(no title)
mentar
|
7 months ago
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'
AndrewHart|7 months ago
monegator|7 months ago
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
numpad0|7 months ago
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.
AlotOfReading|7 months ago
The ITAR stuff is way more fun though. It's great to read between the lines for the intended customer in the datasheet.
contingencies|7 months ago
thijson|7 months ago
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.