GroundControl and MAVLink have been improved substantially behind the scenes over the last months. The most obvious new feature on the user level are custom user widgets. You can configure yourself parameter sliders and buttons and even export this widget into a *.qgw file, which other users can import. The video shows how to create a custom attitude control widget for ArduPilotMega. Most of the other improvements are speed and stability improvements which are not directly visible, but improve the user experience a lot. Since we wanted to make sure to get some testing done this is the first preview of the new version. Before end-users can test it, it will also require porting all autopilots, e.g. APM, to MAVLink v1.0.0, which is already scheduled and will happen in a few weeks. Porting is straightforward, as the C-API is mostly unchanged, only a few message signatures were updated.

Thanks to Andrew Tridgell and Paul Grobler for their contributions on the protocol. And Andrew Tridgell completely rebased the protocol generator on Python, allowing to now generate C and Python code from a single generator.

A porting guide for autopilots will be available soon.

The MAVLink mailing list is currently very actively discussing which route to take to CAN-MAVLink integration. Especially engineers working in their day jobs on ARINC 825 or CANaerospace could bring important feedback to the table, so please share your knowledge.

Google Groups MAVLink CAN discussion

 Since this design will be very likely the reference design not only for the first 2-3 autopilots implementing it, but might also become the DIYDrones community standard, I'd like to invite all potential developers and adopter to join the discussion (on the mailing list please, not in the comments).

Further reading:
http://de.wikipedia.org/wiki/CANaerospace

http://en.wikipedia.org/wiki/ARINC_825

The design we pioneered in 2009 for machine vision with Gumstix Overo is now finally available as product from Gumstix. They did a great job of converting our initial raw open source design into a usable product, our internal prototype made it not beyond basic sensor readout routines. The picture on the top shows the finished Caspa board, the image on the bottom one of the earlier prototypes:

The module provides 752x480 (640x480) pixel resolution in color and can be purchased from Gumstix either with IR (VS) or without IR cut filter (FS). For most applications not operating at dawn/dusk the version with IR cut filter will provide better image quality.

PLEASE NOTE: We're thrilled that this tiny machine vision platform is now available for the general public. PIXHAWK is however not associated to Gumstix or does benefit financially from the product. We're just happy that the concept of open hardware worked out again.

• Caspa FS (Full spektrum, color)
• Caspa VS (Visible spektrum, color, recommended)

This video shows how each user can configure the layout and even individual sliders and buttons of QGroundControl for his personal needs. This version is compatible with the current ArduPilotMega pre-release 2.0 codebase from the SVN repository (trunk). Please note that the video shows only a snapshot, not the final QGroundControl 0.8.3 release version (we're still improving it on a daily basis). User feedback is very welcome, if you want to try it yourself you can download a binary for Mac OS and Windows.

https://github.com/pixhawk/qgroundcontrol/downloads/

QGroundControl is currently improved on a daily basis along with the efforts to implement a common mission interface for ArduPilotMega and MAVLink. While this is work in progress, I'd like to share some impressions of the new features. Once the next APM version is released, a matching stable version of QGC will be released as well optimally supporting APM. The picture above shows the Google Earth mission interface on Mac OS X, which supports waypoint creation (double click) and dragging. The Windows version is lagging slightly behind: Waypoint visualization works, dragging not yet. I would like to particularly thank our restless beta testers, their excellent feature requests and bug reports really helped improving the usability.

Realtime Linechart Plot: Allows to log data to a CSV file (e.g. for Matlab) and to see how sensors and filters behave in realtime. It includes mean and variance values (second and third column) and you can freely set the window size for the calculation of mean and variance.

2D Map: Perfect for mission planning and computers without the processing power for Google Earth

QGroundControl got now also persistent settings, which means that preferences are stored. Most of the widgets store the last configuration (e.g. which option you checked). You also can rename MAVs, e.g. MAV001 to ALPHA. You can even set QGroundControl to auto-connect your serial link with the last settings on startup. On the protocol side safety was improved by retransmitting lost packets, ensuring now that not a single parameter is lost.

QGroundControl can now also log MAVLink packets with timestamp and replay whole missions. It accepts binary logs (raw data from e.g. serial logs) as well. So you can now run a HIL simulation and view the output in realtime in QGroundControl, log it, send it to a friend or export the data to Matlab. The offline logfile analysis tool (not shown here) allows you also to print 2D plots or create PDF or PNG files from them.

