Planning backward from a predicted final latent goal, instead of forward into the future, reduces error accumulation in long-horizon robot manipulation and outperforms prior planning methods on LIBERO-LONG.
Rvs: What is essential for offline RL via supervised learning? In International Conference on Learning Representations, 2022
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Efficient Robotic Policy Learning via Latent Space Backward Planning
Planning backward from a predicted final latent goal, instead of forward into the future, reduces error accumulation in long-horizon robot manipulation and outperforms prior planning methods on LIBERO-LONG.