Towards an Autonomous Vision-Based Unmanned Aerial System against Wildlife Poachers

• Main Authors: Miguel A. Olivares-Mendez, Changhong Fu, Philippe Ludivig, Tegawendé F. Bissyandé, Somasundar Kannan, Maciej Zurad, Arun Annaiyan, Holger Voos, Pascual Campoy
• Format: Article
• Language: English
• Published: MDPI AG 2015-12-01
• Series: Sensors
• Subjects: unmanned aerial vehicles; computer vision; animal tracking; face detection; vision-based control; object following; autonomous navigation; autonomous landing; anti-poaching
• Online Access: http://www.mdpi.com/1424-8220/15/12/29861

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.