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

Published

Author(s)

Rajmohan (. Madhavan, Tsai H. Hong

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.
Conference Dates
October 13-15, 2004
Conference Location
Washington, DC, USA
Conference Title
Applied Imagery Pattern Recognition (AIPR): Emerging Technologies & Applications for Imagery Pattern Recognition

Keywords

Building detection, LADAR, LADAR/LIDAR Sensors, registration, Robotics & Intelligent Systems, UAV, Unmanned Ground Vehicle (UGV), Unmanned Systems

Citation

Madhavan, R. and Hong, T. (2004), Robust Detection and Recognition of Buildings in Urban Enviroments from LADAR Data, Applied Imagery Pattern Recognition (AIPR): Emerging Technologies & Applications for Imagery Pattern Recognition, Washington, DC, USA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822521 (Accessed April 21, 2024)
Created October 14, 2004, Updated October 12, 2021