LAUSR

Terrain traversability analysis is a challenging problem for mobile robots to adapt to complex environments, including the detection of cluttered obstacles, potholes, or even slopes. With the accurate distance information, using distance sensors such as three-dimensional light detection and ranging (LiDAR) for terrain description becomes a preferred choice. In this article, a terrain description method for traversability analysis based on elevation grid map is presented. After the elevation grid map is generated, the ground is segmented with the aid of a height difference kernel and the non-ground grids in the map are then clustered. The terrain description features, including height index, roughness, and slope angle, are calculated and estimated. The slope angle is estimated using random sample consensus (RANSAC) and least squares method, and specifically, the roughness is combined to eliminate false slopes. Experimental results verified the effectiveness of the proposed method.