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A team of researchers from the Massachusetts Institute of Technology (MIT) has recently demonstrated an innovative landing control system that allows planes to land similarly to birds. Since this method allows quick changes of speed and fast landings, it might improve future aircraft...



From The Future of Things: "Airplanes’ landing procedure is common knowledge. First, the plane maneuvers slowly into an approach pattern; then, there is the long descent, and finally, the wheels touch the ground and the pilot applies the brakes until the plane comes to a full stop. In comparison, birds switch from barreling forward at full speed to lightly touching down on a target as narrow as a telephone wire. Now, a team of scientists tried to understand this difference in order to improve landing technique for airplanes.

According to this recent study, birds’ ability to land precisely depends on a complicated physical phenomenon called "stall." In fluid dynamics, a stall is a reduction in the lift coefficient generated by an airfoil as angle of attack increases. This occurs when the critical angle of attack of the airfoil is exceeded; typically, about 15 degrees, but it may vary.

When a commercial airplane is changing altitude or banking, its wings are never more than a few degrees away from level. Within that narrow range of angles, the airflow over the plane's wings is smooth and regular, like the flow of water around a small, smooth stone in a creek bed. However, when a bird approaches its perch it will tilt its wings back at a much sharper angle; it makes the airflow over the wings turbulent, and it creates large vortices — whirlwinds — from behind the wings. The effects of the vortices are hard to predict; for instance, if a plane tilts its wings back too far, it can stall and fall out of the sky (hence its name).

The newly designed control system is based on mathematics, and developed by MIT associate professor Russ Tedrake, a member of the Computer Science and Artificial Intelligence Laboratory, and Rick Cory, a PhD student in Tedrake's. Their challenge was to describe the stall phenomenon mathematically; although most engineers understand it, modeling it is time-consuming, in terms of computation.

The developed model enabled Professor Tedrake and Cory to guide a foam glider to its perch, but executing a fluid landing was not that simple "It gets this nominal trajectory," Cory explains. "It says, 'If this is a perfect model, this is how it should fly.' But, because the model is not perfect, if you play out that same solution, it completely misses."

The imperfections of the initial model drove Cory and Tedrake to develop a set of error-correction controls that could nudge the glider back onto its trajectory when location sensors determined that it had deviated from it. By using innovative techniques developed at MIT's Laboratory for Information and Decision Systems, they were able to calculate precisely the degree of deviation that the controls could compensate for.

The control system ends up being a bunch of tubes pressed together like a fistful of straws. The addition of the error-correction controls make the trajectory look like a tube snaking through space; the center of the tube is the trajectory calculated using Cory and Tedrake's model, and the radius of the tube describes the tolerance of the error-correction controls. Once the glider launches, it just keeps checking its position and executing the command that corresponds to the tube in which it finds itself. The ultimate solution found allows the glider to constantly be in one of the possible courses; if it goes so far off course that it leaves one tube, it will still find itself in another.

A cruising plane tries to minimize its drag coefficient—the measure of air resistance against a body in flight. Usually, when an aircraft is trying to slow down, it tilts its wings back in order to increase drag. Ordinarily, they cannot tilt back too far, for fear of stall. However, because Cory and Tedrake's control system takes advantage of stall, the glider has a drag coefficient that is four to five times that of other aerial vehicles

There are several potential applications for the new system. For one, the U.S. Air Force has been interested in the possibility of unmanned aerial vehicles (UAVs) that could land in confined spaces; therefore, it has been funding and monitoring Tedrake and Cory’s research. "What Russ and Rick and their team is doing is unique; I don't think anyone else is addressing the flight control problem in nearly as much detail," says Gregory Reich of the Air Force Research Laboratory. More accolades come from Boeing, who gave Cory the 2010 Engineering Student of the Year Award for the system’s development.

Still, current design interferes with the military’s plans: In the conducted experiments Cory and Tedrake used data from wall-mounted cameras to gauge the glider's position, and the control algorithms ran on a computer on the ground that transmitted instructions to the glider. "The computational power that you may have on board a vehicle of this size is really, really limited," Reich says.

