Georgia Tech researchers release EgoWAM to help robots learn from human videos by bridging the embodiment gap

Happy to share EgoWAM, led by @BaoyuLi6! Naive co-training on in-the-wild human data hurts policy performance. The reason is simple: humans move very differently from robots. EgoWAM bridges this gap through world representations: humans and robots may move differently, but achieve similar effects. We find that motion-centric representations and strong visual pretraining solve different parts of the embodiment gap.