Robust detection and recognition of buildings in urban environments from LADAR data

R. Madhavan, T. Hong
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引用次数: 13

Abstract

Successful unmanned ground vehicle (UGV) navigation in urban areas requires the competence of the vehicle to cope with Global Positioning System (GPS) outages and/or unreliable position estimates due to multipathing. At the National Institute of Standards and Technology (NIST) we are developing registration algorithms using LADAR (LAser Detection And Ranging) data to cope with such scenarios. In this paper, we present a building detection and recognition (BDR) algorithm using LADAR range images acquired from UGVs towards reliable and efficient registration. We verify the proposed algorithms using field data obtained from a Riegl LADAR range sensor mounted on a UGV operating in a variety of unknown urban environments. The presented results show the robustness and efficacy of the BDR algorithm.
基于LADAR数据的城市环境中建筑物的鲁棒检测和识别
无人地面车辆(UGV)在城市地区的成功导航需要车辆能够应对全球定位系统(GPS)中断和/或由于多路径导致的不可靠位置估计。在美国国家标准与技术研究所(NIST),我们正在开发使用LADAR(激光探测和测距)数据的注册算法来应对这种情况。本文提出了一种基于地面车辆雷达距离图像的建筑物检测与识别(BDR)算法,以实现可靠、高效的配准。我们使用安装在UGV上的Riegl LADAR距离传感器获得的现场数据验证了所提出的算法,该传感器在各种未知的城市环境中运行。实验结果表明了BDR算法的鲁棒性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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