Older blog entries for hudson (starting at number 31)

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.

PCM decoding is working! I've managed to reverse engineer most of the protocol used by Futaba PCM1024 equipment and am now tackling the checksum and failsafe features. My code is able to accurately determine six of the nine channels fairly reliably, although some timing issues still remain.

Speaking of which, why can't they just use a regular serial protocol? There is a full MCU inside the PCM receivers, so it would be possible to include more useful features like start and stop bits, Manchester waves, sync points and such. Tracking an unknown 150 usecond bit clock over 30 ms is just asking for jitter and skew.

Full code is available from the CVS tree; a more details writeup will be posted on http://autopilot.sourceforge.net/ soon.

I've redesigned my controller boards to be more modular and fit in less space. Several folks wanted the inertial sensors to be separate from the microcontroller and servo interface, so I've put them on their own boards. You can see the preliminary files and images, although some changes do need to be made.

I have also been hard at work decoding the Futaba PCM radio protocol. It is far more complex than the PWM pulse train that is PPM and will require a software uart to decode. The important bits are that it uses a 150 usecond bit clock, a 2.7 msec sync pulse and two 120 bit frames.

These frames are then transmitted inverted, including the sync pulses. I suppose if there are any errors the frame is to be discarded. You can see this clearly in an image of the PCM frames. Each raster line is the four frames. The source code for generating this is in plotpcm, which uses the output of the microcontroller running onboard/rev2/pcm.c.

I've spent last night and this morning hacking on my Kalman filter code to process inertial measurements from my board's gyros and accelerometers.

We had several successful autonomous flights running the filter on my Linux iPAQ. I optimized the C++ AHRS code to produce a lean, fast version that will run on an 8 bit microcontroller. Right now it can sample the sensors at 60 Hz and produces an attitude estimate every 20 Hz. That should be good enough for jerky autonomous flight.

I'm amazed at how much extra speed there was to wring out of the code. The iPAQ has a 206 Mhz StrongARM SA-1110, while the 2.2 board has an 8 Mhz ATmega163, yet the speed difference between the C++ code and the C code is only a factor of five. Wowza! I guess the very clean templated Matrix math code is easier to read and write, but sure does add some speed penalties.

There is an banner ad encouraging me to try the ISOPOD. 40 MIPS is five times faster than the 8 MIPS I have now; it might be worth a try...

IT ACTUALLY WORKS! This weekend, Aaron Kahn and I flew the Rev 2.2 board on my Concept 60 helicopter. Unlike the past few weekends of sensor calibration and data collection, we turned on the autopilot software and it actually flew the helicopter.

The first day we spent tuning the control loops to remove oscillation in the pitch axis and slowly expanded the control authority that the software had. We destroyed a CF 802.11 card due to vibration and had to stop for the day. But it flew!

The second day we came back with new software that I wrote the night before. This allowed Aaron to give attitude commands to the autopilot rather than flight commands to the servos. The standard helicopter is flown by directly commanding the cyclic and collective (and throttle and anti-torque and ...). If you hold forward cyclic, the helicopter will nose over and do a loop or two before crashing.

With our software and hardware, he was able to instead provide attitude commands with his joystick. If he holds the stick full forward, it instead commanded the software to maintain 8 degrees nose down. If he released the stick, it would level out. Suddenly, it became a very flyable aircraft, rather than an unimaginable nightmare to fly.

Next weekend we'll have the compass and GPS hooked up, which should provide even better control. The GPS aided INS won't be running, but we will have a working heading hold.

I've curated flight data from Sunday and we have movies, too:

The Rev 2.2 IMU boards are being assembled by lots of folks and many of them have reported successful assemblies. I'm glad to hear that everyone has had such good luck so far.

Aaron Kahn wrote a six state Kalman filter AHRS that tracks gyro bias. We've found that the Toking CG-16D gyros have significant drift and temperature sensitivity, so this extra state is required. Full source code is available in sim/src/imu-filter/ahrs.cpp.

The code works great and tracked twelve hours of data with no problems. It runs at 62 KHz on my P4 and 70 Hz on my iPAQ. We'll be running with the iPAQ on the helicopter, so this is fast enough for realtime sensing. There is no FPU in the SA1110, so it is an enormous difference in speed between it and a desktop CPU.

Aaron Kahn and I did flight testing of our Rev 2.2 control boards over the weekend. I've performed post flight analysis of the flight data that recorded and posted the curated data. You can see the calibration run, the initial starting and liftoff, several pirouettes and sensor tuning steps, and an autorotation following fuel exhaustion. We damaged part of the accelerometer on due to a somewhat sudden stop. You can see the acceleration spike in the last graph.

I was able to snap a great many pictures of the helicopter in flight, and the best one of all is available as 1024x768 wallpaper image. Let me know if you like it!

We finally put together a group order of our control boards and the parts have started to arrive in bulk at my apartment. I've put together assembly instructions to show the other users how to solder the parts together and test them.

These boards are " feature packed " -- twenty 16-bit servo controllers, an LCD interface, a PPM decoder, three axis rate gyros, two axis accelerometers, three extra analog inputs, an NMEA GPS interface, an engine tachometer, a video overlay interface and a serial port. And, Pong! We had a few kb in the flash left over, so I wrote a pong game that is played with the PPM decoder and displays on the video overlay.

I have a few extra kits, if anyone is interested for US$120 + shipping. Here is the list of included parts list and a clarification.

802.11 had some range issues that need to be worked out for controlling the helicopter, so we're back to using the "traditional" interface. However, I have hacked my Hitec RCD3500 to output its PPM signal on a servo port and can now process it with our onboard systems. Here is an image of the jumper soldered on the receiver.

This means that the 802.11 can be used for data logging, while actual control will flow over the FM PPM stream. We can also use the switches on the transmitter to toggle between different modes of augmented flight control.

As I mentioned earlier, I've written some details on decoding the PPM stream and some source code for the AVR ATmega163.

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