Decentralized Pursuit of an Evader With Probabilistic Collision-Free for Differential Drive Robots

This article addresses the pursuit-evasion problem among differential drive robots in an obstacle environment with perception uncertainty. To calculate probabilistic collision-free trajectories during the pursuit process, this article introduces the chance-constraint pursuit Voronoi cell (CCPVC), which consists of separation hyperplanes between robots and separation hyperplanes between robots and obstacles. The optimization problems are formulated to compute the separation hyperplanes, and the solution methods are provided. By incorporating two buffer terms, CCPVC exhibits favorable probabilistic collision avoidance properties. Furthermore, a nearest point finding algorithm specifically designed for pursuit scenarios, along with a distributed pursuit control policy tailored for differential drive robots are proposed based on CCPVC. Rigorous proofs for the probabilistic collision avoidance guarantees of CCPVC and the control law during the pursuit process are provided, respectively. Finally, the effectiveness of the proposed methods is validated through simulations and experiments.