Reference Trajectory Reshaping Optimization and Control of Robotic Exoskeletons for Human-Robot Co-Manipulation

Area of Science:

• Robotics
• Control Systems
• Human-Robot Interaction

Background:

• Human-robot co-manipulation relies on interaction forces for action coordination.
• Existing methods often require continuous human guidance for trajectory adjustments.

Purpose of the Study:

• To present an optimization approach for reshaping physical interactive trajectories in robotic exoskeleton co-manipulation.
• To enable humans to adjust robot trajectories via impedance control and force feedback.

Main Methods:

• Formulation of a quadratically constrained programming problem solved by neural dynamics optimization.
• Development of an adaptive neural-network controller using a barrier Lyapunov function (BLF).
• Integration of impedance control for human adjustment of desired and actual robot trajectories.

Main Results:

• The proposed method reshapes desired trajectories during physical human-robot interaction (pHRI) based on force feedback.
• Achieved smooth, minimal-energy trajectories mimicking natural human movement.
• The adaptive controller effectively handled uncertain dynamics and joint space constraints.

Conclusions:

• The developed optimization and control scheme enables effective human-robot co-manipulation using robotic exoskeletons.
• Experimental validation on an exoskeleton robot confirms the controller's efficacy in co-manipulation tasks.