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Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

in partnership with...


Teleoperation System

We introduce ALOHA: A Low-cost Open-source Hardware System for Bimanual Teleoperation. With a $20k budget, it is capable of teleoperating precise tasks such as threading a zip tie, dynamic tasks such as juggling a ping pong ball, and contact-rich tasks such as assembling the chain in the NIST board #2.

Learned Policy

We introduce Action Chunking with Transformers (ACT). The videos below show real-time rollouts of learned policies, imitating from only 50 demonstrations for each task. ACT predicts a sequence of target joint positions given RGB images and proprioception. For the three following tasks, ACT obtains 96%, 84%, 64% success respectively.

Observations during policy execution

We show example image observations (i.e. the input to the ACT policy) at evaluation time. There is a total of 4 RGB cameras each streaming at 480x640. Two of the cameras are stationery and the other two are mounted on the wrist of robots.

Slide Ziploc

Slot Battery

Open Cup

Interested in bringing this project to your University?

Fill out the contact information or give us a call: 866-478-3731

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