I just realized this is the very first blog I ever wrote :) 

RTK GNSS is an interesting topic for many quadrotor diyers like myself. It can provide stable sub meter coordinates which is very attractive for autonomous quadrotor flights. Initially, I tried RTKLIB on windows platform, and the result is pretty encouraging. However, I cannot imagine to have a windows running computer on a quad. Intel edison is another option for me: reasonably priced, small enough, and powerful enough to run real time RTK algos. After having this idea for a few month, I noticed REACH is commercialized RTK GPS using a very much close methodology. My intention is not to commercialize my design so REACH's results confirmed Intel Edison is suitable for RTK algos.

In the second version design, I would like to have Linux take over the control. which means linux can get the data for running RTK algo without the help of of a MCU. In my design, I put a four port USB hub on board along with a few USB-UART bridges. These USB-UART converters will get rover data from GPS modules, and reference data from either MCU or 433Mhz radio. On top of that, the USB hub also connected to a 3G modules. in this way, the RTK module could get online to take advantage from real time networks. 

It's always such a pleasure to find new projects with Navio2 and Reach RTK GNSS  in project category on our community forum.  This time we've decided to share the details and cool demonstration of one of them.

Recently @Mr337 shared his terrific MowPilot - autonomous lawn mower with Navio2 on board running ROS. 

Navio2 is responsible for interface with GPS, RC In/Out, I2C, and it will be used for some simple sensor interfacing. All while the Rpi3 is running ROS in making decisions.

The fastest speed for now is 1.5ms/ (3.3 mph) while still keeping cutting accuracy.

The error is normally within 4 inches but can peak to 8 inches with really rough terrain.

Hardware used:
Navio2 + RPI3
Arduino Nano
Motor Controller
RTK GNSS

Software:
ROS
Interfaces provided by Navio2 SDK

Here is a spiral cut to test turns and tighter turns

Track:

From The Verge:

Audi, like pretty much every other automaker under the sun, continues to introduce more and more automated driving features for its cars. The next step, says the company, will be machine learning-powered driver assist features that work in constrained situations like driving in traffic and parking. They’ll be available in the new generation of Audi A8 saloons in 2017, but for the moment the German company is testing these features in a much more compact model — specifically, a model car 1/8th the size of the real thing.

You can see this pint-sized vehicle in action in the video above. Using deep reinforcement learning (a type of machine learning that’s essentially trial and error with "rewards" for the computer when it gets something right), Audi’s technicians have enabled it to autonomously search and park in a 3 x 3 meter arena. "An algorithm autonomously identifies the successful actions, thus continually refining the parking strategy," writes Audi in a blog post. "So in the end the system is able to solve even difficult problems autonomously."

Audi isn’t the only player in the auto industry to use machine learning to develop autonomous driving (startup Drive.ai is doing something similar) but it is one of the biggest, and technology it introduces will affect more drivers. Just like Audi’s miniature training car, pretty soon technology will make us all model drivers.

Some of you might be familiar with the Black Magic Probe, but some might not. As you know most UAV autopilots these days use one of the many STM32 microcontrollers. They are based on the ARM Cortex-M core family. Most of the boards also have either a JTAG or at least an SWD interface exposed. What you might not know or be familiar with is how useful these interfaces are.

If you connect a Black Magic Probe to your autopilot you can connect the GDB (GNU Debugger) directly to it and you can read, write memory, inspect the status of registers, manipulate peripherals, load a new firmware into flash and much much more. This will make debugging your autopilot firmware much easier, than adding print statements or blinking an LED. For those more familiar with JTAG/SWD debugging Black Magic Probe does not require a man in the middle software like texane/stlink or OpenOCD. This decreases the amount of setup complexity. Also we have put a lot of effort into making the target interface circuitry robust, using dual supply transceivers, adding a target supply switch and a built in USB to serial adapter.

If you are still not convinced that you need this tool, you should read the Hackaday article, and take a look at the Pixhawk website you will also see that the Black Magic Probe is their tool of choice too. (if you are interested in Drone Code development, 1BitSquared sells ARM Cortex 10pin connector to Drone Code connector adapter)

In this Kickstarter we are introducing the new version of Black Magic Probe V2.1. It has a more robust target front end, making sure the JTAG/SWD signals are solid and you will be able to debug your target device even if you are using long wires. (especially useful when your autopilot is buried deeply in the fuselage of your aircraft. Additionally you can also get a matching STM32F415 based development board, that you can learn and test the use of Black Magic Probe and GDB on. This is the same CPU that can be found on the Elle0 autopilot that we have featured here in the past.

