LEAP Hand: Low-Cost, Efficient, and Anthropomorphic Hand for Robot Learning — mentioned by claytonwramsey

Fri, 03 May 2024 22:22:27 GMT

Your edit is roughly correct. It's a bit odd that they're comparing a single human-made policy with the very best of the DrEureka outputs; in practice, I would expect to make multiple different reward functions and then do validation on the functions and hyperparameters based on the resulting trained models. However, their comparison isn't necessarily wrong, since it seems (I could be wrong) that they used the reward function from prior papers in the field of policy learning. If you're interested in methods for actually learning policies for these sorts of dynamic motions, note that this…

Paper and discussion history. A mention is not an endorsement.

LEAP Hand: Low-Cost, Efficient, and Anthropomorphic Hand for Robot Learning · HackerPapers discussions

LEAP Hand: Low-Cost, Efficient, and Anthropomorphic Hand for Robot Learning — mentioned by claytonwramsey