Simultaneous high transparency and robust stability-oriented Physical Human-Robot Interaction using an Interaction Intention Filter and a vibration observer

Abstract

Physical Human-Robot Interaction (pHRI) systems equipped with compliant admittance controllers typically utilize F/T sensors to capture the forces applied by the operator. However, the impedance force feedback generated by the robot’s motion and the impedance of the human hand can significantly distort the intentional forces. This distortion can lead to vibrations that compromise both interaction transparency and stability. To address this issue, we propose a variable admittance control strategy that incorporates an Interaction Intention Filter (IIF) and an Enhanced Time-Domain Vibration Observer (ETDVO). We first introduce the concept of the IIF, which is designed based on a frequency-domain analysis of force signals collected from real-world human–robot cooperation tasks. This filter effectively prevents unintended impedance force feedback from being transmitted to the admittance controller. Moreover, to ensure interaction stability across diverse environments, we propose a variable-width time window-based ETDVO for accurately computing the vibration index. By leveraging this index, we introduce a variable admittance control strategy based on exponential mapping, which enables rapid adjustment of the admittance parameters, effectively suppresses vibrations and enhances stability. Finally, the proposed strategy is validated through human–robot cooperative laser tracking experiments conducted on a 7-DoF manipulator. Statistical results from the experiments demonstrate that our approach not only improves interaction transparency but also significantly enhances overall stability. Compared to the stable high-gain admittance controller, the Task Time, Required Energy, and Mean Force are reduced by over 10%, 54%, 58%, respectively.