Optimal docking path planning and tracking method for reconfigurable unmanned shuttle with a six-DoF parallel docking mechanism

Reconfigurable transport vehicles, capable of dynamically altering their configurations through the assembly and disassembly of reconfiguration units (RUs), can adapt to diverse environmental conditions and evolving task requirements. This paper introduces a novel reconfigurable unmanned shuttle (RUS) that achieves vehicle reconfiguration via a six-DoF parallel docking mechanism (PDM), thereby enhancing transport capacity. To enable mechanical docking using the PDM, this paper proposes a four-phase autonomous docking process (4P-ADP) framework, consisting of the far-end approach phase (FEAP), near-end capture phase (NECP), collaborative docking phase (CDP), and host establishment phase (HEP). Focusing on the NECP, the most critical phase, an optimal docking path planning and tracking (ODPPT) method is proposed. First, a kinematic model is used to compute the pose envelope of the docking mechanism (PEDM). From this, a set of endpoint samples is generated to form a path cluster. The optimal path is then selected and tracked using linear time-varying model predictive control (LTV–MPC). Finally, the proposed methods are validated through 27 experimental trials on the RUS test platform, with all path tracking endpoints satisfying the PEDM, thereby confirming the effectiveness of the ODPPT method.