Image-Based Visual Servoing With Collision-Free Path Planning for Monocular Vision-Guided Assembly

The demand for robotic assembly technology is increasing with the advancement of Industry 4.0. Image-based visual servoing (IBVS) is highly anticipated for robotic assembly since it enhances robotic systems' flexibility and accuracy. However, since IBVS drives the robot by controlling image features in image space without 3-D position information, the Cartesian spatial path cannot be pre-planned, inevitably causing collision problems during assembly. This article proposes a novel collision-free spatial path planning method for IBVS. Through perspective transformation, it is rigorously proved that there exists a unique path node (PN) on the line connecting the camera and target, enabling zero orientation error for the part here. By defining a virtual camera, image path midpoints corresponding to this Cartesian PN are generated as intermediate goals for visual servo control. Hence, a two-stage assembly path involving leveling followed by docking is devised, with orientation adjustment completed already in the leveling path to avoid assembly collisions during docking. The translational docking path is innovatively determined by the camera position, making it flexible and predictable. Then, a controller is presented to track planned paths. By deriving a depth-independent image Jacobian matrix, depth error interference on the docking path is eliminated. The closed-loop system's dynamic stability is rigorously proved with Lyapunov methods. The simulation and experimental results confirm the significant regulation and improvement of spatial paths for IBVS, with 100% collision avoidance. Satellite prototype assembly results further illustrate the feasibility of using the proposed method in practical scenarios.