Research on Object Recognition Method Robust to LIDAR Installation Height

Abstract

LIDAR has attracted attention as a surrounding environment recognition sensor in advanced driving support system (ADAS). The number of scan lines of LIDAR irradiated on objects varies, when setting LIDAR at different height. This variation causes the decrease of the recognition performance. We improved our proposal method with added pooling layer, and enhanced robustness against the variation of LIDAR setting height. And we classified the simulation data and KITTI dataset of pedestrians, cars, bicycles, motorbikes, and other objects. The results showed the our improved proposal method had robustness against the variation of LIDAR setting height.