Autonomous Robotic Plane Flies Indoors

Researchers have been working for decades on the most challenging aspect of control algorithms for autonomous helicopters that pilot themselves.

But the team of talented MIT's Robust Robotics Group has modulated themselves for an even tougher 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 the 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.

The MIT researchers have wrapped up with 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," says Nick Roy, an associate professor of aeronautics and astronautics and head of the Robust Robotics Group. "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. With the plane, the problem is more complicated because it's going much faster, and it can't do arbitrary motions. They can't go sideways, they can't hover, and they have a stall speed."

The researchers built their own plane in order to buy a little extra time for their algorithms to execute, and to ensure maneuverability in close quarters.

The study author Adam Bry, a graduate student in the Department of Aeronautics and Astronautics consulted AeroAstro professor Mark Drela about the plane's design. 

This challenge undertaken by the MIT researchers is new area of research they have to deal with problem of autonomous plane navigation in confined spaces that is very difficult; hence the team is initially giving its plane a leg up by providing it with an accurate digital map of its environment.   

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.

Because many of those properties are multidimensional, to determine its state at any moment, the plane has to calculate 15 different values.

Paul Newman, a professor of information engineering at the University of Oxford and leader of Oxford's Mobile Robotics Group, says that because autonomous plane navigation in confined spaces is such a new research area, the MIT team's work is as valuable for the questions it raises as the answers it provides. "Looking beyond the obvious excellence in systems," Newman says, the work "raises interesting questions which cannot be easily bypassed."

The MIT researchers' next step will be to develop algorithms that can build a map of the plane's environment on the fly.