Paper Info
Title
A novel setup method of 3D LIDAR for negative obstacle detection in field environment
Abstract
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.
Year
DOI
Venue
2014
10.1109/ITSC.2014.6957888
ITSC
Keywords
Field
DocType
belief networks,collision avoidance,intelligent transportation systems,remotely operated vehicles,road vehicle radar,support vector machines,3d lidar,bayesian framework,svm,ugv,field environment,negative obstacle detection,support vector machine,unmanned ground vehicle,laser radar,visualization,sensors,calibration
Computer vision,Obstacle,Visualization,Simulation,Support vector machine,Unmanned ground vehicle,Lidar,Artificial intelligence,Lidar data,Engineering,Calibration,Bayesian probability
Conference
Citations 
PageRank 
References 
3
0.44
7
Authors
4
Name
Order
Citations
PageRank
Er-Ke Shang1243.10
Xiangjing An222612.15
Jian Li361.53
Hangen He430723.86