关于自动驾驶:为什么在定位中必须使用整体匹配和特征匹配?

Mohammad Aldibaja, N. Suganuma, Keisuke Yoneda, R. Yanase, Akisue Kuramoto
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引用次数: 3

摘要

本文强调了在自动驾驶中整合整体和基于特征的定位系统的重要性。基于强度的定位系统通过计算激光雷达与地图图像之间的匹配分数来表示,而基于特征的定位系统通过提取相对于车辆航向角的侧边来集成。然后,基于地图和激光雷达图像之间的共同特征,应用边缘匹配技术估计横向位置。实验结果表明,结合图像和边缘匹配结果,对天气和环境条件变化的横向和纵向姿态估计具有更强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On autonomous driving: Why holistic and feature matching must be used in localization?
This paper highlights the importance of incorporating holistic and feature based localization systems in autonomous driving. The intensity based localization system is represented by calculating the matching score between LIDAR and map images whereas the feature based system is integrated by extracting the lateral edges with respect to the vehicle heading angle. An edge matching technique is then applied to estimate the lateral position based on the common features between the map and LIDAR images. The experimental results have verified that the estimation of the lateral and longitudinal poses has become more robust by combining the image and edge matching results against the changes of weather and environmental conditions.
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