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Artificial Life and Robotics
Published in: Artificial Life and Robotics 2/2019

15-10-2018 | Original Article

Mono-camera based vehicle localization using lidar intensity map for automated driving

Authors: Keisuke Yoneda, Ryo Yanase, Mohammad Aldibaja, Naoki Suganuma, Kei Sato

Published in: Artificial Life and Robotics | Issue 2/2019

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Abstract

This paper reports an image-based localization for automated vehicle. The proposed method utilizes a mono-camera and an inertial measurement unit to estimate the vehicle pose. Self-localization is implemented by a map matching technique between the reference digital map and sensor observations. In general, the same types of sensors are used for map data and observations. However, this study is focused on the mono-camera based method using Lidar-based map for the purpose of a low-cost implementation. Image template matching is applied to provide a correlation distribution between the captured image and the predefined orthogonal map. A probability of the vehicle pose is then updated using the obtained correlation. The experiments were carried out for real driving data on an urban road. The results have verified that the proposed method estimates the vehicle position in 0.11[m] positioning errors on real-time.
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Metadata
Title
Mono-camera based vehicle localization using lidar intensity map for automated driving
Authors
Keisuke Yoneda
Ryo Yanase
Mohammad Aldibaja
Naoki Suganuma
Kei Sato
Publication date
15-10-2018
Publisher
Springer Japan
Published in
Artificial Life and Robotics / Issue 2/2019
Print ISSN: 1433-5298
Electronic ISSN: 1614-7456
DOI
https://doi.org/10.1007/s10015-018-0502-6

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