DJI Waypoints Repeatability Test - Logs vs Real Flight Path (Mini 5 Pro & Mavic 3 Pro)

[trisen1981]

Hi everyone,

I ran a controlled waypoint repeatability test using the same mission flown multiple times on:

• Mini 5 Pro & Mavic 3 Pro
• Day and night flights
• Planned in Litchi Mission Hub
• Analyzed using DJI logs, Google Earth paths, footage comparison, and photogrammetry

From the log perspective, everything appears clean and repeatable.
However, when comparing actual footage and reconstructed camera paths, things are… not as straightforward.


I documented the full process - flying, log analysis, Google Earth comparison, and camera reconstruction using photogrammetry - in this video:

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[Meta4]

Hi everyone,

I ran a controlled waypoint repeatability test using the same mission flown multiple times on:

• Mini 5 Pro & Mavic 3 Pro
• Day and night flights
• Planned in Litchi Mission Hub
• Analyzed using DJI logs, Google Earth paths, footage comparison, and photogrammetry

From the log perspective, everything appears clean and repeatable.
However, when comparing actual footage and reconstructed camera paths, things are… not as straightforward.


I documented the full process - flying, log analysis, Google Earth comparison, and camera reconstruction using photogrammetry - in this video:

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For more detailed information, see our cookies page.

Accept third party cookies

It's important to understand the limitations of your equipment.

Your drone's height measurements are all done with a barometric sensor that measures air pressure and all heights are based on the power up location = 0 metres.
Setting heights above ground in Litchi does not use actual height above ground level.
Your drone has no way to measure heights above the ground (except at close range).
Litchi is using a digital elevation model (DEM) for ground level all over the world - a sort of digital contour map with only approximate accuracy.
Then Litchi converts your desired heights above the approximate DEM ground level to heights relative to the launch point which the drone will understand.
The AGL heights are only going to be approximate reflecting the accuracy of the DEM and if you launch from different locations which are not at the same ground level, this will add another inaccuracy since all heights are from startup location = 0.
Changes in local atmospheric pressure from one flight to another might contribute to small differences in height too.
Also if you land the drone at the launch point and compare the inndicated height at landing to the start at zero feet, you will often see that there is drift in the indicated height for the duration of the flight.

With respect to horizontal positioning:
You've just demonstrated the variable (in)accuracy of consumer GPS.
Consumer GPS is unable to have repeatable pinpoint accuracy and is only is only accurate to +/- 2-3 metres.
The "drift" you noticed might be due to GPS inaccuracy rather than actual drone movement.
I would not expect wind to cause the sawtooth pattern you showed.

 

[trisen1981]

Thanks for the detailed response - I agree with a lot of what you wrote, especially regarding barometric altitude drift and consumer GPS limitations.

A few clarifications on why I decided to investigate this deeper:

• I’m not assuming AGL mode in Litchi represents true ground clearance - I’m aware it’s DEM-based and approximate. The comparison here is not “AGL accuracy vs reality,” but repeatability across identical missions flown from the same launch point.

• The horizontal offsets I’m seeing aren’t single-point GPS noise. When reconstructing the flights using photogrammetry and aligning the footage, the offsets are consistent over time, not random jitter. That’s what raised the red flag for me.

• I fully expect 2–3 m GPS variance. What surprised me was seeing up to ~8-10 m separation between reconstructed camera paths across repeated flights, while the logs themselves still appear nearly identical.

• I’m also not suggesting wind alone caused this - the issue shows up even in segments with minimal lateral correction and stable yaw/pitch.

That’s ultimately why I documented the whole process (logs, Google Earth paths, footage alignment, and camera reconstruction) instead of relying on any single data source.

Really interested to see any day-night transition with Enterprise drone + RTK with its cm accuracy- in the city environment