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For those following this saga, version 6.1 of the AutoQuad board is complete and has passed initial testing.  I have taken the 5.0 design and added features that should make it more flexible and expandable while increasing performance.  Here is a summary of specifications:

Hardware:

- 2" x 2.5" main board with MK mounting hole pattern

- Input voltage: 6.5v => 18v

- High efficiency DC/DC converters

- STM32F215 32bit Cortex M3 microcontroller @ 120Mhz (1MB flash)

- Standard Arm 10 pin 0.05" pitch SWD connector

- 14 general purpose PWM controllers / receivers (powered or un-powered)

- Dedicated Spektrum satellite (remote receiver) 2.4Ghz R/C radio connector

- uSD card slot driven by 4bit SDIO capable of 100Mb/s transfer (up to 32GB storage)

- optional onboard uBlox LEA-XX GPS module with battery backup and timepulse capture

- optional u.FL active GPS antenna connector

- optional external GPS via standard 6 pin connector (EM406, EM401, uBlox, MTK)

- optional external bi-directional telemetry radio via standard 6 pin FTDI connector - powered up to 1A

- I2C bus connector for I2C ESC's (or other I2C devices)

- onboard IMU options:

+ optional 9 DOF analog sensors (3x RATE, 3x ACC, 3x MAG) w/EMI hardening

+ optional VectorNav VN100

- daughter board options:

+ 9 DOF analog sensor board

+ VectorNav VN100

+ High performance SOM (Sytem on Module)

+ Any combination of the above

- Two barometric pressure sensors

- Battery voltage monitor

Software:

- Fully threaded RTOS design written in C -  75% idle in flight

- All (15) analog sensors read up to a rate of 276.8KHz (~4.2M sps total)

- 100Hz => 800Hz PWM motor update rate (requires custom ESC's at rates >450Hz)

- 200Hz attitude, 3D velocity / position solutions

- Full downlink telemetry

- Detailed system state dumps @200Hz => uSD card w/FAT32 FS

- Quaternion based attitude filter additionally producing rotation matrix and Euler angle outputs

- All math in single precision floating point

- Temperature compensated and calibrated sensor suite

- Custom ground station software w/bi-directional command and control API

- MavLink protocol support

- Cascading PID control system, velocity based for smooth transitions

- Auto land / takeoff

- Hover position / altitude hold

- Autonomous waypoint mission navigation

- Precise altitude hold indoors

What I call the general purpose PWM controllers are 14 connectors which can be used for PWM (or any other digital) signaling.  Each one can be optionally unpowered or powered with 5.0v or 6.5v (depending on the RECOM part used.)  Since each port is connected to a dedicated timer line on the uController they can be used for input or output. This means you can have any combination of motors / servos / acoustic range finders / LED's, etc. that you can image with power up to ~1.2A.  With the input capture capability, you could also use them to connect a traditional multi-channel R/C receiver.

I have included two pressure sensors (2nd one optional) so that fixed wing users can monitor airspeed.  Or, you could use one as a failover or combine the two to get smoother altitude measurements.

There is a lot of flexibility when it comes to the IMU.  First there is the option of using the onboard analog sensors:

+ 3 axis acc (ADXL335)

+ 3 axis mag (HMC6042 & HMC1041Z)

+ 3 axis gyro (IDG500 & ISZ500)

+ 3 temperature sensors

These must be calibrated by the user which can take a lot of time and aggravation. For the person who would rather pay someone to handle this calibration for them, a VectorNav VN100 can be soldered directly to the main board and used as an IMU.

With the 2x20 pin connectors a daughter board can be connected which can accommodate an analog or digital IMU as well.  In fact, you could have combinations of onboard and external IMUs used simultaneously for failover or co-witness configurations.  Since these connectors contain many analog and multiple high speed digital communications channels, a SoM can be connected such as a GumStix Overo with a 720Mhz Arm Coretex A8 processor with Vector Floating Point hardware running Linux with gobs of RAM and flash storage and optional bluetooth and WiFi radios.  This will allow easy experimentation with complex navigation filtering and the exploration of vision based navigation algorithms.

