Target-tools recognition method based on an image feature library for space station cabin service robots

This paper presents a method to improve the speed and accuracy rate for space robot visual target recognition based on illumination and affine invariant feature extraction. The method takes illumination changes, strong nonlinear light due to refraction and reflection, target affine transformation and occlusion into consideration, all of which occur on the cabin target surface and affect the target recognition accuracy seriously. In this paper, a method is proposed to capture a same target at multi-viewpoints to establish feature library for high recognition accuracy and speed at any viewpoint. By using an analysis of the light intensity and gray level transformation, we obtain the corrected image which reduce the influence of illumination change. Then the affine moment invariants features of the correction images at multi-viewpoints were extracted and the average feature datum were stored in the library. To verify the validity of the method, a robot vision system provided images, followed by image preprocessing, dynamic local threshold segmentation and feature extraction. These methods were verified on a target recognition system of space robot built for this research. The experimental results showed that the methods were feasible and effective.