Research On The Mobile Robot Vision-Based Navigation System

Vision-based navigation technology is a new hot spot in the area of mobile robot research. Researching on the AGV technology, Intelligent Vehicle and National defense technology have acquired breakthrough with the Vision-based navigation technology be in-depth studying. Because the images collected by the vision system can describe roundly the environment, and carry a tremendous amount of information about the scene, it becomes a Development Trend for intellectual control of the mobile robot. According to the controlling requirements on the movement of the mobile robot, this article focus on the recognition of target objects by the methods of Image preprocessing,Image Segmentation,matching for feature area.The analysis of movement model provides theoretical proof for the movement control of the mobile robot. On the consideration of distortion of CCD model in images collection, the Tsai two-step method is accepted to calibrate the internal and external parameters, and test the validity of above prediction with experiment. The result indicates that the calibration could meet for the calibration of the CCD Video Camera.Because of the environmental influences, the collected images have noise and distortion, which must be preprocessed with the gray level transformation,histogram handling and airspace filtering before the image segmentation and matching for feature area to increase the efficiency of image processing. Then by the comparison of the outcome and efficiency of comparison the image segmentation process, the Sobel operator is chosen to do the edge detection on images.In the target recognition, when processing the image segmentation on colors, the auto-threshold method is adopted and the maximum area method is practiced in the selection of the initial threshold, and the max ratio of class among variance and class internal variance is applied to carry through the initial segmentation. In the image modification the methods of image expansion Image Expansion and Image Thinning is used in order to ease the obtain of the edge information of the target. The method of matching for feature area by color techniques is proposed and practiced in the movement testing and control system on Mobile Robot. The system could achieve the recognition of target, though computing the absolute deviation of RGB from Pixel-point in the image to target template.With the utilization of the Visual C++ and image processing technology two systems, movement testing on mobile robot and vision-based navigation are established and Motion Simulation and control are realized. The experiment on the vision-based navigation of mobile robot indicates the prediction and methods proposed in the article is feasible.