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Towards an autonomous vision-based unmanned aerial system against wildlife poachers.

Olivares-Mendez, Miguel A.; Fu, Changhong; Ludivig, Philippe; Bissyandé, Tegawendé F.; Kannan, Somasundar; Zurad, Maciej; Annaiyan, Arun; Voos, Holger; Campoy, Pascual

Authors

Miguel A. Olivares-Mendez

Changhong Fu

Philippe Ludivig

Tegawendé F. Bissyandé

Maciej Zurad

Arun Annaiyan

Holger Voos

Pascual Campoy



Abstract

Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $ 213 billion every year, which is even helping to fund armed conflicts. Poaching activities around the world are further pushing many animal species on the brink of extinction. Unfortunately, the traditional methods to fight against poachers are not enough, hence the new demands for more efficient approaches. In this context, the use of new technologies on sensors and algorithms, as well as aerial platforms is crucial to face the high increase of poaching activities in the last few years. Our work is focused on the use of vision sensors on UAVs for the detection and tracking of animals and poachers, as well as the use of such sensors to control quadrotors during autonomous vehicle following and autonomous landing.

Citation

OLIVARES-MENDEZ, M.A., FU, C., LUDIVIG, P., BISSYANDÉ, T.F., KANNAN, S., ZURAD, M., ANNAIYAN, A., VOOS, H. and CAMPOY, P. 2015. Towards an autonomous vision-based unmanned aerial system against wildlife poachers. Sensors [online], 15(12), pages 31362-31391. Available from: https://doi.org/10.3390/s151229861

Journal Article Type Article
Acceptance Date Dec 2, 2015
Online Publication Date Dec 12, 2015
Publication Date Dec 31, 2015
Deposit Date Feb 23, 2021
Publicly Available Date Feb 23, 2021
Journal Sensors
Print ISSN 1424-8220
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 15
Issue 12
Pages 31362-31391
DOI https://doi.org/10.3390/s151229861
Keywords Unmanned aerial vehicles; Computer vision; Animal tracking; Face detection; Vision-based control; Object following; Autonomous navigation; Autonomous landing; Anti-poaching
Public URL https://rgu-repository.worktribe.com/output/1206031

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