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 Zipeng Fu and Chelsea Finn. At the end, what's better than cooking yourself a meal with the 🤖🧑‍🍳

How does 𝐌𝐨𝐛𝐢𝐥𝐞 𝐀𝐋𝐎𝐇𝐀 work? We seek to achieve a few more goals to augment the dexterity of the original 𝐀𝐋𝐎𝐇𝐀:

1. Moves fast. Similar to human walking of 1.42m/s. 2. Stable. Manipulate heavy pots, a vacuum, etc. 3. Whole-body. All dofs teleoperated simultaneously. 4. Untethered. Onboard power and compute.

To achieve these goals, we mount ALOHA to a mobile base designed for warehouses: Tracer AGV It can carry 100kg, move up to 1.6m/s, while costing only $7k To allow simultaneous arms and base control, we simply tether the operator to the mobile base, i.e. backdriving the wheels.

At test time when the robot is autonomous, the backdriving structure and the leader arms can be easily detached. This reduces the robot's footprint by 45% and shaves off 15kg in weight. The robot can reach 65cm to 200cm vertically, and 100cm away from its base.

We open-source all hardware and software of 𝐌𝐨𝐛𝐢𝐥𝐞 𝐀𝐋𝐎𝐇𝐀: Tutorial: Github: Project Website:

So, what new skills does 𝐌𝐨𝐛𝐢𝐥𝐞 𝐀𝐋𝐎𝐇𝐀 unlock when controlled by a neural network? Check out 𝐌𝐨𝐛𝐢𝐥𝐞 𝐀𝐋𝐎𝐇𝐀🏄 - Learning from Co-lead @zipengfu !

@zipengfu @chelseabfinn If imitation learning for really fine-grained control is ever going to work well, this is the hardware that's going to make it work - incredible demo! :)

@zipengfu @chelseabfinn Haha thanks Cem!!

@zipengfu @chelseabfinn But how did it taste?

@zipengfu @chelseabfinn Congrats Tony!! Very impressive :)

@zipengfu @chelseabfinn Thanks Jason!! Was great chatting during CoRL!