A drone that calculates coordinates using a camera and Google Maps

Each 5 days, a satellite from sentinel mission take a picture of your location. It's 8 days for landsat mission. Those are publicly available data (I encourage everyone to use it for environment studies, I think any software people that care about the future should use it).

It's obviously not the same precision as the google map, and it needs update, but it's enough to take in account seasonal change and even brutal events (floods, war, fire, you name it).

Occurred to me that in a war or over the water this wouldn’t be useful. But I think it will be a useful technology (that to be fair likely already exists), in addition to highly accurate dead reckoning systems, when GPS is knocked out or unreliable, as secondary fall back navigation.

I guess if it's really a possibility for military use they won't use google maps...

So the article is fraud.

Seems like a really good use case for downtown anywhere, because otherwise the buildings make your gps go haywire and navigation sucks. Though I will say, and certain providers try not to admit this too loudly, a much better way to handle those downtown scenarios is to map out and keep track of the location of WiFi signals and use their relative strength as detected by your device to triangulate your position instead. Works really well in super dense areas like cities

First generation Tomahawk did this (TERCOM) but later blocks acquired image matching guidance which is presumably today very advanced (I heard about it first around 1988).

From the original link for this post:

    The drone uses a camera mounted underneath it to position itself with imagery from Google Maps highlighting similarities in the images to get a rough estimate of the co-ordinates. Doesn’t Google Maps still require internet, you may ask?

    Google Maps allows users to download segments of maps ahead of time, usually for use when you are travelling or camping out in remote areas. In this instance, the team used this feature to their advantage, allowing the drone to continue operating regardless of having a GPS satellite connection.

The entire point of such a build is to operate autonomously with local data in the presence of jamming | signal loss for other reasons.

You can download osm and satellite datasets for thousands of square miles in a few GB. If you need very high resolution satellite it's gonna be on the order of 1GB per ~10sqmi depending on what you're up to.

Storm Shadows/SCALP-EGs and Taurus have that too

Lancet drones just use mobile phone with an Ukrainian SIM for navigation.

That's called dead reckoning[1].

The Kalman filter[2], which pops up on this site rather frequently, is often used for updating the current state.

The issue is that sensors are not perfect. Not just noise, but they might be slightly off in one direction more often compared to another for example. These errors accumulate, and so you can be quite off after not that long of a time.

[1]: https://en.wikipedia.org/wiki/Dead_reckoning

[2]: https://en.wikipedia.org/wiki/Kalman_filter

You can only measure acceleration using an accelerometer. A gyroscope is technically still useful here for removing the gravity vector from the data accelerometer is reporting.

measured acceleration = true acceleration + accelerarion error

velocity = (true acceleration)t + (accleration error)t + v_0 + v_0's error

position = (true acceleration)t^2/2 + (acceleration error)t^2/2 + (v_0)t + (v_0's error)t + p_0 + p_0's error

The error grows quadratically meaning that this equation can only be used for a brief amount of time.

Your position would drift insanely fast. In a drone, gyro readings and velocity are being used in the ekf2 filter to calculate your position. But a GPS position is required to prevent longtime drift.

Obviously, in GPS deprived situations, you have to think about alternatives.

This approach is used very commonly - e.g. every airliner, submarine and military plane will have such a navigation system (augmented with GPS these days obviously).

The issue is that the system naturally drifts, so over time it will accumulate error which has to be mitigated somehow (e.g. in military equipment with finding a known landmark and fixing on it).

The so-called INS systems are quite the marvel of mechanical technology: https://en.wikipedia.org/wiki/Inertial_navigation_system

I wonder: have you tried googling the answer for your question?

When searching for "accelerometer navigation", the first result is https://en.wikipedia.org/wiki/Inertial_navigation_system

Don't be lazy.

Yes, this is how navigation was done "in the past", without GPS, using inertial navigation systems. And pilots would recalibrate their position along the way or before arriving "on target" using known landmarks. The fancier systems could recalibrate using known star positions.

That double integral will get you with the noise unfortunately

In an aircraft, your "velocity" is usually the airspeed. This is often a lot different from the true ground speed.

The unknown part is drift caused by measurement error, which will stack up very quickly.

The story is that these young engineers built a 500$ drone that consumes this kind of data to do mapping. In 24 hours for a hackathon no less.

