Everyone knows how an airplane lands: the slow maneuvering into an approach pattern, the long descent, the brakes slamming on as the plane touches down, bringing it to a rest about a mile later. Birds, however, can switch from barreling forward at full speed to touching down on a target as narrow as a phone wire. Why can’t an airplane be more like a bird?
Smooth landings A new control system lets a foam glider land on a perch like a parakeet.
MIT researchers have now demonstrated a control system that lets a motorized foam glider land on a perch like a parakeet. The work could help improve the maneuverability of robotic planes, allowing them to recharge their batteries by alighting on power lines.
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Birds can land so precisely because they exploit a physical phenomenon called “stall.” A bird approaching its perch tilts its wings back at a much sharper angle than a landing airplane does. The airflow over the wings becomes turbulent, and the bird loses “lift,” the force that keeps it in the air. Fighter pilots practice stalling their planes in midair and recovering, but it’s too dangerous a maneuver for commercial aircraft, and the physics of stall have been much too complicated for autonomous vehicles to calculate in real time.
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Associate professor Russ Tedrake, a member of the Computer Science and Artificial Intelligence Laboratory, worked with Rick Cory, SM ‘08, PhD ‘10, to develop a mathematical model of a glider in stall. For a range of launch conditions, they used the model to calculate sequences of instructions intended to guide the glider to its perch. But, Cory says, “because the model is not perfect, if you play out that same solution, it completely misses.”
Watch a high-speed video of the researchers’ computer-controlled glider landing on a suspended string perch here.
So Cory and Tedrake also developed a set of error-correction algorithms that nudge the glider back onto its trajectory when location sensors determine that it has deviated from it. Using techniques developed at MIT’s Laboratory for Information and Decision Systems for studying nonlinear systems, they precisely calculated the degree of deviation the controls could compensate for. The addition of the error-correction controls makes for a trajectory that looks like a tube weaving through space. The center of the tube is the trajectory calculated using Cory and Tedrake’s model; the radius of the tube describes the tolerance of the error-correction controls.
The control system ends up being, effectively, a bunch of tubes pressed together like a fistful of straws. If the glider goes so far off course that it leaves one tube, it will still find itself in another. Once the glider is launched, it just keeps checking its position and executing the command that corresponds to the tube in which it finds itself.
