基于核磁共振距离的自动驾驶汽车定位与映射

Guangjing Li, H. Bao, Bo Wang, Tao Wu
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引用次数: 1

摘要

准确定位是自动驾驶汽车安全行驶的一项重要任务。为了在没有全球定位系统(GPS)信号的情况下实现自动驾驶汽车的精确定位,提出了一种基于核化r尼米距离(KRD)的同时定位与映射(SLAM)算法。在我们的算法中,通过优化两组激光点之间(在测程过程中)或激光点与局部地图之间(在测绘过程中)的KRD来计算姿态估计。实验结果表明,该算法能够准确地定位自动驾驶车辆并构建行车环境地图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Kernelised Rényi Distance for Localization and Mapping of Autonomous Vehicle
Accurate locating is an important task for autonomous vehicles' safely driving. In order to realize the precise locating autonomous vehicles without Global Positioning System(GPS) signal, a Kernelized Rényi Distance(KRD) based simultaneous localization and mapping(SLAM) algorithm is proposed in this paper. In our Algorithm, pose estimation are computed by optimizing KRD between two groups of laser point(in odometry process) or between laser points and the local map(in mapping process). The experimental results indicate that the proposed algorithm can accurately locate autonomous vehicle and build the traveled environment map.
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