Zipeng Fu (@zipengfu) / X

Zipeng Fu

353 posts

Zipeng Fu

@zipengfu

Stanford AI & Robotics PhD @StanfordAILab | Past: Google DeepMind, CMU

Palo Alto, CA

Joined February 2014

Pinned
Zipeng Fu
@zipengfu
Jan 4, 2024
Mobile ALOHA's hardware is very capable. We brought it home yesterday and tried more tasks! It can: - do laundry👔👖 - self-charge⚡️ - use a vacuum - water plants🌳 - load and unload a dishwasher - use a coffee machine☕️ - obtain drinks from the fridge and open a beer🍺 - open
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3M
Zipeng Fu
@zipengfu
Jan 3, 2024
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 @tonyzzhao, @chelseabfinn
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1.6M
Zipeng Fu
@zipengfu
Sep 11, 2023
Introduce our #CoRL2023 (Oral) project: "Robot Parkour Learning" Using vision, our robots can climb over high obstacles, leap over large gaps, crawl beneath low barriers, squeeze through thin slits, and run. All done by one neural network running onboard. And it's open-source!
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Zipeng Fu
@zipengfu
Jun 24, 2024
Our 6ft humanoid HumanPlus at Stanford can autonomously put on a Nike skateboard shoe, tie shoelaces, stand up and walk. Using two transformers & dual RGB vision, it integrates two recipes of general robotics end-to-end: - imitating humans in real world - large-scale RL in sim
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Zipeng Fu
@zipengfu
Jun 13, 2024
Introduce HumanPlus - Shadowing part Humanoids are born for using human data. We build a real-time shadowing system using a single RGB camera and a whole-body policy for cloning human motion. Examples: - boxing🥊 - playing the piano🎹/ping pong - tossing - typing Open-sourced!
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230K
Zipeng Fu
@zipengfu
Jun 13, 2024
Introduce HumanPlus - Autonomous Skills part Humanoids are born for using human data. Imitating humans, our humanoid learns: - fold sweatshirts - unload objects from warehouse racks - diverse locomotion skills (squatting, jumping, standing) - greet another robot Open-sourced!
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Zipeng Fu
@zipengfu
Jan 3, 2024
Replying to @zipengfu
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
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Zipeng Fu
@zipengfu
Dec 29, 2023
Mobile ALOHA 🏄 is coming soon! Special thanks to @tonyzzhao for throwing random objects into the scene, and @chelseabfinn for the heavy pot (> 3 lbs) ! Stay tuned!
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Zipeng Fu
@zipengfu
Jan 3, 2024
Replying to @zipengfu
We open-source all the software and data of Mobile ALOHA! Project Website 🛜: mobile-aloha.github.io Code for Imitation Learning 🖥️: github.com/MarkFzp/act-pl… Data 📊: tinyurl.com/mobile-aloha-d…
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Zipeng Fu
@zipengfu
Jan 4, 2024
Replying to @zipengfu
The robot is teleoperated in the video (for now!) Checkout @tonyzzhao's thread on how we design the low-cost open-source hardware and teleoperation system!
Tony Zhao
@tonyzzhao
Jan 3, 2024
Introducing 𝐌𝐨𝐛𝐢𝐥𝐞 𝐀𝐋𝐎𝐇𝐀🏄 -- Hardware! A low-cost, open-source, mobile manipulator. One of the most high-effort projects in my past 5yrs! Not possible without co-lead @zipengfu and @chelseabfinn. At the end, what's better than cooking yourself a meal with the 🤖🧑‍🍳
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95K
Zipeng Fu
@zipengfu
Apr 15, 2022
Super excited to announce that I will join @StanfordAILab for my PhD as a Stanford Graduate Fellow to keep exploring in Robotics & AI. Deeply grateful to my advisor @pathak2206, mentors Jitendra Malik & @ashishkr9311 for their huge support and guidance! Will miss @CarnegieMellon
Zipeng Fu
@zipengfu
Jan 5, 2024
Good time spending days and nights with @tonyzzhao at the brand new Stanford Robotics Center and @chelseabfinn's lab. Much funnier when sound on!
Tony Zhao
@tonyzzhao
Jan 5, 2024
Robots are not ready to take over the world yet! @zipengfu and I just compiled a video of the dumbest mistakes 𝐌𝐨𝐛𝐢𝐥𝐞 𝐀𝐋𝐎𝐇𝐀🏄 made in the autonomous mode 🤣 We are also planning to organize some live demos after taking a break. Stay tuned!
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Zipeng Fu
@zipengfu
Jan 3, 2024
Replying to @zipengfu
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.
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Zipeng Fu
@zipengfu
Jan 3, 2024
Replying to @zipengfu
Want to dive deeper into the hardware of Mobile ALOHA? Check out 𝐌𝐨𝐛𝐢𝐥𝐞 𝐀𝐋𝐎𝐇𝐀🏄 -- Hardware from co-lead @tonyzzhao!
Tony Zhao
@tonyzzhao
Jan 3, 2024
Introducing 𝐌𝐨𝐛𝐢𝐥𝐞 𝐀𝐋𝐎𝐇𝐀🏄 -- Hardware! A low-cost, open-source, mobile manipulator. One of the most high-effort projects in my past 5yrs! Not possible without co-lead @zipengfu and @chelseabfinn. At the end, what's better than cooking yourself a meal with the 🤖🧑‍🍳
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21K