Obstacle detection based on a 2D large range sonar model

The current state-of-the-art in Autonomous Ground Vehicle (AGV) technology requires expensive, delicate laser range finders to apperceive the environmental impact of driving. The situation of too costly ladar represents a large barrier to adoption of AGV in the future, whereas provides an opportunity for close-to-market large range sonar sensor. In this paper, we propose an obstacle detection algorithm using adjacent periods´ echo data of the large range sonar sensor in the off-road environment. We first integrate vehicle odometry into the sonar sensor and succeed in changing one dimension (1D) distance information into two dimension (2D) signal, which provides a strong prior constraint to filter unstable noisy echoes. We use Hungarian algorithm to solve correspondence of data points to make sure they are reflected back by a mutual object. Matched dual points are used to extract the obstacle´s line feature represented in the manner of common tangent of the two intersecting arcs. Experiments in outdoor environment demonstrate validity of our algorithm.