Although our skies are now filled with quadcopter drones, fixed-wing aircraft have them beat in both speed and endurance; that's why the military's drones don't look like the ones you'd buy on Amazon. One of the biggest drawbacks with fixed-wing planes is that they tend to require a long runway for landing. However, drone makers are searching for a better way, and it turns out nature solved the problem millions of years ago. Now, we're trying to steal its secret.
Birds don't need runways. They can land on a dime by swooping in at low altitude then angling their wings upwards and spreading their feathers to act as air brakes. It's a maneuver called a "deep stall," and you've likely seen it before.
A team of researchers from British company BMT Defence Services and the University of Bristol want to mimic this ability with a new morphing wing. "The wing can sweep forwards and backwards to create a pitching moment," says Antony Waldock, principal systems analyst at BMT Defence Services, "and the tips of the wings can twist, which allows the aircraft to roll." These two types of motion were directly inspired by bird wings and provide far more maneuverability than usual fixed wings.
"The morphing wing enables high-maneuverability while remaining power-efficient," says Waldock. "This could also allow a UAV to fly in cluttered environments." He compared it to the way a goshawk can fly through dense forest at high speed, folding its wings to avoid branches and trunks without slowing down. Future drones may swoop through urban canyons dodging lampposts, power lines and each other as easily as birds.
But wings are only part of the equation. A bird's deep stall is a complicated process in which very slight changes in speed, wind, angle, and position of the wings produced extremely different results. One slip can mean a crash. It's a calculation far too complicated for even the most experienced drone pilots. This artificial bird needed an artificial brain.
So the team turned to "Q-learning," a technique where an artificial intelligence learns by raising its "Q," or satisfaction level. Using this system, one AI recently mastered old Atari video games without any human instruction. Through innumerable failures and errors, the AI figured out how to maximize Q and hit high scores on every single game.
BMT used a similar game concept, giving the machine the end goal of arriving at a landing spot. The drone's score increased as its speed at the landing spot declined. By making slight adjustments to the controls, the AI steadily improved its score. Waldock says the AI gradually worked out how to get from any given starting point to arrive at the desired landing place with minimal horizontal and vertical speed.
Rather than going through thousands of hard landings during this learning process, the drone first practiced in the sky with a virtual 'ground' set at a fixed height. After each pretend landing, the drone recovered, gained altitude, and tried again.
Once the AI honed its perching technique, it was time to start testing real landings. Without any programming or remote controls, the machine taught itself from scratch how to land—and it kept getting better and better. After about five thousand practice attempts, the drone could pull off a successful soft landing—no runway required.
BMT's project is part of a wider defense program called Autonomous Systems Underpinning Research (ASUR), developing drone technology for the U.K.'s armed forces. The specific role of this project was to help drones land on ships (as shown in the video above), but its applications are almost endless.
A more advanced version of this perching drone could go anywhere with limited landing space, whether dousing fires, fighting a war, or just delivering a package. It could one day land on your windowsill as easily and frequently as a pigeon.