via University of Sheffield
New research revealing how honeybees can make fast and accurate decisions, which could help to design more efficient robots and autonomous machines, has been published by scientists at the University of Sheffield.
- University of Sheffield scientists have revealed how honeybees are fast and accurate decision-makers when deciding which flowers to visit when searching for nectar
- Despite having a brain the size of a sesame seed, study shows honeybees excel at decision-making and could inspire the design of more efficient robots and autonomous machines
- University of Sheffield researchers are reverse engineering the honeybee brain to enable robots and autonomous vehicles to see, sense, navigate and make decisions like insects do
The study, led by Dr HaDi MaBouDi from the University’s Department of Computer Science with Professor Andrew Barron from Macquarie University in Sydney, has uncovered the complex strategies that honeybees use to decide which flowers are worth exploring.
Despite this complexity, the research has revealed how the insects make rapid decisions about where to forage for nectar. Their decisions are highly accurate – more so than humans – despite the honeybee brain being the same size as a sesame seed.
Published in the journal eLife, the study has enhanced our understanding of how the honeybee brain works and has evolved, and the Sheffield scientists say it is inspiring a new generation of robots and autonomous machines that can think like a bee – capable of making fast, accurate and efficient decisions autonomously.
In the study, the researchers trained 20 bees to recognise five different coloured artificial flowers. Blue flowers always contained sugar syrup, green flowers always contained tonic water with a bitter taste that bees dislike and the remaining colours sometimes had glucose.
The team then introduced the bees to a custom-designed garden where the flowers only had distilled water to test their performance in different scenarios. The researchers filmed each bee then tracked their path and timed how long it took them to make a decision on which flower to visit.
Results showed that if the bees were confident that a flower would have food, they quickly decided to land on it – on average in 0.6 seconds. If they were confident that a flower would not have food, they made a decision just as quickly.
The scientists then built a computer model aiming to replicate the bees’ decision-making process. Upon review, they found the structure of their computer model looked very similar to the physical layout of a honeybee brain.
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