Adaptive Visual Servo of Soft Robot With Interaction Estimation and Compensation

Soft robots face significant control challenges due to the coupling effects of strain and external forces, particularly with external interactions that change their original model. This paper proposes a vision-based controller integrated with an adaptive algorithm to estimate and compensate for external contact disturbances in such environments. Specifically, the adaptive law can online estimate unknown camera parameters, eliminating the need for costly and environment-specific calibration procedures. In parallel, a contact disturbance estimation strategy is introduced to model and compensate for real-time interaction effects without the foreknowledge of the constitutive equation of the soft mechanism. The adaptive algorithm is seamlessly integrated into the adaptive image-based visual servo (IBVS) controller, allowing simultaneous calibration and contact compensation during task execution. We validated the algorithm on a tendon-driven, octoarticular soft robotic manipulator prototype. The experimental results demonstrated the algorithm’s ability to position the end-effector even under external interactions, with the adaptive parameters converging, thereby validating the effectiveness of the online estimation in assessing the impacts of interactions.