Prescribed-Time Safe Pursuit Control with Dynamic Obstacle and Occlusion Avoidance

Abstract

Performing target tracking and surveillance in dynamic obstacle environments requires maintaining continuous visual focus on the target while ensuring collision avoidance. This paper presents a safety-critical tracking control method that ensures dynamic obstacles remain outside the camera’s line of sight while simultaneously avoiding collisions between the chaser vehicle and obstacles. A novel real-time occlusion detection function is developed, and motion constraints are systematically integrated using a hybrid framework combining the artificial potential field (APF) method with an observer-based control strategy. To address temporal-sensitive tasks, a prescribed time controller (PTC) based on time-scale transformation technique has been proposed. Furthermore, a prescribed time linear extended state observer (PTESO) is proposed, featuring a simplified structure to enable rapid and accurate estimation of unknown environmental disturbances and non-linear terms. Finally, the effectiveness of the proposed method was verified via simulation in a simplified physical scenario.