A bio-inspired looming detection for stable landing in unmanned aerial vehicles<sup>*</sup>

Flying insects, such as flies and bees, have evolved the capability to rely solely on visual cues for smooth and secure landings on various surfaces. In the process of carrying out tasks, micro unmanned aerial vehicles (UAVs) may encounter various emergencies, and it is necessary to land safely in complex and unpredictable ground environments, especially when altitude information is not accurately obtained, which undoubtedly poses a significant challenge. Our study draws on the remarkable response mechanism of the Lobula Giant Movement Detector to looming scenarios to develop a novel UAV landing strategy. The proposed strategy does not require distance estimation, making it particularly suitable for payload-constrained micro aerial vehicles. Through a series of experiments, this strategy has proven to effectively achieve stable and high-performance landings in unknown and complex environments using only a monocular camera. Furthermore, a novel mechanism to trigger the final landing phase has been introduced, further ensuring the safe and stable touchdown of the drone.

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Publication Details

Journal
Bioinspiration & Biomimetics
Published
2024-10-31
DOI
https://doi.org/10.1088/1748-3190/ad8d99
Citations
3
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.75
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article

A bio-inspired looming detection for stable landing in unmanned aerial vehicles*

Jiannan Zhao, Liubin Song, Y Xie
3 citations
Bioinspiration & Biomimetics
Robotic Path Planning Algorithms
0.75
article

A bio-inspired looming detection for stable landing in unmanned aerial vehicles*

Jiannan Zhao, Liubin Song, Y Xie
article en
3 citations

Abstract

Flying insects, such as flies and bees, have evolved the capability to rely solely on visual cues for smooth and secure landings on various surfaces. In the process of carrying out tasks, micro unmanned aerial vehicles (UAVs) may encounter various emergencies, and it is necessary to land safely in complex and unpredictable ground environments, especially when altitude information is not accurately obtained, which undoubtedly poses a significant challenge. Our study draws on the remarkable response mechanism of the Lobula Giant Movement Detector to looming scenarios to develop a novel UAV landing strategy. The proposed strategy does not require distance estimation, making it particularly suitable for payload-constrained micro aerial vehicles. Through a series of experiments, this strategy has proven to effectively achieve stable and high-performance landings in unknown and complex environments using only a monocular camera. Furthermore, a novel mechanism to trigger the final landing phase has been introduced, further ensuring the safe and stable touchdown of the drone.

Bioinspiration & BiomimeticsVol. 20(1)
Guangxi University (CN), Guangxi Academy of Sciences (CN)
Life below water
Openalex Percentile: Top 27%
Robotic Path Planning Algorithms
0.75
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A bio-inspired looming detection for stable landing in unmanned aerial vehicles<sup>*</sup> — Jiannan Zhao, Liubin Song, et al. · Bioinspiration & Biomimetics (2024) | TGRS Research Map | TGRS