NYU’s Courant Institute of Mathematical Sciences has received a grant from the U.S. Office of Naval Research to develop a bird-sized, self-flying plane that could navigate through both forests and urban environments. The Courant Institute shares the $4.5 million, 5-year grant with MIT, Carnegie Mellon Univ., and Harvard Univ. Photo: Josh Presseisen.
New York Univ.’s Courant Institute of Mathematical
Sciences has received a grant from the U.S. Office of Naval Research (ONR) to
develop a bird-sized, self-flying plane that could navigate through both forests
and urban environments.
The Courant Institute shares the
$4.5 million, 5-year grant with MIT, Carnegie Mellon Univ. (CMU), and Harvard Univ.
“The plane would be about the
size of a crow, and, like a bird, would use vision to navigate, but it would
use orientable propellers and not flap its wings.” explained Yann LeCun, a
professor at NYU’s Courant Institute.
The work will rely, in part, on a
technology that emulates the visual system of animals called Convolutional
Networks, which mimics the neural network in the mammalian visual cortex and
can be trained to quickly interpret the world around it. The vision system will
run on a new type of computer chip that uses a “dataflow” architecture. Dubbed
NeuFlow, the new chip will enable Convolutional Networks and other computer
perception algorithms to run on very small and lightweight devices hundreds of
times faster than a conventional computer.
“The NeuFlow hardware is a key
element of this project, as it is the only vision architecture that is powerful
enough and compact enough to do the job,” said LeCun, who is collaborating with
Yale Univ. researcher Eugenio Culurciello and
his team on the NeuFlow project.
The ONR grant brings together
seven researchers from diverse fields that include machine learning, computer
vision, planning and control, aerodynamics, computational neuroscience, and the
study of bird flight. Besides LeCun, team members include: J. Andrew Bagnell
(CMU), Andrew Biewener (Harvard), Emilio Frazzoli (MIT), William Freeman (MIT),
Martial Hebert (CMU), David Lentink (Wageningen Univ.), and Russ Tedrake (MIT).
Under a previously awarded
National Science Foundation grant, LeCun and his colleagues at Stanford Univ.,
MIT, and the Univ. of California, Berkeley
are working to develop new computational models of how the visual system learns
to recognize objects. The project’s researchers hope to uncover new mechanisms
that could explain the learning process in neural circuits.