University of Cincinnati (UC) researchers have developed a flapping-wing drone that can navigate autonomously and hover around a moving light, much like a moth. This innovative drone operates without artificial intelligence or global-positioning equipment.
UC College of Engineering and Applied Science Assistant Professor Sameh Eisa and his aerospace engineering students are studying these drones for their highly efficient flight capabilities. Their research suggests the technology could be scaled down for covert surveillance operations.
Moths possess an exceptional ability to hover in place, fly backwards, and make precise adjustments to counteract wind or obstacles. Similarly, Eisa's drone constantly adjusts to maintain a desired attitude and distance from a light source, even when it moves.
The drone employs "extremum-seeking feedback systems," a principle theorised by Eisa and doctoral student Ahmed Elgohary. These systems facilitate real-time drone navigation by making constant adjustments to control inputs, such as the number of wing flaps per second.
This method allows the drone to operate without complex calculations, global-positioning equipment, or artificial intelligence. Elgohary, the study’s lead author, stated, "Our simulations show that extremum-seeking control can naturally reproduce the stable hovering behaviour seen in insects — without AI or complex models.”
The latest project was published in the journal *Physical Review E*. The research takes place in Eisa’s Modeling, Dynamics and Control Lab, where he previously explored animal-inspired engineering, including drones harnessing dynamic soaring like albatrosses.
The flapper drone controls its roll, pitch, and yaw by independently flapping its four wire and fabric wings. This independent flapping occurs too rapidly for the human eye to perceive, appearing instead as a blur, similar to a hummingbird’s wings.
The drone continuously measures its performance to optimise functions, like finding a light source, in a constant feedback loop. This enables remarkably consistent and stable flight, allowing it to match the subtle back-and-forth sway of various hovering insects and hummingbirds.
The drone was designed to mimic the flight patterns of moths, bumblebees, dragonflies, hoverflies, and craneflies. Hovering insects, such as the nectar-loving hummingbird clearwing moth, achieve lift on both the downstroke and upstroke of their wings through a unique figure-eight motion.
Elgohary and graduate student Rohan Palanikumar demonstrated the drone's flight in Eisa's flight lab, which is enclosed by soft netting. They noted that controlling the sensitive drone manually is significantly more challenging and less dependable than using its autonomous system.
Once activated, the flapper drone lifted and hovered with a slight, intentional wobble. This wobble provides the necessary perturbations for the system to evaluate changes in performance, enabling continuous course correction to optimise its flight.
Eisa highlighted the research's significance for new autonomous unmanned aerial vehicles and for understanding how tiny insects achieve complex aerobatics with brains the size of a pollen grain. He added, "It could change a lot of things about biophysics."
Eisa suggested that if hovering insects, like moths, employ the equivalent of extremum-seeking feedback, this mechanism likely evolved in other creatures as well.
University of Cincinnati researchers developed a flapping-wing drone that navigates autonomously without AI or GPS.
The drone mimics moths' ability to locate and hover around a moving light.
It uses "extremum-seeking feedback systems" for real-time navigation by constantly adjusting wing flaps.
Source: UC NEWS
