We introduce a novel measure of terrain unevenness, which is computed in terms of ranges of neighbouring laser beams of a 3D laser scanner mounted on a mobile robot. The unevenness so computed over all sampled points forms an unevenness field around the robot. We explore the nature of this measure of unevenness through analysis, and arrive at a reasonable policy for setting thresholds on unevenness in order to detect obstacles, and in the process mark out the traversable region around the mobile robot. The traversable region is obtained as a connectivity graph over 180 × 32 cells in about 30 ms time on an Intel i3 processor. This connectivity graph can be potentially used for path planning of the mobile robot. Conceptually and computationally the measure is simple and efficient. It has an added advantage of being robust against small tilts of the sensor during locomotion. It also works well on slopes. Although there are numerous ways of detecting traversable regions in the literature, it is the novelty of the measure and its analysis, which we believe is our contribution through this paper. We demonstrate its usefulness through experimental results and compare its performance with a standard method that uses both height and slope between neighbouring range points to detect obstacles.
['Satish Kumar Reddy', 'Prabir K. Pal']
Computing an unevenness field from 3D laser range data to obtain traversable region around a mobile robot