Real-Time Object Detection Using a Sparse 4-Layer LIDAR

M.P. Muresan, S. Nedevschi, I. Giosan

Proceedings of 2017 13th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), Cluj-Napoca, Romania, September 7-9, 2017, pp. 317-322.

The robust detection of obstacles, on a given road path by vehicles equipped with range measurement devices represents a requirement for many research fields including autonomous driving and advanced driving assistance systems. One particular sensor system used for measurement tasks, due to its known accuracy, is the LIDAR (Light Detection and Ranging). The commercial price and computational intensiveness of such systems generally increase with the number of scanning layers. For this reason, in this paper, a novel six step based obstacle detection approach using a 4-layer LIDAR is presented. In the proposed pipeline we tackle the problem of data correction and temporal point cloud fusion and we present an original method for detecting obstacles using a combination between a polar histogram and an elevation grid. The results have been validated by using objects provided from other range measurement sensors.