Washington, A team of researchers has set itself the tough challenge of developing autonomous-control algorithms for the indoor flight of GPS-denied airplanes.
At the 2011 International Conference on Robotics and Automation (ICRA), a team of researchers from MIT’s Robust Robotics Group described an algorithm for calculating a plane’s trajectory.
in 2012, at the same conference, they presented an algorithm for determining its “state” — its location, physical orientation, velocity and acceleration.
Now, the MIT researchers have completed a series of flight tests in which an autonomous robotic plane running their state-estimation algorithm successfully threaded its way among pillars in the parking garage under MIT’s Stata Center.
“The reason that we switched from the helicopter to the fixed-wing vehicle is that the fixed-wing vehicle is a more complicated and interesting problem, but also that it has a much longer flight time,” Nick Roy, head of the Robust Robotics Group, said.
“The helicopter is working very hard just to keep itself in the air, and we wanted to be able to fly longer distances for longer periods of time,” he said.
With the plane, the problem is more complicated because “it’s going much faster, and it can’t do arbitrary motions,” Roy says.
“They can’t go sideways, they can’t hover, they have a stall speed,” he said.
To buy a little extra time for their algorithms to execute, and to ensure maneuverability in close quarters, the MIT researchers built their own plane from scratch.
Adam Bry, a graduate student in the Department of Aeronautics and Astronautics (AeroAstro) and lead author on both ICRA papers, consulted with AeroAstro professor Mark Drela about the plane’s design.
The plane that resulted has unusually short and broad wings, which allow it to fly at relatively low speeds and make tight turns but still afford it the cargo capacity to carry the electronics that run the researchers’ algorithms.
Since the problem of autonomous plane navigation in confined spaces is so difficult, and because it’s such a new area of research, the MIT team is initially giving its plane a leg up by providing it with an accurate digital map of its environment.
That’s something that the helicopters in the AUVSI challenges don’t have: They have to build a map as they go.
But the plane still has to determine where it is on the map in real time, using data from a laser rangefinder and inertial sensors — accelerometers and gyroscopes — that it carries on board.
It also has to deduce its orientation — how much it’s tilted in any direction — its velocity, and its acceleration. Because many of those properties are multidimensional, to determine its state at any moment, the plane has to calculate 15 different values.