Robust Detection and Recognition of Buildings in Urban Environments from LADAR Data

Authors:
R. Madhavan;T. Hong
Affiliations:
National Institute of Standards and Technology, Gaithersburg, MD;National Institute of Standards and Technology, Gaithersburg, MD
Venue:
AIPR '04 Proceedings of the 33rd Applied Imagery Pattern Recognition Workshop
Year:
2004

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Building-based structural data for core functions of outdoor scene analysis

ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications

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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.