Adaptive Image-Space Regulation for Robotic Systems

Abstract

This brief investigates the image-space regulation problem for visually servoed robotic systems by considering the uncertainties in the camera model and the manipulator kinematics and dynamics. By exploiting the depth-related passivity of the overall system kinematics, we first propose an adaptive dynamic controller that avoids the image-space velocity measurement by introducing a filter. In addition, we further show how to utilize the passivity property to design an adaptive kinematic control scheme, which simplifies the controller structure of the visually servoed robotic systems with the assumption that the low-level control loop can guarantee the square-integrability and boundedness of the joint velocity tracking error. We prove that both the proposed adaptive controllers can ensure the asymptotic convergence of the image-space position error. The results from a numerical simulation and extensive experimental studies illustrate the performance of the proposed adaptive image-space regulation control schemes.