Hi all,
looks that with the spread of processing methods and technology,
we can make things that were available only to national security agencies, once upon a time.
Take a look at the maps of the flight made May 18th:
one day to fly, one day to upload, one day for processing, (one day for grill party), one day to download.
Few of you might remember the 3km long flight with EasyStar (a single line), stitched with Microsoft ICE.
The map above is 2.2x2.2km. It took 746 photos to make this map.
Funny fact: if the aircraft would fly straight, the surface covered would be >16km2 instead of just 4.5km2 (null side overlap).
The overlap used was 70% side, 80% along.
Comments
@Loljze "with good GPS and weather conditions a 3-5 cm absolute accuracy of flightline can be achieved."
What is the reference measurement? It could be you are using a GPS for a few KUSD.
"Maybe some additional IMU (in 5000€ range)"
...and a Hellfire or two ;-) This is more than half of Pteryx Lite pricing and a quarter of Pteryx Pro. At the current market conditions where large companies sit comfortably in a cessna and the newcomers believe you can make it of rubberbands and RC model, we are targetting the low price regions. We have the equipment for startups that want to challenge the larger companies with much less startup capital.
I think that we didn't understand each other. I was talking about GPS+RTK method only in GCP acquisition. In Pix4d workflow GPS coordinates just helps to order images for faster tie point search. In the worst case I doubt that they even need GPS coordinates. They can probably produce so called relative positioned orthophoto. Certainly accurate position and orientation helps significantly in bundle adjustment (less iterations) but it is unnecessary if they are using SfM principles and this is what revolutionize photogrammetry and UAV usage.
I'm working in professional photogrammetric company. We are not using GPS RTK in flying. We are using as John Bond mentioned, carrier phased GPS (L1,L2) and differential based GPS postprocessing. Using a civil grade IMU (256 Hz, 0.1deg/h drift) with good GPS and weather conditions a 3-5 cm absolute accuracy of flightline can be achieved. Sometimes it is good enough to produce an orthophoto without additional image orientation. But all this equipment is not cheap and I'm convinced that UAVs like Pterxy can replace it in an small area orthophoto production workflow. Maybe some additional IMU (in 5000€ range) with Kelman's filtering to get more accurate projection centers, good GCPs coverage and we can be very near professional results.
The only thing I'm confused about is why you think "All flying GPS RTK or not RTK have horrible accuracy compared to ground measurement strictly because the most uncertain value, teh altitude, cannot be filtered out accurately in the air." There's nothing magical about the GPS receiver or antenna being on the ground versus in the air. It doesn't know, it doesn't care. GPS is used on rockets and spacecraft. Altitude measurements don't suffer.
The professional photogrammetric companies use differential (carrier phase based) GPS for a reason. GPS works at the speed of light. The dynamics of anything humans fly through the atmosphere are irrelevant. Sure it may take ~10+ millseconds to compute a position in real time, but the data that went into that position has a very, very accurate time tag. You can either predict forward what the position is at a given instant - say when a camera trigger sends a voltage pulse, or better interpolate the position accurately later during post processing. The limiting factor here is your shutter speed ( crank it up :) ) and ground speed - or get into motion compensated cameras, but we're not going there.
While Pix4d doesn't have any real technical data on their site they do say that, of course, differential GPS helps.
In your example the 746 GPS measurements are essentially averaged and some of the error does tend to cancel, but it's not as much as you might think. There could still be a bias of a meter or two. With carrier phase differential there might be a bias of a centimeter or two. This is where the improvement comes. Of course there are other errors involved, but this helps.
In most situations the addition of a few high quality GCPs to the processing would be the thing to do, but again the idea of no GCPs is what intrigued me.I think you are mixing things. It doesn't matters where the aircraft is relative to flight plan and how it maneuvers, it is precisely about if it is able to know the position when making a photo. All flying GPS RTK or not RTK have horrible accuracy compared to ground measurement strictly because the most uncertain value, teh altitude, cannot be filtered out accurately in the air. This variable of the error elipsoid cannot be flattened anymore and spreads overall horisontal precision since all you are truly measuring is time phase, what impacts all dimensions. Once you essentially liberate time-averaged 2D problem into 3D problem (because of accelerations along Z-axis that you never do on the ground), the GPS position error fit 'explodes'.
Then, even this low accuracy, is not dominant factor towards IMU and mounting precision.
"When Pix4d does its adjustments the only way it can add georeferencing info is via the GPS coordinates you give it."
Exactly. In fact, it takes 746 measurement estimations out of 746 photos and the errors cancel out to some degree. It works that much that I am observing about 1m accuracy. But their initial accuracy per photo is a few meters at best, RTK or not. Military achievements suggest it is almost impossible to make it better and error contribution suggests there is no 80/20 rule, the stupid mounting screw and uneven lenses contribute as much as GPS accuracy.
The accuracy of RTK or the post-processed version is actually better in an aircraft compared to ground work. Excellent satellite visibility and little multipath give a GPS antenna in the sky an advantage over one on the ground. While it might not be a large advantage - when the ground isn't too cluttered - airborne RTK certainly isn't worse.
Now if you are talking about navigating a UAV precisely that will be more a function of your control system. If you've ever seen a rotorcraft maneuver with RTK vs autonomous GPS you will appreciate the difference.
