Human-Robot Cooperative Heavy Payload Manipulation based on Whole-Body Model Predictive Control

Abstract

Human-robot collaborative manipulation with mobile, multiple manipulators is crucial for expanding robotic applications, requiring precise handling of coupled force-position constraints between partners. Current systems, however, exhibit end-effector oscillations and instability during dynamic interactions. To overcome these limitations, this work develops a collaborative framework integrating a collaborative controller and a whole-body controller. The collaborative controller employs the object’s center-of-mass dynamics model with real-time contact forces and motion states to predict trajectories while coordinating with an attitude stabilization controller to adjust the desired end-effector poses. The whole-body controller utilizes model predictive control to generate coordinated motions that strictly follow pose commands from the collaborative controller, ensuring stable transportation. Simulation and physical experiments validate the proposed framework’s effectiveness in real-world scenarios.