A stability observer for human-robot and environment-robot interaction with variable admittance control

Abstract

Abstract When interacting with the environment or human, the robot is prone to unstable oscillation if the stiffness of the environment or human increases suddenly. In human-robot interaction, traditional frequency-based stability observers are easily impacted by the high-frequency signal noises or filter phase error, which may cause misdiagnosis. In environment-robot interaction, adaptive algorithm keeps the contact force stable by identifying the environmental stiffness, but the varying environmental stiffness may cause the failure of the adaptive algorithm. Therefore, this paper proposes an improved observer using the ratio of the force standard deviation to the maximum allowable force to eliminate the effect of high-frequency noises and alleviate the misdiagnosis. Moreover, we use the designed stability observer to monitor the interaction forces in real time and ensure the stable operation of the adaptive algorithm by updating the initial environmental stiffness. And we design a variable admittance control algorithm based on the stability observer to ensure the stability of the interaction. The final experimental results show that the stability observer and the corresponding control algorithm designed in this paper have better accuracy and robustness in human-robot and environment-robot interaction.