I hope you will consider taking a look at our Kickstarter and decide to support us. The revenue from this project will go directly back into the open-source projects that made it all possible. We will be able to spend more time developing more software and hardware making open-source ARM development easier.

Cheers,

Piotr Esden-Tempski

If Gary is convinced, so am I:

A while ago I thought that small 3D printed drones would not really become a thing. I based this on weight and build size. I could not see how it could be made to work.

I was utterly wrong.

Stepan Dokoupil and Patrik Svida, of 3D Lab Print in the Czech Republic, have created works of art. Scale warbirds and a glider right now but it can only be a hop and skip to making unmanned aircraft that can be reproduced at a low cost as fast as your printer can print.

I cannot begin to imagine how many hours of work have gone into designing these machines.

The thought of being able to email an update of a design or indeed an entirely new design to somebody in the field is delicious. It would create an entirely new sort of relationship with drone designers and customers.

Regulators will also have something else to think about.

I’m convinced locally printed drones have a future. I am late to the party.

https://www.youtube.com/watch?v=UJw9KC7ut0A

It is amazing to see how fast our industry is advancing. Reliable, repeatable data collection is no longer the challenge it once was. Through the efforts of many of you on this site, organizations are now able to start focusing on how to leverage reliable data collection with advanced sensors in new ways.

Two dimensional vegetation indices have now moved into the third dimension.

Please take a moment to review the Parrot/Pix4D Climate Innovation Grant. We are looking for leading edge climate researchers to start thinking about how to apply autonomous vehicles, advanced sensors and best of breed processing software to difficult challenges related to the climate that we all share.

The best part is FREE Sequoia sensors with Pix4D licenses!!

--------Links and more information below----------

To help foster further innovation surrounding the impact of climate change, Parrot and Pix4d are announcing a Climate Innovation Grant. This grant program consists of a hardware and software award. Successful proposals will receive a  Parrot Sequoia multispectral sensor, a Pix4D software license, and training.

With climate innovation as the underlying theme, grant proposals should include a geographical/mapping component using UAVs and Pix4D mapping software, as well as multispectral imagery related to the technical capabilities of the  Parrot Sequoia sensor.

This competitive grant program is open to students and researchers across the globe and across a range of disciplines, from archaeology to zoology.

Deadline for submissions is January 31st, 2016. You can apply at edu.parrot.com/climate

We are currently on the 5th prototype of the DeltaQuad VTOL and today we have put it through its paces with a 60KM autonomous flight. Over at DronesLab we have been working on this machine for more than a year and are in the final stages before releasing it to market. Above is a sneak preview.

The 60KM flight was planned after settling on the final specs of the fixed wing drive. After this flight the battery had only discharged 65% of it's total capacity. This puts the range of the DeltaQuad on our 100KM goal. 

The log of this flight can be found here: http://logs.uaventure.com/view/LDwQsdRc3LpVwrd7EsenR8

We have always been careful with releasing specs as we did not want to over promise anything, but after many inquiries here's a small overview of the current specs;

Cruise speed: 60kph
All out weight: 5.2KG
MTOW: +- 6.5KG
Wing span: 2370mm
Range: 100KM (carrying 1KG payload)

These specs are not final and more tuning will be done to maximize reliability and efficiency.

Uniquely on this airframe the payload bay is located directly on the CG, it can therefor fly with dynamic payload weights without needing to balance the CG. We have also successfully managed to eliminate the requirement for an airspeed sensor (no more daily calibrating required).

It is designed to be controlled from a tablet or cloud system and flies fully autonomous from takeoff to landing.

As with any R&D project it is hard to give timelines but the DeltaQuad should be available in both hobby and commercial versions mid 2017.

Cheers,
DronesLab

From MIT:

A new system from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) is the first to allow users to design, simulate, and build their own custom drone. Users can change the size, shape, and structure of their drone based on the specific needs they have for payload, cost, flight time, battery usage, and other factors.

To demonstrate, researchers created a range of unusual-looking drones, including a five-rotor “pentacopter” and a rabbit-shaped “bunnycopter” with propellers of different sizes and rotors of different heights.

“This system opens up new possibilities for how drones look and function,” says MIT Professor Wojciech Matusik, who oversaw the project in CSAIL’s Computational Fabrication Group. “It’s no longer a one-size-fits-all approach for people who want to make and use drones for particular purposes.”

