-213-7407285 E-mail: [email protected] Gaurav S. Sukhatme University of Southern California MC 2905 Ronald Tutor Hall (RTH 405) 3710 South McClintock Avenue Los Angeles, California 90089-2905 Tel.:+1-213-7400218 Fax: +1-213-8215696 E-mail: [email protected] games, an algorithm that computes the minimal completion time strategy for pursuit-evasion when pursuers and evaders have same speed, and when all players make optimal decisions based on complete knowledge. Then, we extend this algorithm to when evader are significantly faster than pursuers. Unfortunately, these algorithms do not scale beyond a small number of robots. To overcome this problem, we design and implement a partition algorithm where pursuers capture evaders by decomposing the game into multiple multi-pursuer single-evader games. We show that the partition algorithm terminates, has bounded capture time, is robust, and is scalable in the number of robots. We then describe the design of a real-world mobile robot-based pursuit evasion game. We validate our algorithms by experiments in a moderate-scale testbed in a challenging office environment. Overall, our work illustrates an innovative interplay between robotics and communication.