Path Planning Algorithm Reserch In Non-structural Environment For Mobile Robot

Navigation is the most important and basic problem for mobile robot. It is necessary for mobile robot to have the ability of sensing extern environment and moving autonomously and safely in environment with obstacles. Thus navigation includes two basic tasks: goal-oriented movement and obstacle detection. In this dissertation we present our research on visual homing and obstacle detection.The basic idea of visual homing comes from insect navigation, visual homing calculates the direction from current location to goal location by comparing the images viewed from the two locations. Compared to the traditional navigation methods based on accurate geometric map and self-localization, the storage and complexity of visual homing are greatly reduced, thus visual homing has become an attractive strategy, however, the goal image is stored in advance, the acquisition times of current image and goal image are different; and the distance from current location to goal location are maybe long, the projection of landmarks in two images are different in light intensity,scales,rotation, so how to maintain the efficiency and robustness of visual homing algorithm is still a challenge problem.In this dissertation a test platform for visual homing algorithms is designed, the major visual homing algorithm are tested and compared detailedly,and the links between warping algorithm and RMS algorithm are discussed, which inspires a new method based on random searching, this algorithm can significantly improve the Computational efficiency with keeping the robustness in case of the original warping algorithm. Compared with the original warping algorithm, the computational cost of ours is about one order of magnitude lower.In order to alleviate the damage to the performance of visual homing algorithms caused by illumination changes, a new filter is proposed, which combines the ideas of feature extraction and origin image comparison, turn the coordinates of all edges in image plane into a new image, and calculate the homing vector from difference of filtered Images,which uses feature extraction to alleviate the impact of illumination changes, and avoid the complicated and error-prone process of feature matching. Experiments show good performance of this algorithm with dramatic illumination changesIn order to solve real-time obstacle detection problem in unstructured environment, a stereo vision algorithm based on corner features is presented. A fast two-step corner detection and confirmation algorithm is realized by using the Bresenham Circle template and Moravec filter, sparse filter and corner polar constraint are used for corner matching to reduce computing time. Considering that the obstacle definition by height can not be applied in unstructured environments, a new obstacle definition based on the space relationship of the corners is proposed, and the algorithm solve the problem of errors of corner matching. The algorithm is efficient, which do not need prior knowledge of the environment, and can be applied in unstructured environments. Experiments prove the effectiveness of the algorithm...