If the US government didn't already have this kind of tech, they would spend millions just for the same prototype they built. And probably tens or hundreds of millions for a final product.

I think that's a story

It's easy to shallowly dismiss work with a metaphor for how it works. LLM training is like a marble rolling down a valley. But hacking together a working proof of concept warms the heart.

>if the area is so "remote" it doesn't have GPS coverage

Or if GPS signal is being jammed.

>imagery quality is going to be garbage

Presumably, this relies on fairly limited compute resources, so it maybe probably downscales the image from it's camera to something like 256x256. Also, for machine vision stuff, too detailed an image can produce a lot of noise, so you'd need to pass it through some kind of low-pass filter anyway.

GPS is calculated from signals from a range of satellites far above us in orbit in space. It's not like cellular towers with coverage. There are no real remote areas with GPS - some areas and times of day will have less satellites overhead so calculating a position will be harder. There's more and more of these satellites (from usa, russian, eu, china etc) and modern chips will try calculate position from the signals from many of them rather than one "species"

But yes, remote areas will have less mapping imagery quality because they are remote and uninteresting and don't have roads or people or companies to buy ads on the map. They will buy cheaper imagery in remote areas.

In the context - a hackathon sponsored by the US Department of Defense - it has great utility. GPS (and any radio-based location system) is quite vulnerable to denial by enemy jamming. This technique would by extremely relevant in a war between peers, and probably provides a much lower cost option than high-precision inertial navigation systems.

Tangentially, this isn't really new - ground-pointed RADAR system combined with a good terrain dataset can also be used.

A small team managed to implement relocalisation (the technical name for this) in 24 hours is reasonably interesting.

If you want to try yourself you can use colmap (https://colmap.github.io/faq.html#register-localize-new-imag...) to do the same thing. I suspect that colmap not only does lat:lon but gives you a heading as well. (well I know it does, thats how it )

Now, had they made it happen _on the drone_ that would be more interesting. It looks like it was a simulated flight, especially as there is no rolling shutter wobble. Moreover, if you want real time, you need a monster GPU, unless they've done something clever.

Low cost weapons systems

I’m probably being a little over-pedantic, but I think a fail-safe refers to a feature that puts a device in a safe state when it fails. For example, a good fail-safe device for a drone could be one that navigates it toward the ground and into a somehow out of the way location (away from people or roads where it could be a hazard).

This seems more like a potential device recovery feature.

If anything, it is a fail anti-safe… moving around with degraded navigation is always worse, right? Might miss the fact that you’ve entered restricted airspace…

Interestingly it wouldn’t need satellite imagery. It could be taking and stitching its own image as it flies, then use that imagery to navigate by.

It would also let you do some interesting goal based nav, like, “Fly to that meadow”

Assuming loss of GPS, no, not fail-safe. Weather conditions (or anything that obscures a view of terrain) can cause this type of navigation to fail.

For example: pre-load satellite images and restrict navigation to radius covered by said images. In case of GPS failure, fail-safe to using image navigation for getting back "home".

Not required; assume you are not being jammed in those cases.

what happens with changes due to some natural events (Say flooding etc) ?

It’s multiple parts so multiple printers, I’ve printed some plane parts from lightweight PLA and this seems pretty reasonable to me. Especially so if you imagine prior experience and multiple people. It would get tricky if you had to iterate the design though.

Bambu carbons print that fast, and I think that's what they had at the gundo hackathon.

Unless your drone somehow makes it to Antarctica that would be hard to imagine happening, and even if it did, it could just continue on in one direction until it sees a feature again. Or fly higher. I’ve driven across the Great Lakes when frozen but even from the ground there are landmarks you can see.

People usually don't care about flying drones over areas where there is nothing to look at.

In a sense, they are right. There are several coordinate systems, but the one everyone uses (WGS84) was developed around the time of GPS and intended to be used for that purpose.

So GPS coordinates isn’t really a bad way to describe them.

A while back I saw web feeds described as “like podcasts, but for reading”.

X threads aren't unfortunately very useful for people who don't have account on X. Linking to the original source is much better. If the original source is only X thread, authors should reconsider their life choices. It's never too late.

Ok, we've taken GPS out of the title above.