Dynamic parameter identification and adaptive control with trajectory scaling for robot-environment interaction

To improve the force/position control performance of robots in contact with the environment, this paper proposes a control scheme comprising dynamic parameter identification, trajectory scaling, and computed-torque control based on adaptive parameter estimation. Based on the Newton-Euler method, the dynamic equation and its regression matrix is obtained, which is helpful to reduce the order of the model. Subsequently, the least-square method is implemented to calculate the values of the basic parameters of the dynamics. The identified dynamic parameters are used as initial values in the adaptive parameter estimation to obtain the torque, and trajectory scaling is applied to control the contact force between the robot and the environment. Finally, the dynamic parameter identification method and control algorithm are verified by conducting a simulation. The results show that the comprehensive application can help improve the control performance of robots.

Automated summary

This paper proposes a control scheme to improve the force/position control performance of robots in contact with the environment. The scheme includes dynamic parameter identification, trajectory scaling, and computed-torque control based on adaptive parameter estimation. The dynamic equation and its regression matrix are obtained using the Newton-Euler method, and the least-square method is used to calculate the values of the dynamic parameters. The identified parameters are then used in the adaptive parameter estimation to obtain the torque, and trajectory scaling is applied to control the contact force. Simulation results show that the comprehensive application of these methods can improve the control performance of robots.