Despite the drawbacks mentioned Tedrake is optimistic, saying that in a few years’ time computer processors will be powerful enough to handle the control algorithms. In the meantime, his lab has already begun to address the problem of moving the glider's location sensors onboard. On a humorous note, Cory concludes: "I visited the Air Force, and I visited Disney, and they actually have a lot in common: the Air Force wants an airplane that can land on a power line, and Disney wants a flying Tinker Bell that can land on a lantern."

TFOT has also covered CyberQuad, a UAV capable of vertical take-off and landing, and Deep Throttling, a technology developed by NASA to make smoother landings.

For more information about the technology that allows planes to land like birds, see MIT’s press release."
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PIXHAWK pxIMU available! Hardware and Firmware

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We proudly announce the launch of the pxIMU Autopilot! The boards, which are priced at 400 chf (about $420) each, will only be made in batches of at least 30, so when we get that many orders we'll put them into production. We have also released the pxIMU Autopilot Firmware.

You can register to the PIXHAWK user forums to hook up to other users, use the forums and help to push this open-source project.


Please note that PIXHAWK is currently evolving from a research system to a open-source community platform. We offer you the best combination of weight (8g), high-performance processing and sensor precision of any current open-source IMU. But you should be experienced enough or ready to learn to handle and to program the device. Our system is targeted at high-end hobbyists and research use. Of course the whole project is well-documented in our wiki, so it will be convenient to work with. Look for example at the excellent wiki articles onpxIMU, flashing the firmware or the Intel CORE 2 DUO baseboard for MAVs. We expect this user wiki to improve even further as more and more users are joining in. If you just want to get started and are looking for a very affordable system, we recommend to look at the projects on DIYDrones as well.

The pxIMU code is available at the PIXHAWK downloads page. You can browse it online or download a ZIP file.

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Simulation_UBLOX.gif

As a fan of inexpensive GPS units I've always been interested in keeping NMEA GPS's compatible with ArduPilot and ArduIMU. So last night and today, while I was incorporating Remzibi's OSD code into the AP2.7.1 source I did some testing with my new GPS Emulator navigation logic. During this test, I had problems with the plane waffling back and forth around 0 degrees (due north). I have seen this before during testing with AP2.6 and my old Emulator. For a while, I attributed this to an error in my program and spent a good 2 hours searching for the cause. Finally, I tried the same exact test using uBlox for my GPS_PROTOCOL... and what do you know? It worked like a dream!?!? So I went back to NMEA and upped the Hz. I tried everything from 5-30Hz and nothing made it any better.

Any time the plane approached or passed 0 degrees the AP would tell my emulator to turn hard left, then hard right, then hard left and sometimes would get stuck in this cycle (not the sine wave I posted yesterday) but a very tight sine wave only varying about 10 to 40 degrees before snapping back hard the other direction.

Finally, I started looking at the NMEA parsing code in the AP source. It turns out, there are 2 atoi() function calls for ground_speed and ground_course in the GPRMC parsing routine. Simply changing atoi to atof completely solves the problem. I assume it's a rounding issue and since the GPS sends one decimal place after the degrees, this decimal place was getting rounded to an integer and then multiplied by 100. I believe this bug has been there since the very beginning when the NMEA parsing routine was first written. I wouldn't have guessed that one decimal point would make such a difference!



Simulation_NMEA_NoFix.gif

Simulation_NMEA_Fix.gif
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I'm having fun today incorporating my changes to the uBlox, NMEA and EM406 code to better manage the blue blinking light as well as the output for Remzibi's OSD in the AP 2.7.1 code. I re-wrote the trajectory function in my Emulator because there was a bit of an offset in my old code. Here's what I'm finding with the new code

Simulation_SineWaves.gif

Does anyone know what changes I need to make to the gain settings (or something like that) to cut down on this pattern?

Thanks!!!

