A Robot Precision Positioning Method Based on Complementary Visual Servoing With a Mid-Joint Configured Camera

Hand-eye coordination is one of the important ways to enhance the flexibility of industrial robots. The mid-joint configured camera is an emerging configuration mode that combines the operational flexibility of the eye-in-hand mode with the imaging stability of the eye-to-hand mode. However, the mismatch between the camera and the robot’s degrees of freedom (DOF) prevents traditional visual servo methods from fully playing their guiding role. This article studies a vision-guided positioning method for a typical cooperative system with mismatched DOF between the hand and eye. First, the kinematic model and Jacobian matrix of the hand-eye system are established. The control difference caused by the mismatching of DOF is clarified. A depth estimation method is introduced that can calculate depth values without hand-eye parameters. On this basis, a complementary visual servo algorithm is developed. Independent controllers are designed to control the manipulator in different DOF, and algorithm fusion is carried out. The Lyapunov method is adopted to prove the system’s stability. An adaptive adjustment algorithm has been designed to accelerate system convergence and overcome the accuracy degradation caused by system friction. Experiments are carried out to verify the high positioning accuracy and good control performance of the proposed algorithm.