Robomimic
Visit Toolrobomimic is a modular framework for robot learning from demonstration. It provides broad demonstration datasets and offline learning algorithms to train robots.
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robomimic is a modular framework for robot learning from demonstration. It provides broad demonstration datasets and offline learning algorithms to train robots.
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Also listed in
About
robomimic is a comprehensive, modular framework designed for robot learning from demonstration. It offers a wide array of demonstration datasets specifically collected for robot manipulation domains, alongside robust offline learning algorithms to effectively learn from these datasets. The primary goal of robomimic is to enhance the accessibility and reproducibility of robot learning research, enabling researchers and practitioners to benchmark tasks and algorithms consistently. This framework facilitates the development of the next generation of robot learning algorithms, supporting features like Diffusion Policy, multi-dataset training, language-conditioned policies, and integration with robosuite and DeepMind MuJoCo bindings. It also supports various observation modalities, pre-trained image representations, and logging with wandb.
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