Here is a picture of an external VN100 attached as a second IMU:

I have received a lot of positive feedback on my past designs as well as a lot of requests for hardware that I could not fulfill so I have decided to try to find ways to make this board available to those who want to build a machine around it.  I can't say exactly when, but I hope to be able to announce hardware availability through various sources in the not too distant future.

I have been blogging for some time on a tumblr blog called microdrones 2.0 .

Up until now I have been collecting articles and videos of advanced microdrones features.

Soon we will start to discuss what will be the next generation of microdrones, and what

features these next generation microdrones will include.

I opened this blog because for some time I feel that all the microdrone available today

have more or less the same features, and I think that it is time to take microdrones to

the next level.

So, you're all invited to visit, comment and participate at:

http://microdrones.tumblr.com

I made a program that shows log data in visual way. I can see plane position, altitude, elevator, ailerons etc.

Here are some screenshots from program:

My plane made strange curves during flight. All curves are in the same places. After a very careful check I found an error in APM navigation code. It is now corrected in version 2.21 (In downloads section there is still the version 2.20, and there is the error.) Issue 376

First flight attempts can be quite curvy. Probably Nav_Roll P value is too big?

 
It seems that I must make also Nav_Pitch_Alt_Pid smaller... ?

GPS altitude (violet line) is rather slow? Air pressure altitude is probably quite ok.

 
Sometimes GPS altitude jumps quickly. In the last column are the values, and there is sudden 70 meters jump.


You can download this program from the address

http://sites.google.com/site/alpohassinen/logbrowser/APMLogBrowserSetup.zip

Normally only part of the flight data is saved to log. I have changed settings so that also CTUN and NTUN are saved. This is done easily in APM Planner and there in Configuration: I changed LOG_BITMASK to 382.

 
PS. It was impossible to analyze flight data in the field with laptop, touchpad and very poor internet connetions. I made this program with quick and dirty method, so there may be errors.
PPS. NO, I will not make modifications or corrections to this program, but please ask Michael Oborne to make similar system to APM Planner... :-)

Another one from Hack-a-day. It's just a concept so far, but the team that's behind it may be competent enough to pull it off. They're using a Kickstarter-like model to raise funds to make it. $670 buys you a pre-order if the project is funded.

an Open Source Remote Control transmitter. This is one of the most impressive looking RC transmitters we’ve ever seen. The OSRC could be great for a small UAV – just get the GPS position from the aircraft and map it with the transmitter’s screen. There’s also support for a video downlink so flying around New York City is possible with a single device.

 

The transmitter/receiver combo are more actually referred to as transceivers. According to [Demetris], the radios on both the ‘ground side’ and ‘vehicle side’ can talk to each other on a 115 kbps data link on the 2.4GHz band. Sending commands and getting telemetry to something we’ve seen before, but never in a single integrated package. The expected range is in the neighborhood of 10 – 40 km.  The ground unit is based on a Gumstix board and has a 4.8 inch display. This really isn’t so much an RC transmitter but a computer that happens to control RC airplanes.

[Demetris] has had some success doing some professional development with Gumstix boards, so it looks like he has the skills to build a very nice R/C controller.

From Hack-a-day. This ducted-fan beast uses the Sparkfun 6DoF IMU that Jordi wrote the software for. No, it hasn't flown yet.

Behold the Land-Bear-Shark, a quadcopter on a rather grand scale. At a full eight kilograms it’s an easy target to compare the [Howard Hughes] behemoth, but in addition to the weight, this still has yet to make its first flight.

To give you some scale to the image above, the board at the center is an Arduino. It controls the beast, along with the help of a SparkFun IMU board which rides atop. Really, if any quadcopter of this size has a chance of working, this should be the one. The construction is beautiful, making use of carbon fiber rod along with 3D-printed connectors to assemble the frame. A lot of thought has gone into small things like conserving weight used on the landing gear, which are incorporated into the bottom corner brackets. The batteries are connected in a manner that makes them easy to adjust, acting as ballast for balancing the craft.

