Demonstrates improved odor-source localization in bio-hybrid drones, suggesting enhanced navigation capabilities.
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.
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Fukui et al. (2025) studied this question.
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