Robust Curb Detection Based on the Accessible Route Analysis and Key Frames Prediction

CORC > 合肥物质科学研究院 > 中国科学院合肥物质科学研究院 > 中科院合肥智能机械研究所

	Robust Curb Detection Based on the Accessible Route Analysis and Key Frames Prediction
	Yu ZH(余泽海)1,2; Zhu H(祝辉)2; Lin LL(林玲龙)2; Yang HZ(杨浩哲)1,2
	2021-08-26
会议日期	2021-5-28
关键词	Autonomous driving curb detection LiDAR accessible route key frame Bayesian filter
英文摘要	For autonomous driving in urban environments, road curb plays a significant role in tasks such as lane-keeping, assisted localization, and path planning. A real-time robust curb detection algorithm based on 3D LiDAR is proposed in this paper. Firstly, the iterative beam model is applied to get the accessible route of the road to obtain the starting point of the search step for each scan line. Secondly, the candidate curb points are extracted according to the spatial distribution characteristics of the point cloud. To effectively combine the historical boundaries information, a Bayesian filter is used to track the road width to reduce the false detection of curb points when the boundaries are interrupted, or on-road obstacles appear. The proposed algorithm is tested in different road environments. The experimental results show that our method has strong scene adaptability. The detection accuracy is over 90%, and the average runtime is 34.62 ms.
会议录	2021 IEEE International Conference on Artificial Intelligence and Industrial Design
语种	英语
内容类型	会议论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/125912]
专题	合肥物质科学研究院_中科院合肥智能机械研究所
作者单位	1.中国科学技术大学 2.中科学院合肥物质科学研究院
推荐引用方式 GB/T 7714	Yu ZH,Zhu H,Lin LL,et al. Robust Curb Detection Based on the Accessible Route Analysis and Key Frames Prediction[C]. 见:. 2021-5-28.