F. Oniga, S. Nedevschi
Proceedings of 2018 14th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), Cluj-Napoca, Romania, September 7-9, 2018, pp. 209-214.
A low complexity approach for computing the orientation of 3D obstacles, detected from lidar data, is proposed in this paper. The proposed method takes as input obstacles represented as cuboids without orientation (aligned with the reference frame). Each cuboid contains a cluster of obstacle locations (discrete grid cells). First, for each obstacle, the boundaries that are visible for the perception system are selected. A model consisting of two perpendicular lines is fitted to the set of boundary cells, one for each presumed visible side. The main dominant line is computed with a RANSAC approach. Then, the second line is searched, using a constraint of perpendicularity on the dominant line. The existence of the second line is used to validate the orientation. Finally, additional criteria are proposed to select the best orientation based on the free area of the cuboid (on top view) that is visible to the perception system.