Frequency-division based hybrid force/position control of robotic arms manipulating in uncertain environments

This paper aims to propose a hybrid force/position control algorithm based on the stiffness estimation of the unknown environment. A frequency-division control scheme is developed to improve the applicability and reliability of the robot in welding, polishing and assembly.

The stiffness estimation algorithm with time-varying forgetting factors is used to improve the speed and accuracy of the unknown environmental estimation. The sensor force control and robot position control are adopted in different frequencies to improve system stability and communication compatibility. In the low frequency of sensor force control, the Kalman state observer is used to estimate the robot’s joints information, whereas the polynomial interpolation is used to ensure the smoothness of the high frequency of robot position control.

Accurate force control, as well as the system stability, is attained by using this control algorithm.

The entire algorithm is applied to a six-degrees-of-freedom industrial robot, and experiments are performed to confirm its applicability.

The frequency-division control strategy guarantees the control stability and improves the smoothness of the robot movement.