4.5 Article

Long-term vehicle localization in urban environments based on pole landmarks extracted from 3-D lidar scans

Journal

ROBOTICS AND AUTONOMOUS SYSTEMS
Volume 136, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.robot.2020.103709

Keywords

Mapping; Localization; Lidar; Pole; Landmark; Feature extraction; Autonomous driving

Funding

  1. Samsung Electronics Co. Ltd. under the GRO program

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This work presents a mapping and long-term localization system based on pole landmarks extracted from 3-D lidar data. Through extensive experiments, it has been demonstrated that the proposed approach improves on the state of the art in terms of long-term reliability and accuracy.
Due to their ubiquity and long-term stability, pole-like objects are well suited to serve as landmarks for vehicle localization in urban environments. In this work, we present a complete mapping and long-term localization system based on pole landmarks extracted from 3-D lidar data. Our approach features a novel pole detector, a mapping module, and an online localization module, each of which are described in detail, and for which we provide an open-source implementation (Schaefer and Buscher, 0000). In extensive experiments, we demonstrate that our method improves on the state of the art with respect to long-term reliability and accuracy: First, we prove reliability by tasking the system with localizing a mobile robot over the course of 15 months in an urban area based on an initial map, confronting it with constantly varying routes, differing weather conditions, seasonal changes, and construction sites. Second, we show that the proposed approach clearly outperforms a recently published method in terms of accuracy. (C) 2020 Elsevier B.V. All rights reserved.

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