Kinematics-based incremental visual servo for robotic capture of non-cooperative target

Abstract

This paper presents the concept and experimental results of a kinematics-based incremental visual servo control approach for robotic manipulators with an eye-in-hand configuration to capture non-cooperative targets autonomously. The vision system is adopted to estimate the real time position and motion of the target by an integrated algorithm of photogrammetry and the adaptive extended Kalman filter. The unknown intercept point of trajectories of the target and the end-effector is dynamically predicted and updated based on the target estimates and is served as the desired position of the end-effector. An incremental control law is developed for the robotic manipulator to avoid multiple solutions of the robotic inverse kinematics. The end-effector is then controlled by the proposed control scheme to approach the dynamically estimated interception point directly. The proposed approach is validated experimentally by custom built robotic manipulator. To demonstrate the effectiveness of the proposed approach, uncertainties, such as, joint flexibility of the robotic manipulator, backlash of actuators, nonlinear target motion, camera mounting bias, etc., have not been considered in the control law. The experimental results show that the predicted minimum tracking time is reduced asymptotically as the end-effector approaches the target, which demonstrate the proposed control scheme is effective and reliable. The advantages of the proposed control approach are: it does not require a robotic dynamic model that most of the existing robotic control based on; it avoids the multiple solution problem in the inverse kinematics; it is insensitive to system uncertainties; and it is much easier for engineering implementation.