Manipulator-Effort-Aware MPC for Body Motion Coordination of an Underwater Walking Robot under Ocean Current Disturbances

Abstract

This paper proposes a manipulator-effort-aware model predictive control (MPC) framework for coordinating body motion of a multi-legged underwater walking robot during moored mine clearance under ocean-current disturbances. The method treats the norm of manipulator joint torques as an effort-related input and uses it in an upper-layer MPC to adapt the robot’s body approach motion and posture, while lower-level whole-body control and impedance control handle body stabilization and rope grasping. Simulation studies in a ROS1 Noetic–Gazebo environment with a UUV-Simulator-based model show that, under increasing unidirectional current, conventional decoupled controllers cause manipulator torques to grow and approach saturation, whereas the proposed framework keeps torques within safe limits by generating adaptive body-motion compensation. These results indicate improved mechanical stability and reduced manipulator burden during rope-grasping interactions, though validation is currently limited to a simplified unidirectional flow without full locomotion and is sensitive to model accuracy, motivating future experiments with more complex currents, dynamic walking scenarios, and refined hydrodynamic modeling.