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Introduce 𝐌𝐨𝐛𝐢𝐥𝐞 𝐀𝐋𝐎𝐇𝐀🏄 -- Learning! With 50 demos, our robot can autonomously complete complex mobile manipulation tasks: - cook and serve shrimp🦐 - call and take elevator🛗 - store a 3Ibs pot to a two-door cabinet Open-sourced! Co-led Tony Zhao, Chelsea Finn
1,567,687 просмотров • 2 лет назад •via X (Twitter)
Комментарии: 10

Our robot can consistently handle these tasks, succeeding: - 9 times in a row for Wipe Wine - 5 times for Call Elevator - robust against distractors for Use Cabinet - extrapolate to chairs unseen during training

How do we achieve this with only 50 demos? The key is to co-train imitation learning algorithms with static ALOHA data. We found this to consistently improve performance, especially for tasks that require precise manipulation.

Co-training (1) improves the performance across all tasks, (2) is compatible with ACT, Diffusion Policy and VINN, (3) is robust to different data mixtures.

We open-source all the software and data of Mobile ALOHA! Project Website 🛜: Code for Imitation Learning 🖥️: Data 📊:

Want to dive deeper into the hardware of Mobile ALOHA? Check out 𝐌𝐨𝐛𝐢𝐥𝐞 𝐀𝐋𝐎𝐇𝐀🏄 -- Hardware from co-lead @tonyzzhao!

@tonyzzhao @chelseabfinn Awesome project, congrats!

@tonyzzhao @chelseabfinn Thanks Karol!

@tonyzzhao @chelseabfinn Did you eat the shrimp?! How did it taste!?

@tonyzzhao @chelseabfinn > cook and serve shrimp Are you trying to provoke me?

@tonyzzhao @chelseabfinn Can it?
