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hudson is currently certified at Master level.
Name: Trammell Hudson
Homepage: http://www.swcp.com/~hudson/ Notes: I'm building an automatic flight control system (autopilot) for model helicopters. So far we have designed a three-axis, six degree of freedom IMU board that has two dual axis rate gyros, two dual axis accelerometers and extra features for realtime control of the helicopter. Everything about it is GPLed and available from: http://autopilot.sourceforge.net/ We hope to have the PID control loops tuned and the rotorcraft hovering under its own control within a few months. Then the autonomous navigation and strategic software design can begin. Projects
Articles Posted by hudson
Recent blog entries by hudsonSyndication: RSS 2.0
I've posted a
high
res (5.9 MB) and low
res (1.9 MB) QuickTime of the tuning process on our
Bergen
Observer. We ran out of time to fully smooth out all
the oscillations and enable the collective control due to a
tropical storm that moved in over Charleston, SC.
On the Nova we have position tuned to +/- 30 cm and altitude tuned to +/- 20 cm. The Observer is a bit more "pitchy", which is causing it to drift forwards and backwards. I'm hoping to get the CCPM code working with the JetCat mechanics soon and try tuning it on a turbine.
The onboard systems hovered Dennis' Nova helicopter for
entire tanks of fuel yesterday! We closed all the control
loops except altitude, so the throttle/collective were still
under manual control. Despite a 20 degree magnetometer
error, the flight controller managed to keep the helicopter
within 1 m CEP during calm winds and 2 m CEP during gusts.
Onboard the Nova was our IMU / Servo controller, our three axis mangetometer, a Cerfboard with 802.11 CF, and our new u-blox TIM-LP / IO board.
We'll have movies and plots of the sensor data (plus overhead maps) available from autopilot.sourceforge.net. And Rotomotion will be selling IMU / INS kits and turnkey UAV systems based on the designs, too.
Fast on the heels of my
1-D
Kalman Filter for tracking gyro bias and determining
tilt angle in a balancing robot, I've checked in code for an
entire GPS aided inertial navigation system. You can see
the full source code for the 17 state Kalman filter in
gpsins.cpp
andgpsins.h.
This filter uses the 3 axis, 6 dof IMU from Rotomotion, a three axis magnetometer from PNI and a u-blox TIM-LP GPS. It computes position in a local tangent frame for ease of use with the flight controller and tracks both gyro and accelerometer biases. We all know about the gyro drift problems, but the ADXL units also have a slight amount of temperature drift that can be tracked by the filter.
I'm still doing static testing on the software and hardware. Hopefully within a few weeks I'll be able to flight test it on my helicopter. As far as I know, this is the only Free Software GPS aided INS in existance.
For folks building balacing robots like Dave Anderson's
marvelous
nBot
or Larry Barello's
gyrobot,
I've written an extensively commented Kalman
Filter that uses a dual axis accelerometer and a single
axis angular rate gyro to accurately determine tilt angle,
angular rate and gyro bias. The filter is able to be tuned
for different amounts of noise in the sensors and to place
varying trust in the different sensors. It also
automatically tracks the gyro bias by comparing the
covariance of the state estimate with the state measurement.
The full source code is in tilt.c and tilt.h. It is available under the GPL for your use and education.
I've just added Futaba and JR high-speed digital servo
support to my autopilot control board. The Futaba servos
use 275 Hz refresh rate, while the JR units use a 166 Hz
rate. The data pulse is the same, between 1 and 2 ms long.
This is a hardware upgrade that requires the new
Rev
2.4 boards.
I also wrote a page that details the Futaba PCM format. We'll have a software-only upgrade to support PCM transmitters / receivers soon. hudson certified others as follows:
Others have certified hudson as follows:
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