Hybrid force/position control of industrial robotic manipulator based on Kalman filter

Abstract

This paper proposes a hybrid force/position controller for industrial robotic manipulator based on Kalman filter. Firstly, the mathematical model of real contact force is built to estimate the actual contact force by applying Kalman filter using a force derivative to achieve the system state description. The estimated actual contact force is used to control the end-effector force as well as estimating the stiffness of environment. To refine the environment stiffness estimation the Recursive Least Square (RLS) technique has been employed. Owing to the fact that the general industrial manipulator only provides the position control mode, the position-based hybrid force/position control architecture is designed and realized by using the position tracking mode of the motion control card. The main advantages of the implemented controller is simplicity, computational efficiency and robustness to unknown environment, it is convenience for the general industrial manipulators. Besides, it lends itself for industrial manipulators in order to achieve compliant behavior and perform complex tasks. The proposed control structure is successfully validated by practical experiments. The results show that the controller has a satisfactory performance in term of force control and trajectory tracking and robustness to force/torque sensor measurement interferences.