NDLI: Road edge detection based on improved RANSAC and 2D LIDAR Data

Content Provider	IEEE Xplore Digital Library
Author	Xiangdong Wang Yunfei Cai Tingmin Shi
Copyright Year	2015
Description	Author affiliation: Inst. of Intell. Robot., Nanjing Univ. of Sci. & Technol., Nanjing, China (Xiangdong Wang; Yunfei Cai; Tingmin Shi)
Abstract	For the road edge detection under the structured and semi-structured road environment, we model the road edge using a linear regression and propose an improved RANSAC algorithm to finish the model selection, and it is applied to the fitting and filtering of road edge points extracted from the 2D LIDAR (light detecting and ranging) data. First, road edge points are extracted using the discrete Kalman filter from each frame 2D LIDAR data. Then, based on GPS and gyroscope data, multiple continuous road edge points are associated to the same coordinate system by translation and rotation of the coordinate. Finally, the points are fitted and filtered adaptively by the model which is automatically selected by the improved RANSAC algorithm, and the real road edges are consequently extracted. Experimental results show the feasibility and practicability of the method.
Starting Page	191
Ending Page	196
File Size	588019
Page Count	6
File Format	PDF
e-ISBN	9781479998920
DOI	10.1109/ICCAIS.2015.7338660
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	RANSAC Road edge detection Laser radar Roads Image edge detection 2D LIDAR Linear regression Time measurement Mathematical model Kalman filters Vehicles
Content Type	Text
Resource Type	Article

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