Autonomous Robot Plane Albe Navigates Around Pillars
Lee Rannals for redOrbit.com – Your Universe Online
MIT researchers have completed a series of flight tests in which an autonomous robotic plane successfully navigates its way among pillars in a parking garage.
For the past two years, MIT’s Robust Robotics Group has been challenging itself to build robotic planes that are able to navigate indoors without the use of GPS.
In 2011, the team developed an algorithm for calculating a plane’s trajectory and presented it at the International Conference on Robotics and Automation. In 2012, the team presented an algorithm for determining its “state,” which included its location, physical orientation, velocity, and acceleration.
The team has now completed a series of test flights in which the robotic plane utilizes their state-estimation to successfully thread its way among the pillars in the garage.
“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, an associate professor of aeronautics and astronautics and head of the Robust Robotics Group, said in a press release. “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 that the problem with the plane is more complicated because it is going faster and is unable to do arbitrary motions.
“They can’t go sideways, they can’t hover, they have a stall speed,” Roy said in the press release.
The team built their own planes from scratch in order to counter this problem, creating a robotic plane that had unusually short and broad wings, allowing it to fly at relatively low speeds and make tight turns.
The researchers initially gave its plane a leg up, providing it with an accurate digital map of its environment. However, despite the advantage, the plane still has to determine where it is on the map by using data from a laser range finder and inertial sensors.
The team used an algorithm developed by AeroAstro professor Emilio Frazzoli’s Aerospace Robotics and Embedded Systems (ARES) Laboratory to help plot the plane’s trajectory. They added a variable to the algorithm to describe the probability that a state estimation was reliable.
Because the autonomous plane navigation is in confined spaces, the team’s work “raises interesting questions which cannot be easily bypassed,” according to Paul Newman, a professor of information engineering at the University of Oxford and leader of Oxford’s Mobile Robotics Group.
“Navigation of lightweight, dynamic vehicles against rough prior 3-D structural maps is hard, important, timely and, I believe, will find exploitation in many, many fields,” he said in a press release. “Not many groups can pull it all together on a single platform.”
The team’s next step is to develop algorithms that can build a map of the plane’s environment on the fly.
Newman said that adding visual information to the rangefinder’s measurements could make the problem more tractable.
“There are definitely significant challenges to be solved,” Adam Bry, a graduate student in the Department of Aeronautics, said in a press release. “But I think that it’s certainly possible.”