Abstract 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.

中文翻译：

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基于从 3-D 激光雷达扫描中提取的极地地标的城市环境中的长期车辆定位

摘要 由于它们的普遍性和长期稳定性，杆状物体非常适合作为城市环境中车辆定位的地标。在这项工作中，我们基于从 3-D 激光雷达数据中提取的极点地标，提出了一个完整的映射和长期定位系统。我们的方法具有一个新颖的极点检测器、一个映射模块和一个在线定位模块，每个模块都有详细的描述，我们为此提供了一个开源实现（Schaefer 和 Buscher，0000）。在大量实验中，我们证明了我们的方法在长期可靠性和准确性方面改进了现有技术：首先，我们通过在市区 15 个月内对系统进行定位移动机器人的任务来证明可靠性基于初始地图​​，面对不断变化的路线，不同的天气条件、季节变化和建筑工地。其次，我们表明所提出的方法在准确性方面明显优于最近发布的方法。