The secret to developing flying robots and drones may lie on honeybees or at least how they avoid obstacles and crashes, according to a new UK study.
Bees, honeybees in particular, are a unique lot. First, they don't have as many neurons as humans do (a difference of billions). However, they are described as "excellent navigators," so they don't get involved in too many crashes. They know how to look for food and even tell their fellow bees where to find them.
What makes these honeybees see? The answer is optic flow. You can liken it to an odometer of a vehicle that determines how far it has already traveled, although this one is quite different since this one is based on the speed of motion. This also explains why bees are more prone to hitting glass windows since these objects almost don't have optic flow.
To determine optic flow needs at least two things: direction and speed of motion. Scientists know the former. What they don't is the latter.
This is the subject of the study of researchers from the University of Sheffield. To find out the answer, they used a corridor centring response model.
Using the model, the researchers created how bees would probably navigate in the virtual world and then replicated it, this time taking into consideration how real bees fly based on their optic flow while passing through a corridor. They then determined the response of the insects' neurons.
The model has been particularly helpful in measuring angular velocity (AV), which subsequently prevents the bees from crashing to any obstacle by maintaining a good distance with the object.
"Based on our model we suggest that the AV response can be considered as an evolutionary extension to the optomotor response," expressed the researchers.
While the study is focused on bees, its vision may inspire the development of flying robots and drones, which still end up crashing into many things.
"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," said Dr. Alex Cope, lead researcher.
Additionally, designers can take a hint from other animals like bats and birds.
The study is now in PLOS Computational Biology.
To see the model at work, see the video below:
Photo: Cory Barnes | Flickr
