A sampling-based algorithm for multi-robot visibility-based pursuit-evasion

We introduce a probabilistically complete algorithm for solving a visibility-based pursuit-evasion problem in two-dimensional polygonal environments with multiple pursuers. The inputs for our algorithm are an environment and the initial positions of the pursuers. The output is a joint strategy for the pursuers that guarantees that the evader has been captured. We create a Sample-Generated Pursuit-Evasion Graph (SG-PEG) that utilizes an abstract sample generator to search the pursuers' joint configuration space for a pursuer solution strategy that captures the evaders. We implemented our algorithm in simulation and provide results.