Safe environment contact, and high-performance motion control are typically conflicting design goals. Admittance control can improve safety and stability in contact with a stiff environment but remains challenging on industrial robots. Typically, high-performance motion control is achieved by low-admittance systems, which can give high transient forces or instability in contact with high-stiffness environments. This article proposes a linear admittance control framework from which a multifunction observer (MOB)-based control scheme that succeeds in directly improving the motion control accuracy by suppressing disturbances, while achieving better loop shaping in the outer-loop admittance control is designed. By using the task space force and position measurement of the robot, combined with linearized position-controlled robot and payload models to design the MOB, the outer-loop controller can render improved interactive dynamics. In addition, a methodology to design the proposed MOB based on the reduced-order model is developed. Furthermore, the bounded-magnitude frequency-domain uncertainty in the linear model is identified at a variety of robot poses. Theoretical evaluations and experiments verify the effectiveness of the proposed MOB-based control method, in contact with a very stiff environment and with a 7-kg payload.
Research Interests
Research on Human-friendly motion control; Development of human assistance;rehabilitation system; Design of robotic system based on human musculoskeletal system; Analysis of human walking dynamics and its application to robotics; 친인간적인 운동제어 설계연구; 인간 보조;재활 시스템의 설계 및 개발연구; 인간 근골격계에 기초한 로봇기구 개발연구; 보행운동 분석과 모델 및 로봇기구에의 응용