A Smooth Planning Method for Multi-Robot Transportation System With Decoupled Path and Orientation Planning

Abstract Multi-Robot Systems (MRS) are gaining popularity in various fields due to their adaptability and scalability, particularly in transporting large items. Integrating motion constraints presents a challenge for these systems, as these constraints affect the robots’ dynamics, complicating planning and control. Traditional methods that use general motion modes and constraints simplify planning but can limit maneuverability. Moreover, conventional collision detection often simplifies interactions too much, hindering the system’s ability to adjust its orientation to navigate around obstacles, a significant issue with slender objects. This paper introduces a novel planning methodology that strategically decouples path planning from orientation planning. This decoupled approach facilitates the generation of smooth trajectories that inherently accommodate static obstacle avoidance, ensuring seamless navigation throughout the transportation task. Theoretical analysis confirms the method’s efficacy in achieving smooth motion, while empirical evidence demonstrates its superiority in reducing overall travel distances when compared to existing algorithms. This dual-phase planning strategy not only enhances the operational efficiency of MRS in complex environments but also extends the potential applications of robotic transportation systems by mitigating the limitations imposed by traditional planning constraints.