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After some more PID tuning, here is another video of my quadcopter trying to hold its position via the hacked mouse sensor (plus an ultrasound range finder for altitude control).
This was shot about 2 hours before sunset and the sensor already started having some trouble on my dark and fairly featureless driveway in the shadow - that's why I tried to make it hover over a sandy spot that stuck out...
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Solving PPM issues with APM boards


So I get my new APM in the post, excitedly open it connect a few servos, upload the dancing firmware test and.... nothing. Jitter and a crazy flashing mux led.

Anyway to cut a long story short it seems the PPM chip has not been programmed right by Sparkfun. I tried following the steps here,
using the manual process, but found that even though the source from here,
compiles and uploads fine, the chip still doesn't work.

Seemed to me that it may be the brown out protection that is the issue here since the servos probably drop the +v rail when doing stuff, and it looks like there isn't much filtering to the servo +5v rail.
So reading the fuses I notice that the brown out was set to 4.3v which seems quite high, more than likely the issue. So I set it to 1.8v hit program and voilà it all works nicely.

Looking through Jordi's batch file confirms this as this is the setting used in the batch.

Here is the old settings:

>
And the new:


So the process is this:
  • Connect up the APM to your programmer (follow the guide for programming firmware)
  • Go to the fuses tab and click read
  • It should show the extended fuse setting as 0xFC and brown out show as 4.3v (as the first image)
  • You can then either set the drop down to 1.8v OR change the setting directly to 0xFE in the lower section
  • Then hit program, check all the status messages are ok
  • For double confirmation, click read again
  • The settings should now be 1.8v / 0xFE
For me this fixed the PPM chip and now the dancing servos program works fine.

Powering the APM is something of an avoided topic. Seems to me like from the guide someone may blow the board by connecting things up wrong.
My personal preference is to de-solder SJ1 and power the radio gear & APM separately.
On the desk the APM uses the usb (for power and serial debug) and I use a bench supply for the servos (connected to input channel 8).
In the air, I use one of the ESCs (quadrotor) to power the radio etc and a separate BEC/regulator connected to the battery for the APM (connected to the power header).

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Robot cars invade California, on orders from Google


CNet article:

Google has been testing self-driving cars on roads in California, according to a report, and so far they've avoided everything but a minor fender bender--caused by a human-driven car.

The New York Times reports that seven test cars have traveled 1,000 miles without need for human intervention (a driver has been stationed behind the wheel just in case, accompanied by a technician to monitor the navigation system), and that they've covered more than 140,000 miles with the human chaperone stepping in only occasionally. One of the cars was even able to safely make its way down Lombard Street in San Francisco, the fabled "crookedest street in the world," the Times says.



Read more: http://news.cnet.com/8301-11386_3-20019136-76.html?tag=cnetRiver#ixzz11wC79QRi
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Ever fly on days you know you shouldn't? Trees were swaying, and my gut was saying no. But I guess you never know until you try. I'd have to say that I couldn't fly in this wind. The ground track of the aircraft was so unintuitive, especially on landing. At times it was just hoovering overhead making minimal progress.

Days like this that really test your autopilot.

Anyway, this video shows my full auto-landing sequence, complete with the dive from 180 feet down to 50, and final flare with reverse thrust. The throttle you hear on landing is reverse, not forward thrust.

Entire flight is automated. Takeoff, flight to 3 waypionts, and finally landing. Enjoy :)
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Hi guys,

I uploaded the current version of my QT-based GCS to google code. The sources are available via the SVN repository at https://code.google.com/p/yagcs/ .

Current features:
- Real-time map display (native interface, does not rely on google earth plugin, allows offline access)
- Real-time data plot for distance, altitude, etc.
- Simple presentation of roll and pitch via opengl
- Easily extendible (at least that was the goal) via QT ports/slots
- Should be relatively platform independent due to QT

Also, it now functions as a generator of mission header files which can be loaded via the APM waypoint writer. The GUI, however, is still a bit rough on the edges, meaning it's still lacking quite a few features.

The code only relies one two libraries in addition to QT (one for the data plotting, one for the serial port access), which are itself based on QT. That means you do not need google earth plugins, labview, etc., and all is based on open source. For installation instructions see INSTALL.txt and for more information README.txt.

