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

Area of Science:

• Robotics
• Control Systems Engineering
• Mechanical Engineering

Background:

• Robots operating in contact with environments require precise force and position control.
• Existing control methods may struggle with dynamic uncertainties and environmental interactions.

Purpose of the Study:

• To develop an advanced control scheme for enhancing robot force/position control performance during environmental contact.
• To integrate dynamic parameter identification, trajectory scaling, and adaptive computed-torque control.

Main Methods:

• Utilized the Newton-Euler method to derive the robot's dynamic equation and regression matrix, reducing model order.
• Employed the least-square method for initial dynamic parameter identification.
• Implemented adaptive parameter estimation for torque calculation and trajectory scaling for contact force management.

Main Results:

• The proposed control scheme effectively integrates dynamic parameter identification and adaptive control.
• Simulations demonstrated the efficacy of the combined approach in improving robot control performance.
• Trajectory scaling proved effective in managing contact forces.

Conclusions:

• The proposed control scheme offers a significant improvement in robot force/position control during environmental interactions.
• The synergy between dynamic parameter identification, adaptive estimation, and trajectory scaling is crucial for enhanced performance.
• This approach provides a robust solution for complex robotic tasks involving physical contact.