Parallel multi-speed Pursuit-Evasion Game algorithms

Abstract

Pursuit-Evasion Game (PEG) consists of a team of pursuers trying to capture one or more evaders. PEG is important due to its application in surveillance, search and rescue, disaster robotics, boundary defense and so on. In general, PEG requires exponential time to compute the minimum number of pursuers to capture an evader. To mitigate this, we have designed a parallel optimal algorithm to minimize the capture time in PEG. Given a discrete topology, this algorithm also outputs the minimum number of pursuers to capture an evader. We also extended parallel algorithm to consider other versions as: heterogeneous/multi-speed players; the pac-dot technique to increase evader lifetime in a game; and a pruning strategy for pac-dot technique to increase the scalability. The parallel algorithm performance was evaluated by speedup metric and this algorithm and its extensions were simulated and evaluated on many different topologies to validate the viability of our algorithms by discussing and evaluating a set of simulation results. The parallel algorithm enables us to scale up to 8.13 times with 8 cores compared to state-of-the-art. Considering the complexity of the state space growing up, pruning technique to pac-dot algorithm minimizes the state space and generated transition, and can handle a large number of states (≈830 M) and transitions (≈11 G) generated. In general, our algorithms increase the scalability and make it feasible to compute the PEG optimal strategy for more realistic cases.