Bee Model Developed by University of Sheffield Could Help Advance Autonomous Robots

A computer model has been created by University of Sheffield scientists to study how bees are able to fly without hitting walls. This knowledge will be helpful to develop autonomous robots.

The computer model, developed by researchers at the Department of Computer Science, help to study how bees utilize vision to avoid crashes, by detecting the movement of the surrounding world. It is a known fact that bees use the speed of motion or optic flow of the surrounding visual world for controlling their flight. However, how it has been executed by bees remains a mystery. The neural circuits that are found in the brain of the bees are responsible for helping the insect to detect the direction of movement, not the speed.

The study results show the possibility of using the motion-direction detecting circuits to determine motion-speed, which is critical for controlling the flight of the insect. The researchers have described their work in a paper, titled “A Model for an Angular Velocity-Tuned Motion Detector Accounting for Deviations in the Corridor-Centering Response of the Bee,” in the PLOS Computational Biology journal.

Honeybees are excellent navigators and explorers, using vision extensively in these tasks, despite having a brain of only one million neurons. Understanding how bees avoid walls, and what information they can use to navigate, moves us closer to the development of efficient algorithms for navigation and routing - which would greatly enhance the performance of autonomous flying robotics.

Dr Alex Cope, University of Sheffield

Professor James Marshall, the lead investigator of the project, added: “This is the reason why bees are confused by Windows - since they are transparent they generate hardly any optic flow as bees approach them.”

Dr Cope and his collaborators on the project; Dr Chelsea Sabo, Dr Eleni Vasilaki, Professor Kevin Gurney, and Professor James Marshall, are now applying this finding to explore how bees recognize the direction of flight and use this insight to solve tasks.

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