But MIT’s Robust Robotics Group — which fielded the team that won the last AUVSI contest — has set itself an even tougher challenge: 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. 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,” 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,” Roy says. “They can’t go sideways, they can’t hover, they have a stall speed.”

Found in Translation

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. “He’s a guy who can design you a complete airplane in 10 minutes,” Bry says. “He probably doesn’t remember that he did it.” 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.

Because 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.

That’s a massive computational challenge, but Bry, Roy and Abraham Bachrach — a grad student in electrical engineering and computer science who’s also in Roy’s group — solved it by combining two different types of state-estimation algorithms. One, called a particle filter, is very accurate but time consuming; the other, called a Kalman filter, is accurate only under certain limiting assumptions, but it’s very efficient. Algorithmically, the trick was to use the particle filter for only those variables that required it and then translate the results back into the language of the Kalman filter.

Confronting Doubt

To plot the plane’s trajectory, Bry and Roy adapted extremely efficient motion-planning algorithms (http://web.mit.edu/newsoffice/2011/smarter-robot-arms-0921.html) developed by AeroAstro professor Emilio Frazzoli’s Aerospace Robotics and Embedded Systems (ARES) Laboratory. The ARES algorithms, however, are designed to work with more reliable state information than a plane in flight can provide, so Bry and Roy had to add an extra variable to describe the probability that a state estimation was reliable, which made the geometry of the problem more complicated.

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.”

But the answers are interesting, too, Newman says. “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 says. “Not many groups can pull it all together on a single platform.”

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,” Bry says. “But I think that it’s certainly possible.”

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“HyTAQ Robot (Hybrid Terrestrial and Aerial Quadrotor)”
“The Spherical Air Vehicle developed by Japan’s Ministry of Defense”

The HyTAQ robot has been developed in the Robotics Lab at Illinois Institute of Technology (IIT), part of the Mechanical, Materials, and Aerospace Engineering Department. It is a novel mobile robot capable of both aerial and terrestrial locomotion. Flight is achieved through a quadrotor configuration; four actuators provide the required thrust. Adding a rolling cage to the quadrotor makes terrestrial locomotion possible using the same actuator set and control system. Thus, neither the mass nor the system complexity is increased by inclusion of separate actuators for terrestrial and aerial locomotion.

During terrestrial locomotion, the robot only needs to overcome rolling resistance and consumes much less energy compared to the aerial mode. This solves one of the most vexing problems of quadrotors and rotorcraft in general — their short operation time. Experimental results show that the hybrid robot can travel a distance 4 times greater and operate almost 6 times longer than a aerial only system. It also solves one of the most challenging problems in terrestrial robot design — obstacle avoidance. When an obstacle is encountered, the system simply flies over it.

A team at the Robotics Lab at the Illinois Institute of Technology (IIT) has come up with another take on the caged flying robots like the spherical air vehicle developed by Japan’s Ministry of Defense (JMD) and the more recent Kyosho Space Ball. However, instead of a spherical shape, the the outer protective cage of the HyTAQ (Hybrid Terrestrial and Aerial Quadrotor) is cylindrical and is attached to the quadrotor via a shaft connected by two rotating joints, thereby providing the HyTAQ with the ability to fly or roll over the ground.

With the quadrotors providing thrust for both aerial and terrestrial locomotion, there’s no requirement for additional actuators that would increase the weight of the system. When on the ground, the rolling cage means the robot only needs to overcome rolling resistance to move forward, and when it encounters an obstacle to difficult to roll over, it can simply take to the air to jump over it.

The developers say the robot’s hybrid nature makes it much more energy efficient than aerial-only systems, with the ability to operate almost six times as long and travel a distance four times greater than such systems. Experiments conducted by the team showed that for aerial-only travel, its battery lasted five minutes and it traveled 1,969 ft (600 m), but rolling over a smooth surface saw its endurance extend to 27 minutes and the distance traveled increase to 7,874 ft (2,400 m).

The cage itself is constructed out of polycarbonate and carbon fiber making it both flexible and strong enough to withstand crashing. The development team has tested the HyTAQ’s ground performance over various types of terrain, including flat indoor surfaces and sand and grass outdoors. The ground locomotion capabilities also allow the robot to move when it’s too windy for flight.

Like its spherical kin, the reconnaissance and search and rescue potential of the camera-equipped robot are obvious and the team is now in the process of patenting the design and hopes to attract commercial interest.

The HyTAQ robot can be seen in action in the following video.

External Links

http://robots.iit.edu/

http://www.gizmag.com/hytaq-rolling-aerial-robot/25220/

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This bionic technology-bearer, which is inspired by the herring gull, can start, fly and land autonomously – with no additional drive mechanism. Its wings not only beat up and down, but also twist at specific angles. This is made possible by an active articulated torsional drive unit, which in combination with a complex control system attains an unprecedented level of efficiency in flight operation. Festo has thus succeeded for the first time in creating an energy-efficient technical adaptation of this model from nature.

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