Adaptive Control of Robots Using Visual Feedback

Abstract Vision based robot control systems provide capabilities for modifying positions to accommodate uncertainty in the task environment. Vision based robot control research has focused on vision processing issues, while control system design has been limited to ad hoc strategies In this paper, we formalize an analytical approach to the design of dynamic robot visual servo control systems An image-based structure represents a new approach to visual servo control which uses local image features as feedback control signals image-based control presents formidable engineering problems for controller design, including complex dynamics, kinematics, and feature transformations, as well as unknown parameters, and measurement noise and delays A model reference adaptive Controller (MRAC) is designed to satisfy these requirements Simulation studies are described which indicate the feasibility and expected performance of this approach for systems with 1, 2. and 3 degrees of freedom.