Robots that learn to cook, open cabinets, and ride elevators — from watching people
This project shows a way for robots to learn real tasks by watching humans drive them, using a low-cost setup so more labs or makers can try it.
The robot wears two arms and moves its whole body, not just hands, so it can do bigger jobs — it is bimanual and controlled with the whole base, which helps reach hard spots.
People guide the robot to collect examples, and those examples teach the robot to copy the actions.
Mixing new mobile examples with older bench-top examples makes the learning much better, even when only a few tries are shown.
With just about fifty demos per task the system can jump to near 90% success on messy kitchen jobs.
It can saute and serve a shrimp, open a heavy two-door cabinet, call and get into an elevator, or lightly rinse a pan at the sink.
This work brings robots closer to helping with simple, real chores by learning from human moves, and it makes that learning easier and cheaper to do.
Read article comprehensive review in Paperium.net:
Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-BodyTeleoperation
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