An Uncertain Knowledge Based Real Time Road Scene Understanding Algorithm
基于不确定性知识的实时道路场景理解

Because the environment of outdoor robot is very complicated, the visual navigation should be intelligent and robust enough. In order to improve the performance of computer vision navigation, a real time road scene understanding algorithm based on uncertain knowledge is presented in this paper. In this algorithm uncertain knowledge reasoning is applied to fuse the various image information and application knowledge, which make the algorithm can recognize the road scene robustly, even with the noise such as strong shadow and water on the road. Color information is used to obtain a coarse road region at first. And then image edge information is used to provide the precise road edge, which can meet the accuracy need of the visual navigation task. And this algorithm is well designed for real time application, which ensures that the visual navigation can make decisions in time. This algorithm has been applied on a real robot which has been tested in the real road environment for half a year. The experiment results are satisfying.