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.