The interface lets users design drones with different propellers, rotors, and rods. It also provides guarantees that the drones it fabricates can take off, hover and land — which is no simple task considering the intricate technical trade-offs associated with drone weight, shape, and control.

“For example, adding more rotors generally lets you carry more weight, but you also need to think about how to balance the drone to make sure it doesn’t tip,” says PhD student Tao Du, who was first author on a related paper about the system. “Irregularly-shaped drones are very difficult to stabilize, which means that they require establishing very complex control parameters.”

Du and Matusik co-authored a paper with PhD student Adriana Schulz, postdoc Bo Zhu, and Assistant Professor Bernd Bickel of IST Austria. It will be presented next week at the annual SIGGRAPH Asia conference in Macao, China.

Today’s commercial drones only come in a small range of options, typically with an even number of rotors and upward-facing propellers. But there are many emerging use cases for other kinds of drones. For example, having an odd number of rotors might create a clearer view for a drone’s camera, or allow the drone to carry objects with unusual shapes.

Designing these less conventional drones, however, often requires expertise in multiple disciplines, including control systems, fabrication, and electronics.

“Developing multicopters like these that are actually flyable involves a lot of trial-and-error, tweaking the balance between all the propellers and rotors,” says Du. “It would be more or less impossible for an amateur user, especially one without any computer-science background.”

But the CSAIL group’s new system makes the process much easier. Users design drones by choosing from a database of parts and specifying their needs for things like payload, cost, and battery usage. The system computes the sizes of design elements like rod lengths and motor angles, and looks at metrics such as torque and thrust to determine whether the design will actually work. It also uses an “LQR controller” that takes information about a drone’s characteristics and surroundings to optimize its flight plan.

One of the project’s core challenges stemmed from the fact that a drone’s shape and structure (its “geometry”) is usually strongly tied to how it has been programmed to move (its “control”). To overcome this, researchers used what’s called an “alternating direction method,” which means that they reduced the number of variables by fixing some of them and optimizing the rest. This allowed the team to decouple the variables of geometry and control in a way that optimizes the drone’s performance.

“Once you decouple these variables, you turn a very complicated optimization problem into two easy sub-problems that we already have techniques for solving,” says Du. He envisions future versions of the system that could proactively give design suggestions, like recommending where a rotor should go to accommodate a desired payload.

“This is the first system in which users can interactively design a drone that incorporates both geometry and control,” says Nobuyuki Umetani, a research scientist at Autodesk, Inc., who was not involved in the paper. “This is very exciting work that has the potential to change the way people design.”

The project was supported, in part, by the National Science Foundation, the Air Force Research Laboratory and the European Union’s Horizon 2020 research and innovation program.

Hi all!

We are glad to announce the start of crowdfunding campaign for Nimbus – racing drone with full carbon fiber monocoque body.

Please support us at: https://igg.me/at/nimbusdrone

Our website: aerodyne-rc.com

The  Idea and the Impact of monocoque frames in racing drones.

Carbon fiber is well-known material for making drones, and especially racing ones. Conventional racing drone frame is made of layers of cut flat sheets of carbon fiber with aluminum or plastic stand-offs in between, openly holding the electronic components.

But we do the carbon fiber frame of a racing quad copter in a very different way - it is monocoque.  Monocoque design is widely used for example in aerospace and automotive industries (airplanes and car bodies), it has high structural properties but very lightweight.

We see that monocoque design gives a new step to the drone racing as a new entertainment and growing sport with very high visual attractiveness. The main obstacle holding the drone racing to grow is the obsolete frames design. It is like first wooden airplanes, the bi-plane of Wright brothers from year 1903. Yes, the components are developing fast – new flight controllers, new motors and FPV cameras, but the fundamental frames development has stuck and going in circle for last couple of years. And the usability of flat-frames for drone racing is quite low. Flat carbon cracks and breaks down, during inevitable crashes, open electronics and wires are affected by environment – water, sand, dirt, snow, salt etc. Racing drone pilot spends more time in repairs and waiting for delivery of new components than flying. Having a number of spare drones for each race is not the most efficient way of growing, in terms time and money. Of course, it is hobby! I like building my quad! But sport will not go that way. It has to be an entertainment, and it shall be based on a very durable item with high usability (imagine usability and durability of a soccer ball, or baseball bat, or goalkeeper mask in ice hockey).  And for the development of drone racing as a great hobby and sport it is important - if you want to fly, you need to fly! Survive the crash and fly again! Spend less time with wires and soldering iron, and more time flying! And it really seems, that future of drone-racing in not in the stick-built frames, but something else, something more durable and usable.

