A novel setup method of 3D LIDAR for negative obstacle detection in field environment

Negative obstacle detection is an important task for Unmanned Ground Vehicle (UGV) driving safely in field environments. This paper presents a novel 3D LiDAR setup method to deal with this issue. The proposed setup method has two advantages: 1) the blind area near the vehicle is greatly shrunken, which is very important in driving on narrow roads or taking a turning for the field UGV. 2) Compared to the traditional uprightly mounted LiDAR, the density of LiDAR data with this novel setup method is greatly improved, which is very useful both for positive and negative obstacle detection. With this new setup, a geometrical character based approach is introduced for the negative obstacle detection. Two cues, the width and the back of the negative obstacle are taken into consideration in this paper. Support Vector Machine (SVM) is employed to classify negative obstacles from the background. Meanwhile, these features are combined under a Bayesian framework. Experimental results show that the proposed setup method is useful and the proposed negative obstacle detection approach is effective.