Experiments in unmanned aerial vehicle/unmanned ground vehicle radiation search. Issue 4 (12th March 2019)

• Record Type: Journal Article
• Authors: Peterson, John; Li, Weilin; Cesar‐Tondreau, Brian; Bird, John; Kochersberger, Kevin; Czaja, Wojciech; McLean, Morgan
• Other Names: Schwertfeger Sören guestEditor.; Ohno Kazunori guestEditor.
• Is Part Of: Journal of field robotics. Volume 36:Issue 4(2019)
• Page Start: 818
• Page End: 845
• Publication Date: 2019-03-12
• Subjects: aerial robotics -- emergency response -- terrestrial robotics; Robots, Industrial -- Periodicals; Automatic control -- Periodicals; 629.892
• DOI: 10.1002/rob.21867
• Languages: English
• ISSNs: 1556-4959

Abstract

Abstract: This paper discusses the results of a field experiment conducted at Savannah River National Laboratory to test the performance of several algorithms for the localization of radioactive materials. In this multirobot system, both an unmanned aerial vehicle, a custom hexacopter, and an unmanned ground vehicle (UGV), the ClearPath Jackal, equipped with γ ‐ray spectrometers, were used to collect data from two radioactive source configurations. Both the Fourier scattering transform and the Laplacian eigenmap algorithms for source detection were tested on the collected data sets. These algorithms transform raw spectral measurements into alternate spaces to allow clustering to detect trends within the data which indicate the presence of radioactive sources. This study also presents a point source model and accompanying information‐theoretic active exploration algorithm. Field testing validated the ability of this model to fuse aerial and ground collected radiation measurements, and the exploration algorithm's ability to select informative actions to reduce model uncertainty, allowing the UGV to locate radioactive material online.