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<p>Bio-hybrid drones, which combine biological odor sensors with small drones, introduce an innovative navigation method that compensates for traditional image-based navigation, enhancing the capabilities of aerial robots. Inspired by the odor-source search behavior observed in biological organisms, we identified two key elements for improving odor source direction estimation accuracy for bio-hybrid drones: (1) increasing the anisotropy of the odor sensor using a sensor enclosure, and (2) implementing a stepped rotation algorithm that strategically incorporates pauses during scanning. This integration resulted in a doubling of both search accuracy and range, achieving a search distance of up to 5 m, significantly exceeding the performance of a previous algorithm that sequentially combined rotational and linear motions. Although these elements are commonly observed in various arthropods, they are underapplied in robotics applications. This study provides a novel perspective to robotic olfactory navigation techniques by leveraging these biological behaviors to enhance robotic functionality.</p>

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Advanced bio-hybrid drone for superior odor-source localization: high-precision and extended-range detection capabilities

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月5日

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  • Chihiro Fukui,
  • Tomoya Uchida,
  • Sakito Koizumi,
  • Yuta Murayama,
  • Hao Liu,
  • Toshiyuki Nakata,
  • Daigo Terutsuki

摘要

Bio-hybrid drones, which combine biological odor sensors with small drones, introduce an innovative navigation method that compensates for traditional image-based navigation, enhancing the capabilities of aerial robots. Inspired by the odor-source search behavior observed in biological organisms, we identified two key elements for improving odor source direction estimation accuracy for bio-hybrid drones: (1) increasing the anisotropy of the odor sensor using a sensor enclosure, and (2) implementing a stepped rotation algorithm that strategically incorporates pauses during scanning. This integration resulted in a doubling of both search accuracy and range, achieving a search distance of up to 5 m, significantly exceeding the performance of a previous algorithm that sequentially combined rotational and linear motions. Although these elements are commonly observed in various arthropods, they are underapplied in robotics applications. This study provides a novel perspective to robotic olfactory navigation techniques by leveraging these biological behaviors to enhance robotic functionality.