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题名: A novel outdoor scene-understanding framework for unmanned ground vehicles with 3D laser scanners
作者: Zhuang Y(庄严); He, Guojian; Hu, Huosheng; Wu ZW(吴镇炜)
作者部门: 机器人学研究室
关键词: 3D point clouds ; laser scanner ; unmanned ground vehicles ; urban scene understanding
刊名: Transactions of the Institute of Measurement and Control
ISSN号: 0142-3312
出版日期: 2015
卷号: 37, 期号:4, 页码:435-445
收录类别: SCI ; EI
产权排序: 1
摘要: Outdoor scene understanding plays a key role for unmanned ground vehicles (UGVs) to navigate in complex urban environments. This paper presents a novel 3D scene-understanding framework for UGVs to handle uncertain and changing lighting conditions outdoors. A 2D bearing angle (BA) image is deployed to perform scene understanding so that the computational burden in the process of segmentation and classification of the 3D laser point cloud can be reduced. An improved super-pixel algorithm is used for fast 3D scene segmentation, and then the Gentle-Adaboost algorithm is utilized to perform super-pixel patch classification using the texture features of the Gray Level Co-occurrence Matrix. All false classification results in the uncertain super-pixel patches of BA images are transformed back to raw 3D laser points and a re-classification is conducted to refine the 3D scene understanding for UGVs. The results from a real laser dataset taken from a large-scale campus environment show the validity and robust performance of the proposed approach, in comparison with the results from Korea Advanced Institute of Science and Technology dataset.
语种: 英语
WOS记录号: WOS:000351052900001
WOS标题词: Science & Technology ; Technology
类目[WOS]: Automation & Control Systems ; Instruments & Instrumentation
关键词[WOS]: CLASSIFICATION ; SEGMENTATION
研究领域[WOS]: Automation & Control Systems ; Instruments & Instrumentation
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内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/15776
Appears in Collections:机器人学研究室_期刊论文

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