From Makezine:

The Parrot.AR drone is manifold awesome. And on top of it all, the December Parrot.AR drone teardown on iFixIt saw one of the highest repairability scores that our pals over there have ever awarded. They cite the Parrot.AR’s repair-friendly design, the use of easily demountable fasteners, connectors, and subassemblies, and great repair support from Parrot itself, including readily available replacement parts and a series of how-to-fix it videos on the Parrot.AR site. And while a certain amount of repair-friendly design is just common sense in any R/C aircraft, common sense is not always so common, and even in the R/C market Parrot’s repairability still goes above and beyond the norm.

So congratulations, Parrot! Welcome to the running for the 2011 Makeys.

I am an ex-USAF Avionics Sensors guy, and I have always wanted a gyro stabilized laser targeting system. Now that I am all grown up, I'll settle for a gyro stabilized camera.

A little looking, and I found some nice UAV equipment.It's a little out of my price range at $10,000 for the day system and $20,000 for the FLIR system. http://store.micropilot.com/category-s/21.htm

Now I know this is mechanically and electrically easy, but for me this could become time-consuming. Can we make a cost-effective system for our UAVs?

Some examples:

https://www.youtube.com/watch?v=ewK7NkcCFCk

https://www.youtube.com/watch?v=m5fluZ7mUoY

What do you guys think?

The X-Gyro 500 is a simple single axis head tracking system that can be used to track head movement to for controlling an on board camera in an FPV system. Since today it is available from Hobbyking for US$ 37.44 

Specifications:
Voltage: 8~12v
Weight: 20g
Range: +/- 90degree

Compatible Transmitters:
FUTABA: (FF-7, FF-8, FF-9, T9Z, T12MZ, T14MZ)
Graupner: (MC20, MC24, MX22)
Multiplex transmitter: (Royal Evo, Cockpit SX, mc4000)
JR and other transmitters without programmable channel: (9303, 9X)

The user manual can be downloaded here

Link to product page: http://hobbyking.com/hobbyking/store/uh_viewItem.asp?idProduct=14628&aff=5361

Hello Guys,
public a little video of backstage, just to give you an idea of the potential of platform ...
The video board is so original as they are recorded by the camera are not post processed,I consider the quality pretty good the light in the environment was poor.
The configuration of Heaxfox32 was:
Multipilot32
FULL VRIMU
6 Engine 2212 with regulators 30A
Stabilized Gimbal Pitch and Roll of
5.4 GHz Video TX
HD onboard camera SD90
Full Carbon Frame by Bercelli Labs

Firmware : Custom revision of ArdupiratesNG32 that implement Mixertable.

Leave your comments :)
A greeting and the next video.

Best

Roberto

Original Blog Post: http://www.virtualrobotix.com/profiles/blogs/hexafox32-backstage-in-a-itali

FINAL RUNS BEING WEBCAST THIS AFTERNOON

AUVSI Foundation and ONR's 14th International RoboSub Competition
July 12-17, 2011
SSC Pacific TRANSDEC, San Diego, CA

Co-sponsored by the U.S. Office of Naval Research (ONR), the goal of this competition is to advance the development of Autonomous Underwater Vehicles (AUVs) by challenging a new generation of engineers to perform realistic missions in an underwater environment. This event also serves to foster ties between young engineers and the organizations developing AUV technologies. View photos from RoboSub 2011.  

Teams that have qualified for TODAY's finals:  Cornell, University of Florida, ETS Team SONIA, University of Rhode Island, University of Maryland, U.S. Naval Academy, NC State and Reykjavik University. CONGRATS and GOOD LUCK!!!

Click here for spectator information including event hours, directions, parking instructions, etc.

