Line-of-Sight-Constrained Safe Tracking Control with a RISE-Based Disturbance Observer
摘要
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 avoiding collisions between the chaser vehicle and obstacles. A novel real-time occlusion detection function is developed, and motion constraints are systematically integrated via a hybrid framework combining the artificial potential field (APF) method with an observer-based control strategy. Furthermore, we propose a disturbance observer based on the robust integral of the sign of the error (RISE) method to achieve rapid and accurate estimation of unknown environmental disturbances and nonlinear terms. Finally, the effectiveness of the proposed method was verified via simulation in a simplified physical scenario.