Abstract
Tagging animals with radio devices is a commonly used technique in wildlife and conservation biology. We study the problem of localizing a tagged animal using the audio output of an off-the-shelf receiver mounted on an autonomous Unmanned Aerial Vehicle (UAV). This problem is motivated by the application of taking pictures of bears to document their interactions with the environment after contact with the radio signal has been established. We make two contributions. (1) Received signal characteristics depend on the environment, device and driver characteristics as well as target/receiver geometry. Due to complex interactions among these factors, directly estimating range or bearing from the signal may not be possible. Instead, we show that given a sufficient step-size, we can use signal characteristics to compare the proximity of two sensing locations with respect to the source. We present a novel model from data collected in field experiments. (2) Based on this model, we also present a local-search algorithm which drives the UAV toward the target. We study the performance of the algorithm in extensive simulations using field measurements. The algorithm has also been implemented on the UAV and tested in preliminary experiments.
Original language | English (US) |
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Title of host publication | 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016 |
Publisher | IEEE Computer Society |
Pages | 934-939 |
Number of pages | 6 |
ISBN (Electronic) | 9781509024094 |
DOIs | |
State | Published - Nov 14 2016 |
Event | 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016 - Fort Worth, United States Duration: Aug 21 2016 → Aug 24 2016 |
Publication series
Name | IEEE International Conference on Automation Science and Engineering |
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Volume | 2016-November |
ISSN (Print) | 2161-8070 |
ISSN (Electronic) | 2161-8089 |
Other
Other | 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016 |
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Country/Territory | United States |
City | Fort Worth |
Period | 8/21/16 → 8/24/16 |
Bibliographical note
Funding Information:This work was supported by National Science Foundation Awards #1111638, #0917676, and #1317788.
Publisher Copyright:
© 2016 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.