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2021 | OriginalPaper | Chapter

Road Tracking in Semi-structured Environments Using Spatial Distribution of Lidar Data

Authors : Kosmas Tsiakas, Ioannis Kostavelis, Dimitrios Giakoumis, Dimitrios Tzovaras

Published in: Pattern Recognition. ICPR International Workshops and Challenges

Publisher: Springer International Publishing

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Abstract

The future civilian, and professional autonomous vehicles to be realised into the market should apprehend and interpret the road in a manner similar to the human drivers. In structured urban environments where signs, road lanes and markers are well defined and ordered, landmark-based road tracking and localisation has significantly progressed during the last decade with many autonomous vehicles to make their debut into the market. However, in semi-structured and rural environments where traffic infrastructure is deficient, the autonomous driving is hindered by significant challenges. The paper at hand presents a Lidar-based method for road boundaries detection suitable for a service robot operation in rural and semi-structured environments. Organised Lidar data undergo a spatial distribution processing method to isolate road limits in a forward looking horizon ahead of the robot. Stereo SLAM is performed to register subsequent road limits and RANSAC is applied to identify edges that correspond to road segments. In addition, the robot traversable path is estimated and progressively merged with Bézier curves to create a smooth trajectory that respects vehicle kinematics. Experiments have been conducted on data collected from our robot on a semi-structured urban environment, while the method has also been evaluated on KITTI dataset exhibiting remarkable performance.

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Title: Road Tracking in Semi-structured Environments Using Spatial Distribution of Lidar Data
Authors: Kosmas Tsiakas
Ioannis Kostavelis
Dimitrios Giakoumis
Dimitrios Tzovaras
Publisher: Springer International Publishing
Book: Pattern Recognition. ICPR International Workshops and Challenges
Print ISBN: 978-3-030-68786-1

Electronic ISBN: 978-3-030-68787-8

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-68787-8_32

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