sled-umich/RACER-augmented_rlbench

Rich language-guided failure recovery trajectories augmented from RLbench. We gather the training and validation expert demos from RLbench as $D^{expert}$ (2250 episodes in total), perturb each episode five times and filter unsuccessful trajectories to obtain $D^{recovery+lang}$ (10,159 episodes in total). Both simple and rich language instructions are generated by prompting GPT-4-turbo for comparative study. There are 18 tasks in total, 100 episodes for training set, 25 for validation set:… See the full description on the dataset page: https://huggingface.co/datasets/sled-umich/RACER-augmente

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