Would be great to get feedback of course. Also, if somebody from the windows users would try to compile it and tell me if this works, that would be very interesting. Also thanks to the person who pointed me to qextserialport, don't quite remember who initially suggested that.

Cheers,
Andre
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3D Robotics

Proposed Open Source Hardware guidelines

I'm part of the process attempting to codify what "open source hardware" means and how to ensure the people who want to be part of the movement can make wise choices about licences, file formats and encouraging the best aspects of the open source:

Here's how the latest version of the definitions start:

"Open source hardware is hardware whose design is made publicly available so that anyone can study, modify, distribute, make and sell the design or hardware based on that design. The hardware's source, the design from which it is made, is available in the preferred format for making modifications to it. Ideally, open source hardware uses readily-available components and materials, standard processes, open infrastructure, unrestricted content, and open-source design tools to maximize the ability of individuals to make and use hardware. Open source hardware gives people the freedom to control their technology while sharing knowledge and encouraging commerce through the open exchange of designs."

You can read the whole thing here. What do you think? Are we on the right track?
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Ardupilot goes into the water Part 14

What happened to the boat and the lake ?
Not really much, there seems to be a kind of stagnation in the air...
I tried the radio-control on the boat several times, but found out, that this is not the solution to the swimming recovery problem. Several reasons for that:


The first try ended up in wading through the mud and recovering the boat, that managed to get stuck in some roots on the shoreline. I tried to get the boat managed by RC, but the diameter of the turn was too big to get it right back to the point, where i have started.
Why that?
The turn diameters were OK, when running in AP-mode.
Seems, that the RC outputs servo pulses only for +- 45 degrees.
The AP can output pulses for up to +- 90 degrees.
To cope for that, i modified the rudder-horn steering to its largest extends so that there was more "angle".
With this modification, the AP still worked and the RC-control of the boat was also possible.

Second, the ESC i am using, can only drive the motor in one direction. So, when the boat gets stuck on the shoreline, there is now way to get the boat shifted into reverse.
The only way to rescue the boat is: still swimming.

Third, adding more technology onto the boat´s electronics makes it more prone to errors than before.

For that reasons (and for the thrill) i decided to dismantle all the RC stuff and turned back to the "old" configuration.

I kept the RC equipment to start some crash-flying experiments with an EASYSTAR, but this is another story...

Some days later, i went back to the lake to do some "long-leg" measurements, to see, how the control loop
behaves on a long trip. (a 400m straight line path and a 180° turn).


The first run was OK.
On the second one, the boat made some weird turns on the opposite end of the lake and crashed into the shoreline, mowing away some reed, until the propeller gets stopped by something hard.
Swimming...
Walking back on the shoreline with the boat in my arms, giving comments to the russian fisherman....

What happened?
It was a windy day and maybe the boat had trouble, moving against the wind, the speed went down and the GPS did not output valid direction data.
This must have been the reason!

I tried again some days later, when it was absolutely still air.
The first run was OK.
The second one...
see above.

This time, the propeller milled away some tupperware housing and the servo had shifted the windmill assembly into an extreme 90° position.
Post mortem analysis of the GPS and control loop outputs showed, that the AP behaved absolutely correct.

hmmm...
thinking...

Bingo!

The following picture shows, what happened:

The Rudder Horn steering was still at its extreme positions, that i had used for the RC experiments. And, in some situations (e.g. a full 180° turn) it could happen that the steering rod acted as a "piston" as we have in internal combustion engines. The assembly kept stuck in a 90°+ position.
So it was no wonder, that the boat made some weird turns.

Next, i reduced the angle of the steering and introduced a "push-pull" assembly with two steering rods.
That was it!

Absolutely perfect straight line behaviour. No stalls, no further swimming.
The world was perfect again...

Not absolutely perfect.

The mounting position of the sonar transducer was still something that should be enhanced. Too much drag, too much irritation.

So i mounted the transducer into the right hull.


