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TidyBot: Personalized Robot Assistance with Large Language Models approach enables fast adaptation and achieves 91.2% accuracy on unseen objects in our benchmark dataset. We also demonstrate our approach on a real-world mobile manipulator called TidyBot, which successfully puts away 85.0% of objects in real-world test scenarios abs: project page:... show more

AK

502,269 subscribers

325,986 次观看 • 3 年前 •via X (Twitter)

教育科学技术新闻政治

Anya Rossi• Live Now

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7 条评论

Jimmy Wu 的头像

Jimmy Wu3 年前

Thanks @_akhaliq for sharing our work! I wrote a thread with more details here:

hardmaru 的头像

hardmaru3 年前

This is the easy part :) I need a robot that can clean the bits of pieces of jam, bread crumbs, diapers, and occasionally pieces of poo around various corners of the room, under the tables, and hidden in the kids play area of the house.

hgtp:// Alkimi $ADS $QNT Cat 🐈‍⬛ 的头像

hgtp:// Alkimi $ADS $QNT Cat 🐈‍⬛3 年前

How do I order one??

Defend Intelligence (Anis Ayari) 的头像

Defend Intelligence (Anis Ayari)3 年前

Really nice ! thank you for demonstrating this capability. LLM could then indeed be used as the "reasoning" block to achieves unseen world reasonning and allow tasks to get a better generalization to accomply them.

Dan Rockwell 的头像

Dan Rockwell3 年前

I felt like it was missing something..

St. Clair Newbern IV 的头像

St. Clair Newbern IV3 年前

Should be the standard upsell on all children. 😂

Astral Turf 的头像

Astral Turf3 年前

@ericjang11 Not very impressive really.

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161,453 次观看 • 2 年前