Hi,
I’m a robotics engineer based in Australia, exploring ways to improve robotics perception models using targeted training data.
I’m curious how robotics teams currently handle perception failures, difficult edge cases, and collecting new training data.
Do you face challenges with this? Have you considered paying for external datasets or synthetic data to improve your models?
Thanks!
Jalal