Chen De
ABSTRACT
The core of robot visual servo is how to quickly and accurately recognize the image with the target features under the complex multi-constraint conditions. Mainly combines the characteristics of visual servo system for target detection, and based on the integrated network structure of target detection and feature extraction of YOLO training method, this paper proposes a method of matching the target position of the previous frame with the predicted position of the current frame obtained by Kalman filtering, which is used to locate the key point to judge whether there is a target in the predicted position. Five typical practical application examples are used to demonstrate the effectiveness of the proposed method in the detection efficiency as well as the success rate of image target features.
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Index Terms
- Accurate Spatial Positioning of Target Images in Visual Servo System under Multiple Constraints
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