Detection of traversable region around a mobile robot by computing terrain unevenness from the range data of a 3D laser scanner

摘要

Purpose - The purpose of this paper is to detect traversable regions surrounding a mobile robot by computing terrain unevenness using the range data obtained from a single 3D scan. Design/methodology/approach - The geometry of acquiring range data from a 3D scan is exploited to probe the terrain and extract traversable regions. Nature of terrain under each scan point is quantified in terms of an unevenness value, which is computed from the difference in range of scan point with respect to its neighbours. Both radial and transverse unevenness values are computed and compared with threshold values at every point to determine if the point belongs to a traversable region or an obstacle. A region growing algorithm spreads like a wavefront to join all traversable points into a traversable region. Findings - This simple method clearly distinguishes ground and obstacle points. The method works well even in presence of terrain slopes or when the robot experiences pitch and roll. Research limitations/implications - The method applies on single 3D scans and not on aggregated point cloud in general. Practical implications - The method has been tested on a mobile robot in outdoor environment in our research centre. Social implications - This method, along with advanced navigation schemes, can reduce human intervention in many mobile robot applications including unmanned ground vehicles. Originality/value - Range difference between scan points has been used earlier for obstacle detection, but no methodology has been developed around this concept. The authors propose a concrete method based on computation of radial and transverse unevenness at every point and detecting obstacle edges using range-dependent threshold values.