Task and Motion Planning for Mobile Tracking Robot in Automatic Inspection of Large-Scale Freeform Surface Parts

This article introduced a dual-robot measurement system with a mobile scanning robot (MSR) and a mobile tracking robot (MTR), and proposed a novel task and motion planning method for the MTR. This work aims to deal with two subproblems in the automatic inspection task for the MTR, i.e., the tracking station placement problem (TSPP) and the safe motion trajectory planning problem (SMTPP). First, we analyzed multiple task and motion constraints, including station transition constraints (STCs), tracking volume constraints (TVCs), safe region constraints (SRCs), and dynamical feasible constraints (DFCs). Second, STCs and TVCs are introduced to the TSPP, which is modeled as a set covering problem further. An effective partial-state sampling strategy is proposed to generate candidate stations toward the target object. Then, a novel image-based approximate convex decomposition algorithm (IACD) was presented to reconstruct a 2-D complex environment as a group of convex safe sub-regions. These sub-regions and boundary information make up the graph of convex set (GCS), which provides a powerful approach to guide the movement of the MTR. Finally, we formulated the SMTPP as an optimal boundary value problem (OBVP) with the SRCs and DFCs and proposed a GCS-based method named GCS-OBVP to generate a safe motion trajectory of the MTR. Extensive experiments are designed to demonstrate the effectiveness and superiority of the proposed methods.