RL for robotics: Where do you spend the most time outside of training?

Hey 👋 I’m doing a Cornell Master’s project to understand what actually slows down robotics teams once a policy is trained.
Most papers focus on training. In practice, a lot of engineering seems to go into things like:

– sim-to-real transfer
– policy evaluation
– debugging failures on hardware
– testing and validation
– building simulation environments
– reproducing bugs
– benchmarking new policies

I’m collecting data from researchers and engineers working with RL, behavior cloning, VLA/VLMs, or classical robotics stacks.

The survey takes about 4 minutes.
If you’ve deployed policies on real robots (or spent time trying to), your perspective would be especially valuable.

There’s also an optional follow-up interview with a $25 Amazon gift card for participants.