When Pix4d does its adjustments the only way it can add georeferencing info is via the GPS coordinates you give it. If you can change their uncertainty from a few meters to a few centimeters that will help the situation.
PPL seem to not understand that from 300m AGL the main limitation is IMU accuracy, when we talk about non-military toys under 100KUSD or so. The projected precision is poor, about a few meters at best.
Also not everybody realizes that RTK from a moving plane is FAR from delivering the same precision as on the ground, because the true altitude is moving randomly up and down due to turbulence.
A simple projection errors are some 5-25m (occasionally probably 50m) are typical even for machines like Skylark which are military drones used for artillery fire targetting and similar. Therefore I don't agree with geodesic obsession of taking RTK from the air. The GPS amounts to maybe 20-30% error (you can shave maybe half of it due to 3D motion and accelerations or rather 3D jerks, certainly not to a few cm area), the rest are IMU and camera calibration+mounting. Don't make your camera mount of foam so it is different in each flight and you already win more than all those RTK processings. Sub-meter projection accuracy you cannot avoid without mechanical gyros, large scale camera calibrating range and similar things. In practice - forget it, a toy that uses it is very high quality military mini UAV and it is not going to be 10x cheaper in the next decade for the same reason that passenger jets are not 10x cheaper today than 2 years ago.
The precision is achieved statistically and by cross correlating GPS through optical matching.
I cannot say if the accuracy is sub-meter (no ground equipment), but is some 50 times better than Google Earth accuracy which tends to be somewhere around 50m 100km from larger Polish cities.
Another holy grail of photogrammetry is dispensing with the ground control points. Getting GCPs in an area with easy ground access is no big deal, but for harder to access areas skipping the GCPs and letting the UAV do all the work is kind of nice.
Certainly with a few accurate (cm - level) GCPs your overall absolute accuracy is going to be in the few decimeter range for the most part. There may be certain circumstances where the Pix4d methodology doesn't work so well, but with all the generated contrast GCPs distortion is greatly reduced and a non-metric (uncalibrated) camera works quite well.
I wonder what the absolute accuracy would be like with some highly accurate UAV positions? The hardware is cheap and relatively lightweight. A Ublox Lea4T attached to a Sparkfun Logomatic and you've got 10 Hz GPS carrier phase data that will process to a few cm accuracy. Yes, the "catch" is in the processing if you haven't done it before, but there are free tools. Update the UAV position data via time tags and what type of improvement do you see in Pix4d's accuracy? Are we sub-meter now?
Your actual application will determine if you really care, but sub-meter absolute position accuracy without GCPs and using inexpensive equipment would be pretty cool.
@Lojze The parameters found magically by pix4d are not published but its internal machinery. However I have in-house camera devignetting, whitebalance equalizer and lens corrector (geometrically calibrated), I found that it is cool to upload that to any application I have and it stiches better (in my ftp there are examples in directories _proc which are processed /lens corrected).
I have removed 3 or 5 slightly blurred photos from the image (there was some turbulence and there was only 1/400 exposition if I remember well).
I have no access to RTK GPS, I am not national geodesic research institute (yet).The camera is Canon S90 (Sometimes we fly with double payload, one IR one visual).
So far my major showstopper was the fact that flights longer than 1 hour usually have changing whitebalance and lighting conditions (you fly with fixed settings or else everything goes in all directions during automatic whitebalancing and exposition). Therefore you accept some gradual brightness falloff or rise and counter it after the flight if you really have to fly in the evening - and then the results are as on the image. But more than 2 h starts being difficult for those lighting reasons, camera battery endurance etc (small problems start to pile up).
BTW I would be happy to find a kind of automatic blur detector or a mathematical formula that is not fooled by changing landscape.
The holly grail in photogrammetry is around 0.3 pixel error. Krzysztof do you know what kind of camera parameters (principal points, focal distance, distorsion,...) does Pix4d estimate? I think that with at least 4 GCP (Ground Control Points) loactions measured using RTK GPS (~3cm accuracy), adequate flight pattern (in your case: two or tree crossed flightlines) and calibrated camera (for a good estimation start) the absolute accuracy should be in a range of 10-30 cm (using 10 cm GSD images)
As far as I know UAV imaging the only really big problem can be image blur and with it, the correct tie point positioning. This can be a serious party breaker. But without quality GCPs is impossible to know that.
Absolute accuracy better than 1-2m on a few major crossings. Unable tell better (Garmin Geko).
Anyway the pixel size is 10cm (just to get something round) and since we are not expecting 10cm absolute accuracy, when you do comparative analysis, you might need to do optical matching first.
You must keep in mind that teh result is a projection of 746 coordinates from 10Hz GPS plus dead reckoning at 32Hz, flying both sides and IMU projection - it may go down to a decimeter accuracy in certain areas, but mostyl I woudl say 1-2m. There is least suqare fit report on that processing that says:
Table 2: Bundle block characteristics.
mean reprojection error 0.903891 [pixels]
Table 3: Localisation accuracy in metres without using ground control points.
geo localisation variance rho [m]
latitude direction (x) 2.28658
longitude direction (y) 2.04749
altitude direction (z) 6.34011
(altitude direction variance was a few times lower on flat terrain)
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