So, usability was the main design criteria for Nimbus drone design. And the realization is in the monocoque design for the frame.

What gives a monocoque frame to a racing drone?

First of all, it is strength. Monocoque is the best possible structural form to have best strength-to-weight ratio. Monocoque is basically a structural skin, is a structural system where loads are supported through an object's external skin, similar to an egg shell. The word monocoque is a french term for "single shell" or (of boats) "single hull". A true monocoque carries both tensile and compressive forces within the skin and can be recognised by the absence of a load carrying internal frame.

Early aircraft were constructed using frames, typically of wood or steel tubing, which could then be covered (or skinned) with fabric as lines or cotton. The skin added nothing to the structural strength of the airframe and was dead weight beyond providing a smooth sealed surface. By thinking of the airframe as a whole, and not just the sum of its parts, monocoque structures made sense and various aircraft companies soon adopted practices for building monocoque aircrafts.

In motor racing, the safety of the driver depends on the car body which must meet stringent regulations and a few cars have been built with monocoque structures. McLaren was the first to use carbon-fiber-reinforced polymers to construct the monocoque of the 1981 Mclaren P4/1, and in 1992 the McLaren F1 became the first production car with a carbon-fiber monocoque.

The same we have now for racing drones. We need strength, we need low weight, and we need to save our internal electronic components.

Nimbus –new step in racing drone design

Nimbus racing drone is a true monocoque of carbon fiber. We have some attempts on the drone racing market, which were partly carbon fiber  monocoque, or looked like monocoque, or has very weak points in other aspects. Nimbus drone was not made in a hurry. It took more than a year of development and testing before we came to public.

Production of a monocoque form, and especially carbon fiber, requires significant initial preparations and investments. Therefore we started with small crowdfunding campaign to support first production run of Nimbus. We just started the campaign at Indiegogo 5^th of December 2016. It will last for 30 days.

The backers of the Nimbus campaign will be able to get three alternatives of Nimbus drone: Frame only package, BNF - Bind-And-Fly package – assempled Nimbus to bind with your radio, and RTF – Ready-To-Fly – a package including complete Nimbus and TBS Tango remote control radio.

Strong, durable, lightweight, aerodynamically streamlined, weatherproof racing drone with enclosed electronic components and battery.  Nimbus will become a game changer in drone racing.

If you understand the impact of new monocoque design in drone racing, please join our campaign!

“That is one small step for a drone, one giant leap for drone racing.”

Aerodyne-rc.com

info@aerodyne-rc.com

Hello! I am sales from Skywalker Technology Co., Ltd. 
Recently, we launch new professional mapping survey aircraft, Skywalker X5-PRO. Now, let me take eye feast about this aircraft.

https://v.qq.com/x/page/m0351li7fny.html

Characteristics

• Adopted EPO material, light and sturdy.
• Large capacity cabin, reasonable area distribution,such as parachute cabin, camera slot, GPS and other professional platform.
• Stable and flexible flying.
• Module design, disassemble and assemble easily and conveniently.
• Special winglet design, small resistance, long range, precise operation.

Specifications

• Wingspan:1280mm
• Fuselage length:717mm
• Wing area:44dm2
• Flying weight:1800-2500g

Recommended Cofiguration

• Motor:2816KV840
• ESC:70A
• Servo:12g*2pcs
• Propeller:1060E
• Battery:4S 5300mah
• Radio：3CH 2SERVO

Hi All, Sony has actually given us something to think about.

http://www.sony.com/electronics/actioncam/fdr-x3000-body-kit

The Sony FDR X3000 Action Cam has 4K resolution, but for our use, the BOSS active optical stabilization is the important part.

The Electronic stabilization available on the new GoPro and previous Sony Action Cams has definitely not been up to the needs for being used gimballess on our multicopters.

Especially roll causes problems because of the difficulty in correctly compensating for it in on camera firmware.

Sony is the first company to offer a Action Cam with true optical stabilization and their BOSS stabilization provides possibly the best results of any of the consumer and prosumer video cameras and that is what they say that they have incorporated in this camera.

It sells for $350.00 and if their claims are true (and videos circulating on the internet suggest they are) then this should be very usable in multicopters without a gimbal (or maybe with a simple servo driven pitch only one to provide in flight adjustable up and down angle.)

As to controlling it in flight or extracting an FPV usable image, those are unknowns, but my thought is that it would certainly be worth seeing what this camera can do un-gimbaled on a quadcopter.

