This work will be presented at the Robotics: Science and Systems (RSS) conference in Los Angeles.

Project Page: imle-policy.github.io
Paper: roboticsproceedings.org/rss21/p158.pdf
Code and Datasets: github.com/krishanrana/...

We extended this approach to the conditional action generation setting and found that these attributes carried over, enabling us to learn performant visuomotor policies from as little as 17 demonstrations.

Are Diffusion and Flow Matching the best generative modelling algorithms for behaviour cloning in robotics?

✅Multimodality
❌Fast, Single-Step Inference
❌Sample Efficient

💡 We introduce IMLE Policy, a novel behaviour cloning approach that can satisfy all the above.

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