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Micro air vehicles
capable of operating
in constrained environments
without the use
of an external
motion capture system
are typically limited to
slow and conservative flight.
As a consequence, almost
all of this research
is done with rotorcraft
in the hover regime.
In the robust robotics
group in CSAIL at MIT,
we've developed a
fixed-wing vehicle
capable of flying at high
speeds through obstacles
using only onboard sensors.
The vehicle is equipped
with an inertial measurement
unit and a laser range scanner.
All the computation for
state estimation and control
is done onboard
using an Intel Atom
processor, similar to what
is found in a commercially
available netbook.
We designed a custom
airplane to carry the sensing
and computation payload while
still being able to maneuver
in confined spaces.
Our platform has
a 2-meter wingspan
and weighs approximately
2 kilograms.
At any given time
the laser can only
see a two-dimensional
picture of the environment.
Laser scans are depicted
with yellow points
representing obstacles, and
blue representing free space.
Even with a pre-computed
map, individual 2D scans
don't contain enough information
to uniquely determine
the 3D position, velocity, and
orientation of the vehicle.
To overcome this difficulty,
we aggregate successive scans
and combine laser information
with the inertial measurement
unit to perform
state estimation.
Another technical
challenge is efficiently
generating trajectories
for the vehicle to follow.
The complicated
vehicle dynamics create
substantial computational
difficulties
in determining a path
to fly from point A
to point B. To overcome
this difficulty,
we use an approximate
dynamics model
that makes it easy to map the
control inputs-- elevator,
rudder, aileron, and
throttle-- to corresponding XYZ
trajectories.
We start by connecting a
set of high-level waypoints
with line and arc segments.
We then use our
approximate model
to construct dynamically
feasible paths
by parameterizing an offset
from this underlying trajectory.
Here we demonstrate the
accuracy and reliability
of this system flying
through a parking garage.
In places, the parking garage
is less than 2.5 meters
from floor to ceiling, creating
extremely tight tolerances
for our 2-meter vehicle.
Our algorithms
allowed the vehicle
to complete a 7-minute flight
through the environment
traveling at over 10 meters per
second, or 22 miles per hour,
covering almost 3
miles of distance
and repeatedly coming within a
few centimeters of obstacles.
