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Integration and operation of a sUAS-based multi-modal imaging payload equipped with a novel communication system enabling autonomous platform control
Author(s): Andrew M. Duncan; Bogdan Vacaliuc; Matthew D. Larson; Christopher Davis; David Hughes; Katie Corcoran
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Paper Abstract

Oak Ridge National Laboratory presents a new UAS-mounted multi-modal imaging payload containing five sensors. We have integrated several distinct commercially available sensors onto a large Class-1 autonomous quadcopter aircraft: a LIDAR (Light Detection and Ranging) scanner, a hyperspectral pushbroom sensor, a multispectral camera, a longwave infrared thermal camera, and an RGB camera. The system integrates our proprietary Multi-modal Autonomous Vehicle Network (MAVNet) and communication system, allowing autonomous control via multiple communication networks. Using one common Global Navigation Satellite System (GNSS) and inertial navigation system (INS/GPS), imagery from all sensors are accurately and precisely geolocated and co-registered.

Paper Details

Date Published: 13 May 2019
PDF: 12 pages
Proc. SPIE 11021, Unmanned Systems Technology XXI, 1102103 (13 May 2019); doi: 10.1117/12.2517022
Show Author Affiliations
Andrew M. Duncan, Oak Ridge National Lab. (United States)
Bogdan Vacaliuc, Oak Ridge National Lab. (United States)
Matthew D. Larson, Oak Ridge National Lab. (United States)
Christopher Davis, Oak Ridge National Lab. (United States)
David Hughes, Oak Ridge National Lab. (United States)
Katie Corcoran, Oak Ridge National Lab. (United States)

Published in SPIE Proceedings Vol. 11021:
Unmanned Systems Technology XXI
Charles M. Shoemaker; Hoa G. Nguyen; Paul L. Muench, Editor(s)

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