HuBot: A Biomimicking Mobile Robot for Non-Disruptive Bird Behavior Study

Khalifa University of Science and Technology, UAE
RENECO International Wildlife Consultants LLC, UAE
International Fund for Houbara Conservation (IFHC), UAE
Preprint 2024
HuBot’s autonomous bird observational system

HuBot’s autonomous bird observational system. HuBot leverages real-time bird detection via a YOLOv9 deep learning model to scan its environment. MobileSAM further refines its location and distance upon identifying a bird through sensor fusion techniques. This information allows HuBot to autonomously adjust its position and approach the bird while executing pre-programmed behaviors for closer observation.

Abstract

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 un- precedented 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.

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BibTeX


  @article{SAADSAOUD2025102939,
title = {HuBot: A biomimicking mobile robot for non-disruptive bird behavior study},
journal = {Ecological Informatics},
volume = {85},
pages = {102939},
year = {2025},
issn = {1574-9541},
doi = {https://doi.org/10.1016/j.ecoinf.2024.102939},
url = {https://www.sciencedirect.com/science/article/pii/S1574954124004813},
author = {Lyes {Saad Saoud} and Loïc Lesobre and Enrico Sorato and Saud Al Qaydi and Yves Hingrat and Lakmal Seneviratne and Irfan Hussain}
        }
        
  @misc{HuBotDataset,
  author = {Saad Saoud, Lyes and et al.},
  title = {HuBot Dataset: Annotated Data for Non-Disruptive Bird Behavior Study},
  year = {2024},
  publisher = {Mendeley Data},
  version = {V1},
  doi = {10.17632/tx3vrvsrgv.1},
  url = {https://doi.org/10.17632/tx3vrvsrgv.1}}