A Decentralized Approach to Pursuer-Evader Games with Multiple Superior Evaders in Noisy Environments

Abstract

Few pursuer-evader (PE) game algorithms allow for real-time applications for (1) multi-pursuer-multi-evader situations, (2) noisy environments, and (3) evaders with superior control resources such as higher speeds. This paper introduces a real-time decentralized approach for such games. A sufficient condition for capturing a superior evader is proposed. A particle filter is applied to the complex non-Gaussian multi-model noise. Simulations confirm the efficiency of this approach.