상세정보
학술대회
Drivable Road Detection with 3D Point Clouds Based on the MRF for Intelligent Vehicle
- 발행일
- 201312
- 출처
- International Conference on Field and Service Robotics (FSR) 2013, pp.49-60
- 협약과제
- 13VC1700, ICT기반 차량/운전자 협력자율주행 시스템(Co-Pilot)의 판단/제어 기술 개발, 한우용
- 초록
- In this paper, a reliable road/obstacle detection with 3D point cloud for intelligent vehicle on a variety of challenging environments (undulated road and/or uphill/ downhill) is handled. For robust detection of road we propose the followings: 1) correction of 3D point cloud distorted by the motion of vehicle (high speed and heading up and down) incorporating vehicle posture information; 2) guideline for the best selection of the proper features such as gradient value, height average of neighboring node; 3) transformation of the road detection problem into a classification problem of different features; and 4) inference algorithm based on MRF with the loopy belief propagation for the area that the LIDAR does not cover. In experiments, we use a publicly available dataset as well as numerous scans acquired by the HDL-64E sensor mounted on experimental vehicle in inner city traffic scenes. The results show that the proposed method is more robust and reliable than the conventional approach based on the height value on the variety of challenging environment.
- KSP 제안 키워드
- 3D point cloud, Challenging environment, Classification problems, High Speed, Inference algorithm, Neighboring node, Obstacle Detection, belief propagation(BP), experimental vehicle, gradient value, intelligent vehicle