Road Image Recognition Based on ATN for Outdoor Mobile Robot

Abstract

Road image recognition is a key technique for vision navigation of outdoor mobile robot. Because vision navigation of outdoor mobile robot requires good robustness and rigid time limitation for real time autonomous driving, in order to satisfy the request of good robustness and rigid time limitation, in this paper, we applied successfully Augmented Transition Networks (ATN), which is a kind of method used for sentence parsing in the artificial intelligence field, to the road image recognition of outdoor mobile robot, and proposed a road image interpretation algorithm based on the ATN. The characteristic of the ATN is, aiming at the different road condition, the algorithm can make up of different ATN, but all the ATN are constructed by the uniform construction rules. Therefore, the construction of the ATN is very flexible in application, and the essence of the ATN is coherent yet. The algorithm has good robustness and real time performance, and has been verified by the experiment that it can meet the needs for high speed autonomous vision navigation of outdoor mobile robot.