A computer model of how bees use vision to avoid hitting walls could be a breakthrough in the development of autonomous drones.
Bees control their flight using the speed of motion (optic flow) of the visual world around them. A study by Scientists at the University of Sheffield Department of Computer Science suggests how motion-direction detecting circuits could be wired together to also detect motion-speed, which is crucial for controlling bees’ flight.
“Honeybees are excellent navigators and explorers, using vision extensively in these tasks, despite having a brain of only one million neurons,” said Alex Cope, PhD., lead researcher on the paper. “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,” he added.
“Experimental evidence shows that they use an estimate of the speed that patterns move across their compound eyes (angular velocity) to control their behaviour and avoid obstacles; however, the brain circuitry used to extract this information is not understood, ” the researchers note. “We have created a model that uses a small number of assumptions to demonstrate a plausible set of circuitry. Since bees only extract an estimate of angular velocity, they show differences from the expected behaviour for perfect angular velocity detection, and our model reproduces these differences.”
Their open-access paper is published in PLOS Computational Biology.
Image: A visualization of the model taken at one time point while running. Each sphere represents a computational unit, with lines representing the connection between units. The colors represent the output of each unit. The left and right of the image are the inputs to the model and the center is the output, which is used to guide the virtual bee down a simulated corridor. (credit: The University of Sheffield)
Source: Kurzweil