I expected a faster boat after that modification, but the inrease of speed was neglegtible compared to the the "old" configuration. Anyway, the boat glides much smoother trough the water and there is no more chance for water plants to hook into the transducer.

In the next episode:

A new lake and new Dr Depth pictures....

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Moderator

QuadFox Stable mode test


In this video is possible to see the incredible stability of DCM V3 developed by Jose Julio a member of Arducopter DEVTEAM.In this video I enjoyed playing with my QuadFox. Tell me your impressions. Iported this algorithm and the original code of Arducopter multipilot
hardware and controllers i2c hardware as well as original APM impressive
results in terms of stability in this video you can see how the
aircraft is stable and easily implementable
with automatic flight control systems, GPS, magnetometer, sonar and so on.
Congratulations to Jose and all members of the DevTeam. I am proud to help develop Arducopter project:) Thanks Chris for this opportunity and Jani:)

for more info check original post : http://www.virtualrobotix.com/profiles/blogs/quadfox-stable-mode-outdoor

Regards Roberto
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I did a little digging into the current state of affairs with regard to commercial small unmanned aircraft systems (SUASs) and I'm not really sure what it all means. On the one hand, there seem to be quite a few companies developing and/or manufacturing SUASs. Presumably, many of these are for private, commercial use as opposed to pure research, governmental or recreational activity. On the other hand, judging by what I'm reading from the FAA, the current state of allowable SUAS use does not come close to justifying this level of commercial development. What do these people know, and where are all the SUASs currently in existence being used?

I'm sure that anyone developing a hobby SUAS would love to allow it to fly outside of the range of manual control. Right now, the hobby community is pretty much restricted to the pure excitement of watching a plane fly on autopilot, but within the same airspace as a manually flown R/C plane. The point, and I know it's not new, is that as goes commercial SUAS regulation so goes (to some extent) recreational regulation (hopefully in a positive and/or more unrestrictive way). So, this is the tie-in relative to DIY Drones.

First of all, if you haven't read this FAA fact sheet, it's both interesting and encouraging, so you might want to (it's short).

http://www.faa.gov/news/fact_sheets/news_story.cfm?newsId=6287

For what it's worth, I think there might be some confusion on this site regarding COAs, or Certificates of Waiver or Authorization. These are only available to public entities, i.e. not private commercial ones, who want to fly SUASs in public airspace. As of September 2010, there are only 251 active COAs. By definition, none of these relate to private commercial SUAS use.

The only certification available to civil operators of SUASs is a Special Airworthiness Certificate in the Experimental Category. Since 2005, only 78 have been issued.

While the FAA seems to be very positive about SUAS development and use, it appears that, in reality, there just isn't much practical use of these systems going on in the private sector. Yet, a whole lot of companies and their investors must see something coming, and soon. Is all of this activity based on speculation, or are there current, practical uses of SUASs going on? If so, what are they? Personally, I would love to see an SUAS surveying a corn field as I drive by! I think it's going to be while, though.

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Moderator

QuadFox Stable mode test


This evening i finish to implement the code QuadFox on multipilot this is the first flight test. This code is a porting of Arducopter on my Multipilot board . The different respect of original project is I2C ESC , Mixertable that support Quad , Hexa , Okto , 20 Mhz of clock cpu instead of 16 Mhz and 1 wire RC input compatible wit jeti radio and Robbe - Futaba receiver 2.4 ghz. Other advanced feature is Multi Processor architecture for sonar, gps, magnetometer and ir sensor.

Check the stable mode at minute 4.20 :)

Great Job Arducopter DevCore Team ;) Next Step i would test GPS Hold .... Jose your new revision of DCM v3 ... work fine .. great job Jose ...

Check my blog for more info about the project : www.virtualrobotix.com

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Folding Quad Rotor for Avalanche Rescue

I found this quad while browsing through the James Dyson Awards. There is a link above the pictures to translate to English.

I couldn't find much on the company but they seem to be planning for this to be part of a full UAV system that marks the location of Avalanche victims.

I like the simplicity of the design. This may inspire my next quad...

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