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Dual-arm Object Transportation via Model Predictive Control and External Disturbance Estimation

This paper addresses the problem of transporting a rigid box filled with unknown objects with a dual-arm robotic system. Enforcing non-sliding contact behavior, which guarantees the transportation of the box despite the unknown load's action, is the main difficulty in this setting. To solve this problem, we propose a high-level model-predictive controller, which uses a nonlinear extended state observer to estimate the external disturbance, and determine the wrench required to the box for tracking a trajectory. A quadratic program transforms the calculated wrench into optimal desired contact forces on the two end-effectors. Finally, a low-level admittance control framework with an inner velocity loop is established to indirectly control the actual contact forces. We verify the effectiveness of the proposed control method with experiments carried out on a real dual-arm robotic system.