Helicopters and airplanes both fly, but obviously their physical designs dictate they achieve that flight in very different ways. "[A] helicopter is working very hard just to keep itself in the air," explains Nick Roy, head of MIT's Robust Robotics Group, whereas the gliding capabilities of a fixed-wing aircraft enable longer flying times. Yet common sense dictates that if you need an aircraft to navigate a constrictive, dense environment awash with obstacles, you'd opt for a helicopter.
But the eggheads at the Robust Robotics Group aren't interested in yielding to common sense. That's why after winning the last engineering challenge held by the Association for Unmanned Vehicles System International, a sort of obstacle-course competition for autonomous mini-helicopters, RRG decided to up the challenge ante. "The fixed-wing vehicle is a more complicated and interesting problem," says Roy, explaining why they decided, in the absence of any design competition, to see how tight a space they could get an autonomous model airplane to fly within.
The results are stunning. Through a combination of clever aeronautical design, algorithm-writing, active laser scanning and data-crunching computing, the RRG team produced two-meter-wingspan airplane that cand do this, all by itself:
The team did have to cheat it a little bit by giving the plane a map of the environment ahead of time, a luxury they were not allowed in their AUVSI helicopter challenge, but they're keen to remove that particular crutch:
The MIT researchers' next step will be to develop algorithms that can build a map of the plane's environment on the fly. Roy says that the addition of visual information to the rangefinder's measurements and the inertial data could make the problem more tractable. "There are definitely significant challenges to be solved," [Aeronautics and Astronautics graduate student Adam] Bry says. "But I think that it's certainly possible."
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