For the brave: There are daily experimental builds that work with the SVN version of APM. They are in general stable, but of course not as well tested as a full release version. The executables for Windows and Mac OS can be downloaded at:

https://github.com/pixhawk/qgroundcontrol/downloads

Since this is still beta software, bug reports and feature requests are welcome:

https://github.com/pixhawk/qgroundcontrol/issues

From 0.7.7 to 0.8.0 QGroundControl got many new features and bugfixes, it's impossible to fit all of them into one post. We will therefore run a small blog post series over the next few days to cover them. An experimental release is already available for Windows and Mac OS, so you can try it out on your machine if you like. The application might have still some minor rough spots, the current release is mostly targeted at the different autopilot developers to allow them to give feedback for the "official" release.

Major Improvements and new Features

• New, flexible widget system, every user can have his personal arrangement of the interface (contributed by SLUGS project, Mariano Lizzaraga, JFR Camacho)
• ArduPilotMega MAVLink branch support and actions in waypoints (James Goppert)
• Google Earth support
• QGroundControl now stores many of your preferences automatically, including window size and position, selected widgets, serial port baud rate, etc.
• Support for small screens
• Data logging and plotting (after flight, time line or e.g. lat vs lon)
• MAVLink protocol version detection, user gets warned if MAV and QGroundControl protocol versions mismatch
• Many, many bugfixes

Windows Google Earth View

The screenshot below shows QGC running on Windows 7, with a custom widget arrangement showing the SF area with Google's new 3D trees.

Linux 3D View

The non-maps 3D view is very handy for robotics applications where the focus is on the trajectory of the vehicle and additional 3D information, like e.g. the occupancy grid, should be displayed. The tool widgets surrounding the view can be freely enabled / disabled and will be loaded on the next startup again.

Live Plotting / Engineer View

The live linechart is very handy for reading out sensor or filter values. The parameter tree widget on the right allows to adjust controller or filter values (e.g. PID gains) in realtime and watch the result on the left. Of course other widgets could be activated as well, but this screenshot is a nice example of a really reduced interface.

Data Analysis View

It is often annoying to import logged data into an external plotting tool for just having a quick look at the data. QGC therefore now switches after finishing a logging session in the line chart (live) view to the data analysis view, where you can plot the data in other formats, plot X vs Y instead of X vs time, etc.

Experimental preview executables: They are stable and can be used to test the new features, but are not intended for flight use! We will test the current release thoroughly over the next days and then release the stable version once it is rock-solid. Please note that runtime performance and stability will improve until the final release.

Please use the Github issue tracker to report back bugs or odd behaviour!

• QGroundControl Windows Installer
• QGroundControl Mac OS Leopard DMG file
• QGroundControl Windows Binaries (ZIP file)

Please feel free to add any feedback or feature requests to the bottom of this post.

It was just one of these casual quick hacks (about 10 lines of code), but QGroundControl now also allows to use Google Earth for visualization, including the new trees feature. We're just in the beginning of the integration, a binary including this feature should be available next week.

While Google Earth is very shiny, it does not allow adding additional visualization components with the same degrees of freedom as OpenSceneGraph and osgEarth. We will therefore push the OpenSceneGraph/osgEarth integration further, as osgEarth also allows for better offline use without internet connection. As our MAVs collect aerial images, osgEarth allows to directly render them into the scene (as 3D mapping), a feature missing in Google Earth. But since we now support the best of both worlds, QGroundControl users have all choices at hand.

The QGroundControl dev team is currently hard working on the integration of more autopilots and the 3D outdoor view. In line with these efforts we would like to add more CAD models of airplanes, helicopters and other MAVs to allow users to select a CAD model close to their aircraft.

If you have a CAD file (.step/.stp or .iges or any other common exchange format), please send it to <pixhawk@switched.com>. Please note that the CAD model will be included into the GLP-licensed QGroundControl application. If you send it in, please do not forget to give the name of the model and the real/physical size.

We were already using the Gumstix Overo COM in our winning EMAV 2009 entry. Other projects have started to adapt the system design with Linux onboard computer. It separates the Linux computer vision system and control/estimation code running on an external microcontroller. At that time we already did the electronics design for a custom camera board, but eventually used a USB machine vision camera. However now we have a working driver, which allows to attach the Aptina MT9V032 machine vision CMOS sensor directly to the Gumstix Overo COM. The board will be available from Gumstix Inc., but is not yet released as a product. The pxOvero base board weights only 28g including the camera with M12 glass lens! It works under very low light conditions and has a much lower noise level than typical webcams. We hope to see this pair soon in many computer vision MAVs. Our upcoming aerial robotics middleware is lightweight and has been developed so scale to lightweight computers. Together with this camera, it will provide a very convenient toolkit for computer vision on micro air vehicles.

• IMAV 2011 "summer edition" rules

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.