This paper aims to propose an adaptive control framework for mobile manipulators to seamlessly balance autonomous task execution with human intervention during physical human–robot interaction. The objective is to coordinate a nonholonomic mobile base and a redundant manipulator in response to force-amplitude-based human guidance.
The approach integrates state-dependent dynamical systems for autonomous task encoding with a variable admittance control scheme for reactive interactions. To address the distinct kinematic constraints of the mobile platform and the end-effector, a configuration-dependent damping adjustment method and an external-force-based velocity arbitration mechanism are developed. These methods dynamically modulate the reference velocity generated by the dynamical system and the force-induced admittance velocity, enabling adaptive velocity fusion based on real-time force signals.
Simulation and real-robot experiments using an xArm7 manipulator mounted on a SMART mobile platform demonstrate the efficacy of the proposed framework. The results indicate that the mobile manipulator exhibits bounded and responsive behavior under the tested conditions, effectively reconfiguring to accommodate human guidance while maintaining task velocity.
This work treats the mobile manipulator as a unified redundant system rather than two separate entities. By combining dynamical-system-based trajectory generation with a novel velocity arbitration law, the proposed method realizes real-time, force-mediated coordination of the entire system. This offers a possible solution for high-degree-of-freedom mobile manipulators performing collaborative tasks in industrial environments.
