Improved Uncalibrated Visual Servo Strategy for Hyper-Redundant Manipulators in On-Orbit Automatic Assembly

Abstract

Aiming at on-orbit automatic assembly, an improved uncalibrated visual servo strategy for hyper-redundant manipulators based on projective homography is proposed. This strategy uses an improved homography-based task function with lower dimensions while maintaining its robustness to image defects and noise. This not only improves the real-time performance but also makes the joint space of hyper-redundant manipulator redundant to the homography-based task function. Considering that the kinematic parameters of the manipulator are easily changed in a space environment, the total Jacobian between the task function and manipulator joints is estimated online and used to construct a controller to directly control the manipulator joints without a kinematics model. When designing the controller, the above-mentioned redundancy is exploited to solve the problem of the over-limiting of the joint angles of the manipulator. The KF-SVSF method, which combines the optimality of the Kalman filter (KF) and the robustness of the smooth variable structure filter (SVSF), is introduced to the field of uncalibrated visual servos for the first time to perform the online estimation of the total Jacobian. In addition, the singular value filtering (SVF) method is adopted for the first time to avoid the interference caused by the unstable condition number of the estimated total Jacobian. Finally, simulations and experiments verify the superiority of this strategy in terms of its real-time performance and precision.