I have tried Sony's earlier version with electronic stabilization on my Hoverthings FPV Pro and it definitely does NOT provide sufficient stabilization, but the BOSS optical stabilization in the new one is a whole new ball game.

I know it's a weird form factor and it's interface capabilities are not so straight forward, but the picture is very high quality and it has very good color saturation and contrast and no fish eye and if the stabilizatuion works well enough this could be a great camera for us.

Just thought it was worth bringing this to the attention of my fellow DIYers and to ask if anybody gives one of these a try, please share your results.

Best Regards,

Gary

This video shows me flying a Syma X5C quadcopter, with the factory closed-source flight controller replaced by a Quanum Pico 32-bit brushed FC.  I followed the directions in the "Visible Drone" chapter of this excellent new book, but, lacking the eye/hand coordination required to do surface-mount soldering, I used a Quanum Pico instead of the Teensy-based FC shown by the author.

A simple 3D-printed mount allowed me to attach the new controller with some 3M VHB tape. 1.25mm picoblade connectors, available cheap on ebay, connect the FC to the brushed motors on the Syma.  I flashed my own firmware on the board, using PIDs from a 3DFly/Pico vehicle I'd built.

In addition to having a Spektrum DSM receiver onboard, the Quanum Pico has built-in Molex connectors for attaching I^2C and UART devices.  So I'm hoping to use the modded Syma drone to experiment with proximity sensing, optical flow, and the like.

"Morphology plays an important role in behavioural and locomotion strategies of living and artificial systems. There is biological evidence that adaptive morphological changes can not only extend dynamic performances by reducing trade-offs during locomotion, but also provide new functionalities. 

http://ieeexplore.ieee.org/document/7..."

Hey everyone, 

I wanted to announce the successful first forward flight with the Local Motors/Airbus VTOL UAV. Powered by a Pixhawk 1 with Arduplane 3.7.1, weighing in at 54.85lbs!

I was called in three weeks ago to help them design, build, and fly all before 11/30/2016.  I showed up at the shop and they had nothing but some ESCs, Motors, and concept art. Well on Wednesday we made the attempt to transition, and it came back in one piece.

The full report and video of the flight can be found here:

https://launchforth.io/localmotors/airbus-cargo-drone-build/discussion/topic/flying-drone-final-build-test-flight/62079/

AeroVironment’s new drone and cloud-based analytics platform squarely targets the commercial sector, but are they targeting the wrong vertical, too late in the game?

THE FACTS:

Earlier this month, the military and tactical unmanned aircraft systems manufacturer AeroVironment (NASDAQ:AVAV) proudly unveiled its new Quantix^TM drone and a cloud-based analytics platform called the AeroVironment Decision Support System (AV DSS™).  The combo is designed with the civil/commercial markets in mind. The drone is a hybrid design that enables the aircraft to launch vertically like a quadcopter and then transition itself for horizontal flight, taking advantage of a fixed-wing drone’s aerodynamic efficiency and range.  According to the company, the drone can map 400 acres in about 45 minutes, and its overall flight time is supposed to be an hour per battery.

The Quantix is a key piece to a larger end-to-end solution AeroVironment hopes will meet the needs of the agriculture, energy, and transportation industries, among others. Key to AeroVironment’s solution is a proprietary mobile interface that works with their secure cloud-based data storage.

WHAT’S COOL AND WHAT’S NOT

It’s great to finally see AeroVironment come out with an offering dedicated the commercial drones market.  While their Puma AE was used for aerial surveys in Alaska—and was the first time the FAA has authorized a commercial UAS operation over land, this product will be the first non-military product in their lineup. So, welcome. Or should I say—I’ll welcome you when you get here. Quantix won’t be available until Spring of 2017. And the price has yet to be announced.  However, in my conversations with the company at last month’s Drone World Expo, it’s clear some among their ranks understand it will need to be priced below $20K, or it’s simply not going to sell well.

Read more here: http://droneanalyst.com/2016/12/02/can-aerovironment-compete-in-the-commercial-drone-market/

Wirelessly powered drone by GET technology from GET corp on Vimeo.

Our team of world-class engineers continues working on wireless power technology, and we aim to deliver industrial solution next year – to provide safe and efficient high-power long distance wireless power transmission, and deploy wireless power networks for drones in cities across the globe.

We are glad to present new video of the drone powered completely wirelessly by GET technology (as many suggested in their feedback, this time we made the flight without a tether) – enjoy and share!

