In the ultra-close approaching phase of tethered space robot, a highly stable self-attitude control is essential. However, due to the field of view limitation of cameras, typical point features are difficult to extract, where commonly adopted position-based visual servoing cannot be valid anymore. To provide robot’s relative position and attitude with the target, we propose a monocular visual servoing control method using only the edge lines of satellite brackets. Firstly, real time detection of edge lines is achieved based on image gradient and region growing. Then, we build an edge line based model to estimate the relative position and attitude between the robot and the target. Finally, we design a visual servoing controller combined with PD controller. Experimental results demonstrate that our algorithm can extract edge lines stably and adjust the robot’s attitude to satisfy the grasping requirements.
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