지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2011.10
- 수록면
- 744 - 747 (4page)
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초록· 키워드
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Typically, obstacle that UGV have to avoid can be divided into two different types, static and moving-obstacle. UGV should have an ability to separate static and moving obstacle. Because avoidance method for moving-obstacle is different from method for static-obstacle. The type of output data of LIDAR is cloud points data. When UGV separates moving obstacles, it is difficult to that trace it, calculating vectors by point unit. So we are going to simplify cloud points data into a specific object data, and judge the object"s movement. Also, we can recognize the object"s feature and dimension using processed data. It is just first step to recognize the environment with LIDAR. This research proposes the algorithm that classifies a lot of objects from LIDAR"s point cloud data; The 1st step is the segmentation that is extracting process some specific points from LIDAR"s cloud point data and is clustering step using specific points. Next step is the classification based on segmentation data. Via this process, we are able to obtain the object data. This research will be basis of recognition and avoidance algorithm for moving obstacles.
목차
Abstract
1. INTRODUCTION
2. SENSOR OVERVIEW
3. SEGMENTATION
4. CLASSIFICATION
5. EXPERIMENTS
6. COCLUSION AND DISCUSSION
7. ACKNOWLEDGMENT
REFERENCES
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UCI(KEPA) : I410-ECN-0101-2014-569-000913478