Energy-based variable admittance control to deduce intuitive human intention and mitigate force impact for physical human–robot–environment interaction

Abstract

Purpose This study aims to tackle the primary challenges in human–robot–environment interaction (HREI) within unknown environments. The key issues include recognizing human motion intention and managing force impacts during transitions from free space to constrained space. Addressing these challenges is critical for improving compliance, enhancing force control accuracy, and ensuring the safety and performance of HREI systems. Design/methodology/approach First, the energy equation of the second-order system is presented, and variable admittance control laws are designed for both free space and constraint space based on the energy equation. Then, a smooth switching method based on selection matrix is developed. Subsequently, the admittance-based overall control system is discussed. Finally, comparative simulations and experiments are conducted to verify the efficacy of the variable admittance control method using the 7-degree-of-freedom (7-DOF) manipulator Panda arm. Findings The simulation and experiment results demonstrate that the proposed variable admittance control method outperforms the traditional method in terms of force overshoot and accuracy. Research limitations/implications This study does not account for the shape of unknown surfaces in the formulation of the variable admittance control law. Originality/value This paper proposes an energy-based variable admittance control method that uses energy considerations and uses a smooth switching technique to deduce human intentions and mitigate the effects of impact force.