Admittance control can improve robot performance and robustness in interactive tasks, but is still limited by stability when implemented on low-admittance hardware, such as position-controlled industrial robots. This limits applications which require the payload, reach, or positioning accuracy. While the idealized reference admittance behavior would be stable with any passive environment (provided positive damping), real robots can be unstable, especially with high-stiffness environments. Thus, instability comes from deviation from the ideal reference model, due to either inner-loop bandwidth, time-delay, or other model error. To improve accuracy of rendered dynamics and reduce contact forces, a novel integrated disturbance observer-based admittance control method which is implemented on a position/velocity-controlled industrial robot in task space is proposed. The multisensor information, i.e., the velocity command, measured output velocity, inverse model of the velocity controlled system, and the force/torque (F/T) sensor measurement are integrated to estimate and cancel the disturbances, outside the position/velocity control loop, all in task space. Theoretical analyses and experiments on the actual robot show that the proposed method is able to improve accuracy and reduce contact forces even at higher admittance.

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 paper proposes a linear admittance control framework from which a Multi-function 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 developed. By using the task space force and position measurement of the robot, combined with linearized 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. Theoretical evaluations and experiments verify the effectiveness of the proposed MOB-based control method, in contact with an environment stiffness and with a 7~kg payload.