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This paper introduces Model Predictive Contouring Control (MR-MPCC) for robotic manipulators to address path-tracking errors under moving reference frames, a critical issue in precision tasks like machining and surgery. Unlike conventional controllers that rely on fixed temporal correspondence, MR-MPCC employs a hierarchical approach with an upper-level MPCC optimizing path progress and penalizing errors, and a lower-level RMRC layer mapping Cartesian twists to joint velocities under constraints. Experiments on a UR5e platform demonstrate MR-MPCC's superior path-following performance and reduced deviations compared to PI and time-indexed MPC under moving-reference disturbances.
Robotic manipulators can now achieve sub-millimeter path accuracy even when their target trajectories are unpredictably moving, thanks to a novel predictive control strategy.
Maintaining small path-tracking errors under moving reference frames is essential for robotic manipulation tasks with tight execution tolerances, such as machining and surgical automation. Conventional time-indexed controllers, including tracking Model Predictive Control (MPC), rely on a fixed temporal correspondence with the reference trajectory and may therefore accumulate path-relative error under abrupt reference-frame motion or timing mismatch. This paper presents MR-MPCC, a Model Predictive Contouring Control (MPCC) framework for velocity-controlled robotic manipulators with 6-DoF end-effector pose regulation under Moving-Reference disturbances. A hierarchical control architecture is adopted, in which an upper-level MPCC optimizes path progress while penalizing contouring and orientation errors, and a constrained resolved motion rate control (RMRC) layer maps the commanded Cartesian twist to feasible joint velocities under joint-level and safety constraints. MR-MPCC is implemented in a ROS2--MuJoCo pipeline and validated on a UR5e platform under moving-reference disturbances, where the path frame is perturbed and tracked by electromagnetic sensors. Compared with PI control and time-indexed tracking MPC under matched disturbance, MR-MPCC achieves lower geometric path-following error and smaller deviations in the moving path frame, demonstrating improved path-following performance under reference-frame motion.