A novel control paradigm for collision-free trajectory tracking in tractor-trailer robots

This paper presents a novel control framework for achieving collision-free trajectory tracking in tractor-trailer mobile robots (TTMRs) within both static and dynamic environments. This study addresses the challenges posed by nonholonomic constraints and kinematic coupling inherent in TTMR systems. An inverse kinematic control strategy, augmented with pure integral controllers, is proposed to ensure precise trajectory tracking. The control framework is further enhanced using three obstacle avoidance approaches: two customized artificial potential field (APF) approaches and a novel path planning mode (PPM) for continuous-time trajectory adjustment. APF methods, applied for the first time to TTMR trajectory tracking, incorporate gravitational and repulsive forces to guide the robot away from obstacles, whereas PPM dynamically generates a semi-circular trajectory when the robot approaches an obstacle. Case studies validate the effectiveness of the proposed strategy in accurate trajectory tracking and safe obstacle avoidance. Comparative analyses highlight the superior performance of PPM in managing complex environments.