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Thank you for posting this. This question is great for our Discussions section. I'll move the post there. I think probably it makes better sense to reset after the object is no longer in play for the robot, as there's nothing to learn in subsequent frames. Sensors should help. |
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Collecting Failed / Recovery Demonstrations for Fine-Tuning GR00T
Hi everyone,
First of all, thank you for the great work you’re doing with Isaac Lab and GR00T — it’s been really exciting to experiment with.
I’ve been fine-tuning GR00T on my own dataset of a G1 robot collected with AVP, and I noticed something: when an object (for example, one held in hand) accidentally falls, the model keeps trying to complete the task without the object instead of recovering or retrying.
I was therefore wondering if it makes sense to also include failed demonstrations, or even better, recovery demonstrations (the object slips at first, then I regrasp it) into the dataset for finetuning GR00T ?
If so, could anyone please point me to the direction of how many recovery examples you would recommend collecting to meaningfully improve the model’s behavior?
I was also wondering, will I be able to use these demonstrations in connection with GR00T-Mimic for synthetic dataset generation, or do you think some issues will arise?
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