Analysis of collision avoidance in honeybee flight.

Shreyansh Singh, Matthew Garratt, Mandyam Srinivasan, Sridhar Ravi
Author Information
  1. Shreyansh Singh: School of Engineering and Technology, University of New South Wales, Canberra, Australia.
  2. Matthew Garratt: School of Engineering and Technology, University of New South Wales, Canberra, Australia.
  3. Mandyam Srinivasan: Queensland Brain Institute, University of Queensland, Brisbane, Australia.
  4. Sridhar Ravi: School of Engineering and Technology, University of New South Wales, Canberra, Australia. ORCID

Abstract

Insects are excellent at flying in dense vegetation and navigating through other complex spatial environments. This study investigates the strategies used by honeybees () to avoid collisions with an obstacle encountered frontally during flight. Bees were trained to fly through a tunnel that contained a solitary vertically oriented cylindrical obstacle placed along the midline. Flight trajectories of bees were recorded for six conditions in which the diameter of the obstructing cylinder was systematically varied from 25 mm to 160 mm. Analysis of salient events during the bees' flight, such as the deceleration before the obstacle, and the initiation of the deviation in flight path to avoid collisions, revealed a strategy for obstacle avoidance that is based on the relative retinal expansion velocity generated by the obstacle when the bee is on a collision course. We find that a quantitative model, featuring a controller that extracts specific visual cues from the frontal visual field, provides an accurate characterization of the geometry and the dynamics of the manoeuvres adopted by honeybees to avoid collisions. This study paves the way for the design of unmanned aerial systems, by identifying the visual cues that are used by honeybees for performing robust obstacle avoidance flight.

Keywords

Associated Data

figshare | 10.6084/m9.figshare.c.7126127

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MeSH Term

Bees
Animals
Flight, Animal
Insecta
Cognition

Word Cloud

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