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Título
Vision-Based Module for Herding with a Sheepdog Robot
Autor
Facultad/Centro
Área de conocimiento
Título de la revista
Sensors
Número de la revista
14
Datos de la obra
Riego Del Castillo, V., Sánchez-González, L., Campazas-Vega, A., & Strisciuglio, N. (2022). Vision-Based Module for Herding with a Sheepdog Robot. Sensors (Basel, Switzerland), 22(14). https://doi.org/10.3390/S22145321
Editor
MDPI
Fecha
2022-06-16
Resumo
[EN] : Livestock farming is assisted more and more by technological solutions, such as robots.
One of the main problems for shepherds is the control and care of livestock in areas difficult to
access where grazing animals are attacked by predators such as the Iberian wolf in the northwest
of the Iberian Peninsula. In this paper, we propose a system to automatically generate benchmarks
of animal images of different species from iNaturalist API, which is coupled with a vision-based
module that allows us to automatically detect predators and distinguish them from other animals.
We tested multiple existing object detection models to determine the best one in terms of efficiency
and speed, as it is conceived for real-time environments. YOLOv5m achieves the best performance
as it can process 64 FPS, achieving an mAP (with IoU of 50%) of 99.49% for a dataset where wolves
(predator) or dogs (prey) have to be detected and distinguished. This result meets the requirements
of pasture-based livestock farms.
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