Check more http://getcorp.com

In August 2015, the Swiss humanitarian organization FSD kindly hired me as a consultant to work on the EU-ECHO funded Drones in Humanitarian Action program. I had the pleasure of working closely with FSD and team during the past 16 months. Today represents the culmination of a lot of hard work by many dedicated individuals. Today we’re launching our comprehensive report on “Drones in Humanitarian Action: A Guide to the Use of Airborne Systems in Humanitarian Crises.” More here.

Hello guys,

You probably know that we’ve developed the Mapper version of the SOLO which includes a Sony Qx1 (APS-C sensor, 20 Megapixels) and an automatic geotagging feature. Designed for technical work and compatible with mission planner / Tower (video below)

link to the webpage

Our next production starts on december 19 (two weeks left) so we wanted to share this information with you as there might not be any other opportunities to get them later.

Here is the video on how to use it with Tower (it’s as simple as this)

https://youtu.be/gGGhKhX5n3c

FIY, we released the code that runs in the companion computer open source, you can find it here :
https://github.com/Escadrone/Solo-Mapper and develop your own solutions

Clients will also be provided with this set of documents :

For All DIYDRONES members we’ll include a 32GB memory card instead of an 8GB, just mention that you’re part of the community during your order (or send us an email afterwards)

I've just seen cool tests from Jeff Taylor and his Event 38. They integrated Emlid's Reach in E384/E386 mapping drones and verified processed data accuracy using data from Trimble R6 Model4. 

With the Emlid Reach RTK GPS Receivers now available, we’ve been conducting tests to determine their accuracy and working on the integration into the E384 and E386. The goal was to determine relative, or scale, accuracy as well as absolute accuracy verified with a survey grade Trimble R6 Model 4.

We post-processed the data in three different ways to explore the effect each would have on the resulting data. For PPK GPS processing, there is a receiver onboard the aircraft and another stationary receiver on the ground. The ground receiver (base station) is used to calculate corrections to refine the position of the airborne receiver. The base station also calculates a precise GPS coordinate for itself, with the option of writing in another, more accurate coordinate if desired. We constructed orthomosaics on the Drone Data Management System™ using geotags calculated from the Reach base station and the Trimble base station, using either the Reach base coordinate or the Trimble base coordinate. The combinations for each test are listed below.

Base Station Corrections	Base Station Coordinate
Reach	Reach + CORS
Reach	Trimble R6-4 + ODOT VRS
Trimble R6-4	Trimble R6-4 + ODOT VRS

Test1:

It was clear straight away that there was an offset between the Reach and Trimble coordinates, so we focused on scale accuracy for this test. The offset is clearly visible in the image below, where emp is the Reach base station coordinate and 6 is the same coordinate shot by the Trimble R6. To measure the scale accuracy of the Reach-only orthomosaic, we measured distances between several pairs of GCPs in different directions. The error was 3cm in each case.

GCP Pair	Reach Orthomosaic (m)	Trimble R6-4 (m)
12-4	171.87	171.84	NE-SW
19-3	115.23	115.20	North-South
5-2	145.46	145.43	East-West

Test2:

Processing the geotags using the Emlid Reach base station but using a coordinate shot by the Trimble R6-4 resulted in very good accuracy relative to the Trimble shot GCPs, with an RMSE of 3.36cm.

GCP	Error (cm)
2	2.631
3	3.749
4	4.799
5	2.072
7	2.867

Test3:

Finally, processing using the trimble base station for both corrections and the base coordinate yielded similar results to those obtained with the Reach corrections, RMSE 3.54cm.

GCP	Error (cm)
2	4.667
3	3.099
4	4.189
5	2.104
7	3.075

These results should be considered very preliminary, as there were a number of factors that could have adversely affected the accuracy. The Reach coordinate may improve once we are able to calculate it with a closer VRS. The mission was collected with a relatively high GSD of 3.5cm/pixel, so it is difficult to pick the GCPs accurately.

Still, there are some conclusions we can draw from this data. Even without a good base station coordinate, the Reach system can produce very good scale accurate results. When paired with a higher quality coordinate, the Reach can produce very good absolute GCP coordinates. If a fixed position can be marked once by a survey grade GPS, then it can be used as a reference point for all missions in the same area, forever. It may also still be possible to obtain similar results with the Reach alone using the VRS network or Precise Point Positioning.

We’ll run more tests to verify the accuracy, but initial results are very good. We’re now making the first deliveries of the Reach system to select clients before a wider release in the very near future.

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