TY - JOUR
T1 - HuBot
T2 - A biomimicking mobile robot for non-disruptive bird behavior study
AU - Saad Saoud, Lyes
AU - Lesobre, Loïc
AU - Sorato, Enrico
AU - Qaydi, Saud Al
AU - Hingrat, Yves
AU - Seneviratne, Lakmal
AU - Hussain, Irfan
N1 - Publisher Copyright:
© 2024
PY - 2025/3
Y1 - 2025/3
N2 - The Houbara bustard, an avian species of conservation concern, poses significant challenges to researchers because of its elusive nature and sensitivity to human disturbances. Traditional research methods, often reliant on human observations, face some challenges and can inadvertently affect bird behavior. To overcome these limitations, we propose the HuBot, a biomimetic mobile robot designed to seamlessly integrate into the natural habitat of Houbara. By employing advanced real-time deep-learning algorithms, including YOLOv9 for detection, MobileSAM for segmentation, and vision transformer (ViT) for depth estimation, HuBot semi-autonomously tracks individual birds, providing unprecedented insights into their individual behavior, social interactions, and habitat use. HuBot can thus contribute to a deeper understanding of Houbara behavior and its ecology. The biomimetic design of the robot, including its life-like appearance and movement capabilities, minimizes disturbance, allowing for monitoring of Houbara birds while minimizing disruption to their behavior. Rigorous testing, including extensive laboratory experiments and field trials on challenging terrains, validated the performance of HuBot as a complementary tool for traditional observation methods.
AB - The Houbara bustard, an avian species of conservation concern, poses significant challenges to researchers because of its elusive nature and sensitivity to human disturbances. Traditional research methods, often reliant on human observations, face some challenges and can inadvertently affect bird behavior. To overcome these limitations, we propose the HuBot, a biomimetic mobile robot designed to seamlessly integrate into the natural habitat of Houbara. By employing advanced real-time deep-learning algorithms, including YOLOv9 for detection, MobileSAM for segmentation, and vision transformer (ViT) for depth estimation, HuBot semi-autonomously tracks individual birds, providing unprecedented insights into their individual behavior, social interactions, and habitat use. HuBot can thus contribute to a deeper understanding of Houbara behavior and its ecology. The biomimetic design of the robot, including its life-like appearance and movement capabilities, minimizes disturbance, allowing for monitoring of Houbara birds while minimizing disruption to their behavior. Rigorous testing, including extensive laboratory experiments and field trials on challenging terrains, validated the performance of HuBot as a complementary tool for traditional observation methods.
KW - Animal-inspired robots
KW - Animal–robot interaction
KW - Artificial intelligence
KW - Biomimetic robot
KW - Ecological observation
KW - Locomotion
KW - Non-invasive observation
KW - Real-time deep learning
UR - https://www.scopus.com/pages/publications/85213256592
U2 - 10.1016/j.ecoinf.2024.102939
DO - 10.1016/j.ecoinf.2024.102939
M3 - Article
AN - SCOPUS:85213256592
SN - 1574-9541
VL - 85
JO - Ecological Informatics
JF - Ecological Informatics
M1 - 102939
ER -