View the 2011 Final Rules and Mission

Can't attend RoboSub 2011? Then don't miss our live webcast of the finals on Sunday, July 17th from 1:00-5:00pm PST on www.robosub.org.

friends,

has anyone seen this?... http://www.hobbyking.com/hobbyking/store/__17141__HobbyKing_G_OSD_On_Screen_Display_with_GPS.html

a very small osd at $36 with the gps module included... it was on backorder since some time but i managed to grab one... :) anxiously waiting for my parcel to come...

Hi everyone !!

Here is my Y6 (90 degree branch) !!! can fly in the wind with default parameters !!!

I can put photos of build details ! Thanks

flight in paris at 2 PM, cité universitaire.

Although I have been here for years, this is my first blog post and I would like to present yet another attitude estimator which I have been working in my M.Sc. Thesis. A friend of mine and me have developed an autopilot, but this is for another post. However you can find details about it in the thesis at the end of the post. For our tests we are using a Mentor from Multiplex, shown in the next figure.

The AHRS is based on an Unscented Kalman Filter, which has better performance than the classical Extended Kalman Filter for non-linear systems, such as the kinematic equation for attitude.
This algorithm is based on three axis magnetometers, three axis accelerometers and three axis gyroscopes, so it can estimates the yaw angle at low/none velocity without the GPS aid. As other filters, it uses the accelerometers and magnetometers to estimate and neutralize the biases of the gyroscopes, which estimate the attitude angles in quaternion form. The difference with other algorithms is that the measurements from the accelerometers and/or magnetometers are not put directly in the filter, but they are indirectly put through an algorithm called Fast Optimal Attitude Matrix (FOAM) as it is shown in the next figure (sorry for the Spanish).

FOAM builds the Direct Cosine Matrix (DCM) from the accelerometers and magnetometers readings allowing to weight the sensors, thus in critical stages such as take-off or "aerobatics", we can rely more in magnetometers readings than in accelerometers for correcting the gyroscope's integration in an autonomous way.

I have validated the algorithm using GPS readings for the yaw angle, despite the cross-wing during a turn (10-20secs, the wind speed was around 15m/s this day as you can guess from the video) the yaw and heading angle are closer. The roll angle was validated with a camera on board in the same experiment. The details of the vision algorithm, shown in the video, can be found in the thesis. In simulation (using X-Plane or mathematical model in Simulink), comparing with true values, the error is less than 1º in pitch and roll and 4º in yaw once the filter has converged.

Mentor allows me for automatic taking-off with a robust landing gear. It is nice to see how the AHRS works very well in presence of many vibrations during this stage. Look at the next figures how the trust in accelometers (red line) downs during the take-off moment and rises again when the flight is going to steady, not disturbing the pitch correction in any moment. As well, the algorithm converges very fast to true values (6º of pitch at the moment of take-off).

You can download the master thesis (in Spanish), detailing the algorithm and the hardware/software here: http://dl.dropbox.com/u/2689187/tesina_Hector.pdf

The next article is a resume (in English) of the related algorithm using TRIAD (a simplified version of FOAM). It will be published in the special issue about Kalman Filter Issues in Transactions on Industrial Electronics Journal within next two months, so if you want to cite it, you have to search it there: http://dl.dropbox.com/u/2689187/article_TIE.pdf

Here is a nice resume of several algorithms to estimate the DCM, it includes TRIAD and FOAM among other ones:

http://dl.dropbox.com/u/2689187/dcm_estimation.pdf

If you have questions, fell free to ask :P

http://www.eodevices.com/main_erc_2kit_frameset.htm

Electro-Optical devices sells kits and spare parts to build a real, far-ranged LIDAR ranger, such as: nanosecond timer, transmitter module (high voltage laser power supply included on-board), receiver module (APD photodiode, PIN photodiode), controller, laser diodes (power 10W - 75W).

The price of the cheapest kit ERC2-KIT is $ 429 , but you can get even cheaper if you buy just the modules and assemble it yourself.

The boards are really small and are thus ideally suited to fit an UAV plane which includes a rotating mirror system and a capable memory onboard.  

Maybe there are some restricting laws about the power of the laser? Anyone knows?