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

When the robot interacts with the environment or people, if the stiffness of the environment or people suddenly increases, the robot is prone to instability. Traditional solutions, such as the stability observer based on frequency, are easily affected by high-frequency signal noise or filter phase error, resulting in misdiagnosis. In addition, the adaptive algorithm keeps the contact force stable in the environment-robot interaction by identifying the environmental stiffness. Still, the change in the environmental stiffness is too significant, which may lead to the failure of the adaptive algorithm. Therefore, this paper proposes an improved observer stabilization method, using the ratio of the standard deviation of force to the maximum allowable force to eliminate the influence of high-frequency noise and reduce misdiagnosis. In addition, the designed stability observer can monitor the interaction between the robot and the environment in real-time and ensure the stable operation of the adaptive algorithm by updating the initial environment stiffness. Finally, some comparative experiments are carried out. The results show that the proposed method has good accuracy and robustness in human-robot and environment-robot interaction.