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The lead author, Dr. Sridhar Ravi, studied the way bumblebees sailed through a tunnel with a series of gates with holes of different sizes. The bees were able to successfully fly through the openings, thanks to a remarkable sense of their own size and a detailed perception of obstacle openings.
Dr Ravi said that by scanning the opening, the bumblebees were able to skillfully pass through the gates by manipulating the speed of their approach and posture, even by flying sideways when the hole was smaller than their wingspan. Behavior that required an awareness of one’s body shape and size relative to obstacles, this is the first time such evidence has been seen in flying invertebrates.
Previous research had indicated that complex processes, such as perception of self size, were cognitively driven and only present in animals with large brains. However, our research indicates that small insect with a brain even smaller, can include the size of their body and use that information while flying in a complex environment, “said Dr. Ravi.
Using the “ lateral peering ”, a process in which the bee scans a feature using depth perception and spatial awareness, insects build a complete map of the opening and can change the orientation of their bodies to fit through space, similar to how humans roll their backs to pass through a narrow door.
“We were amazed to see that in some cases the bumblebees have reoriented sideways to fly through gaps they were unable to experience from the front. The dexterity of these insects really got us thinking about what other secret bee behaviors we might unlock, ”said Dr Ravi.
The research also provides the inspiration to apply the attributes of bumblebees to robotics with potential applications for the next generation of drones and the technology of autonomous vehicles to meet the challenges of flying in real conditions.
“Insects are fantastic models for robots because they have extremely small brains and yet are capable of overly complex tasks. For thousands of years, nature has coded insects with some surprising attributes. Our challenge now is to see how we can take this and apply similar coding to future robotic systems, improving their performance in the natural world, ”said Dr Ravi.
The research, published in Proceedings of the National Academy of Sciences of the United States of America (PNAS), is a collaboration between researchers from UNSW Canberra, the University of Bielefeld, the Max Planck Institute, Brown University and the University of California.
The photographs of Dr. Sridhar Ravi and videos of the experiment are available online.
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