The Research Of Binocular Stereo Vision System For Lunar Rover

Lunar Rover is an intelligent mobile robot to explore complex terrain, which is the product of artificial intelligence, automation, mechanism, information technology, computer science and other high-tech technology. It is of great value in research and application, and is paid great attention to all over the world. Of all the Lunar Rover key technologies, the main task of the stereo vision system is to achieve onboard perception and fusion of the complex lunar terrain, by capturing images, matching feature points, producing depth map, recognizing obstacles and reconstructing 3D scene, in order to navigate and avoid obstacle automatically in unknown environment.Response and accuracy conflict with limited computational resource. There is no universal method to design a vision system. Usually, rough estimation of system performance can not maintain system balance. This paper proposes a methodology for the system configuration and design on the rover stereo vision system. The paper analyzes performance of the vision system and presents principles for designing a stereo vision system for planetary rover by fusing main performance of a stereo-based system and the maneuverability of lunar Rover. Performance parameters are optimized, by applying the principles to choose suitable configuration parameters.Camera calibration is essential for stereo vision. A plane-based on-line calibration method is investigated, to calibrate cameras accurately and effectively. Deformation produced by short-focal and wide-angle lens should be undistorted. The searching space in stereo match is reduced from two dimensions to one by rectification. A compact rectification method is studied. By applying the perspective matrix, the stereo image pair can be rectified.Matching is the core of stereo vision. Stereo matching can be divided into local (window-based) algorithms and global algorithms, which both have been investigated in this paper. For rover application, speed and robustness is considered, as the final system is intended to work in a dynamic environment under real-time condition. The topics of our research include correspondence calculating and window size in area-base algorithm, and the evaluation of these methods qualitatively and quantitatively. Preprocessing and post-processing are important in order to improve robustness and accuracy, which including LOG filter, refinement, left-right-line-of-sight consistency check, blob filter, and median filter.The results of stereo matching are expressed by 3D reconstruction. This chapter presents a method to calculate and map the 3D points of objects, using the disparity map from stereo matching, and the camera parameters from camera calibration. In future research, surf map and 3D visualization will be studied for real-time navigation.