How does your system handle the massive variance in sensor quality (accelerometer, gyro, WiFi radio) between a high-end iPhone and a budget Android device? Does the 1m accuracy hold up across the board, or does it degrade gracefully? Getting this right seems critical for scaling to a 'billion people'
All of the videos shown on the speed-run of our technology is on 4 year-old Android devices, such as Samsung S21, Pixel 6 etc.. We always test and gather statistics on older devices to fairly represent what's available, rather than latest-and-greatest.
So, devices that were top of the line a few years ago. But what about budget devices? in the 100-200 range new? I remember my old xiaomi started literally running in circles as the phone heated up 10-15 minutes after starting navigation: If i stood still the position would move in a circle of a few meters of radius.
Incidentally, the devices you metion are what i also use to develop, because those line of products actually behave as they should, per documentation. But most bugs and crashes always come from budget and no name devices because both the hardware and firmware is crap
Peripheral chips aren't differentiated by user values like the end products that use them. You don't get more preciser sensors in high end phones. Everyone gets the same thing. You pay more only for more materials.
Sensors that are actually a lot better than standard offerings would also be subject to and/ofs of ITAR or EAR or MTCR or local equivalents thereof, so progress in IMU appears to have been stagnating a bit due to that issue. Sony Semiconductor Solutions had a Arduino IDE compatible clustered IMU board that they say you can see rotation of Earth in data, they ended up selling it with scary warnings and without any of the cool stuffs.
There's a fair bit of quality difference between different chips and better chips have gotten cheaper. More importantly, default filtering quality has improved with more powerful uCs on the IMU package, which is what most cheap phone vendors are probably using.
The ITAR stuff is way more fun though. It's great to read between the lines for the intended customer in the datasheet.
This is the correct answer. They're all the same. The notion that Apple has some kind of edge here is farcical.
There's something called a Kalman filter:
https://en.wikipedia.org/wiki/Kalman_filter
It can combine several inaccurate sources and output a result that is more accurate than any one of them.
I was at an Amazon Fresh grocery store, and saw squares in the ceiling that look like QR codes. I guess that's how they are mapping the store.