Autonomous Robotic Plane Use New Algorithms for Indoor Navigation

MIT’s Robust Robotics Group has formulated autonomous-control algorithms for maneuvering indoor flight of GPS-denied airplanes.

The group’s research team demonstrated an algorithm for determining the plane’s trajectory during the 2011 International Conference on Robotics and Automation (ICRA). This year an algorithm for calculating its “state” - acceleration, location, velocity, and physical orientation has been presented. A series of flight tests have been accomplished by the MIT researchers, wherein a state-estimation algorithm- based autonomous robotic plane safely moved across the parking garage under MIT’s Stata Center without hitting the pillars.

The plane’s short and broad wings were built by MIT researchers. It can make tight turns and fly at low speed. The team at MIT are creating a precise digital map for mapping the plane’s environment. Based on data from a laser rangefinder and inertial sensors, the plane can determine its location on map in real time, calculating 15 different values.

Challenges with computational algorithm can be met by integrating two different types (particle filter and Kalman filter) of state-estimation algorithms. The particle filter has to be used for variables requiring, followed by translating the results again into the language of the Kalman filter.

For plotting the plane’s trajectory, ARES efficient motion-planning algorithms were used. An extra variable complemented the ARES algorithms for determining the probability concerning reliability of state estimation.

The MIT researchers will continue to formulate algorithms for constructing a map of the plane’s environment aboard.

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