There was a somewhat recent discussion on VTOW, and the consensus is (as it always has been) that there is no use for machine learning in vex, given the limited processing of the brain and not much sensor information to process.
Here are the relevant quotes:
From Thomas | Hail
On the note about using “AI” in autonomous, I don’t think the v5 Brain can handle any remotely intensive ML application. You should however be using sensors in autonomous to make sure your routine is accurate and precise. decision making autonomous programs are extremely complicated and due to the isolated nature of both the VRC and VEXU auton periods I don’t believe having any decision making would be worthwhile due to the time it would take to code for not the greatest of gains. If you do want to check out robots doing decision making in a vex setting the VAIC competition is starting up this season which will be fully autonomous bots, most with complex onboard decision making
technically the v5 brain has enough hardware to make it possible to run a ml model on tensorflow lite
- no decision making (or obstacle avoidance) needed in VRC/VEXU
- I have no idea what you would use ML for, the sensors aren’t great and you don’t have a ton of data in the first place
- the v5 can’t train a model, so you will have to find a way to simulate/get data from the v5 and train on a pc