HumanPlus robot can go from playing piano to ping-pong to boxing

Researchers at Stanford University have created an innovative humanoid robot called "HumanPlus" that can learn and perform a wide range of tasks by observing human actions. This breakthrough in robotics brings us one step closer to developing truly versatile and adaptable machines.

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Built on Unitree's H1 robot base, with hands from Inspire-Robots and custom wrists, HumanPlus stands 5 feet 9 inches tall. It features a 6-DoF (degrees of freedom) hand, which includes one degree of freedom for each of the index, middle, ring and little fingers, plus two degrees of freedom for the thumb. This configuration allows for complex hand movements and manipulations.

The robot also has a 1-DoF wrist, which means it can rotate in one plane, likely allowing for up and down or side-to-side movement, calculated using the relative rotation between the forearm and hand global orientations.

It features 33 degrees of freedom, two RGB webcams mounted on its head, a finger force capacity of up to 10N, an arm payload of up to 16.5 pounds and leg motor torque of up to 360Nm.

N stands for Newtons, which is the standard unit of force. 10N means the robot's fingers can exert a force of up to 10 Newtons. This is equivalent to about 2.25 pounds-force, indicating the gripping strength of the robot's fingers.

Nm stands for Newton meters, the standard unit for torque. 360Nm means the motors in the robot's legs can generate a rotational force of up to 360 Newton meters. This is a significant amount of torque, indicating powerful leg motors capable of performing tasks that require substantial force and movement.

These specifications give us an idea of the robot's grip strength and leg power capabilities, which are crucial for various tasks like manipulation and locomotion.

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HumanPlus utilizes a single RGB camera and a whole-body policy to clone human motion in real time. The robot can learn various activities, including boxing, playing the piano, ping-pong, tossing objects and typing.

The system requires approximately 40 hours of human movement data to learn a task and then reproduce it step by step.

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HumanPlus has also demonstrated remarkable capabilities in various tasks, including wearing shoes and walking, unloading objects from warehouse racks, folding clothes, rearranging objects, typing and greeting another robot. The robot achieved success rates of 60%-100% in these tasks using up to 40 demonstrations.

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While HumanPlus represents a significant advancement in humanoid robotics, it comes with a substantial price tag. The researchers estimate the cost of building a working model at approximately $107,945. However, given its versatility, it may still be one of the more cost-effective options currently available on the market.

One of the most notable aspects of HumanPlus is its open-source design. The researchers have released a GitHub repository, allowing others to build similar models and contribute to its development.

HumanPlus's ability to learn from human demonstrations and perform a wide range of tasks showcases the potential for more adaptable and versatile robots in the future. The open-source nature of the project encourages collaboration and further development, which could accelerate progress in this field.

As humanoid robots continue to evolve and improve, we may see them playing increasingly important roles in various industries, from manufacturing and healthcare to entertainment and education. While the current cost of HumanPlus may limit its immediate widespread adoption, ongoing research and development could lead to more affordable versions in the future, potentially revolutionizing how we interact with and utilize robotic assistants in our daily lives.

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