Flying robots that behave like hummingbirds were developed that are trained by machine learning algorithms based on various techniques the bird uses naturally every day. This means that after learning from a simulation, the robot “knows” how to move around on its own like a hummingbird would such as discerning when to perform an escape maneuver.

Artificial intelligence (AI), combined with flexible flapping wings, also allows the robot to teach itself new tricks. Even though the robot can’t see, for example, it senses by touching surfaces. Each touch alters an electrical current that can be tracked. The robot can essentially create a map without seeing its surroundings, which could be helpful when the robot is searching for victims in a dark place.

Drones can’t be made infinitely smaller due to the way conventional aerodynamics work and they wouldn’t be able to generate enough lift to support their weight. But hummingbirds don’t use conventional aerodynamics and their wings are resilient.

The robots have 3D-printed bodies, wings made of carbon fiber, and laser-cut membranes. The researchers built one hummingbird robot weighing 12 grams — the weight of the average adult magnificent hummingbird — and another insect-sized robot weighing 1 gram. The hummingbird robot can lift more than its own weight (up to 27 grams).

Designing the robots with higher lift enables them to eventually incude a battery and sensing technology such as a camera or GPS. Currently, the robot needs to be tethered to an energy source while it flies but soon will be untethered.

The robots could fly silently just as a real hummingbird does, making them more ideal for covert operations. And they stay steady through turbulence, which was demonstrated by testing the dynamically scaled wings in an oil tank. The robot requires only two motors and can control each wing independently of the other, which is how flying animals perform highly agile maneuvers in nature.

Watch it fly on Tech Briefs TV here. For more information, contact Xinyan Deng at This email address is being protected from spambots. You need JavaScript enabled to view it.; 765-494-1513.