Whole-Body Impedance Control for Mobile Manipulators with Online Uncertainty Compensation

This paper presents a novel whole-body impedance controller for mobile manipulators to enable safe interaction with uncertain environments without the need for force information. The proposed controller employs adaptive radial basis function neural networks to compensate for dynamic uncertainties online. The redundancy of mobile manipulators is managed to perform subtasks alongside tracking control without compromising overall performance. Stability analysis guarantees uniform ultimate boundedness of tracking errors during interaction and ensures asymptotic convergence to zero in free motion. Numerical simulations validate the effectiveness of the proposed method, including the evaluation of subtask performance.