Robots Learn Sports by Watching Humans
Researchers from Stanford have developed a humanoid robot capable of learning complex tasks like playing piano, tennis, and boxing by mimicking human movements. This innovative approach could significantly reduce training time and costs for future humanoid robots, which may soon become integral to workplaces and homes.
A New Approach to Robot Training
Traditional methods of training robots involve dissecting human motion data into separate components, such as visual perception and limb control. This process is often time-consuming and inefficient for scaling up. Instead, Stanford researchers used a reinforcement AI technology model to train their robot, named “HumanPlus,” on 40 hours of human motion data in a simulation environment. The robot, equipped with a single RGB camera, then applied these lessons in the real world by shadowing human movements.
“By mimicking humans, humanoids can potentially tap into the rich repertoire of skills and motion exhibited by humans, offering a promising avenue towards achieving general robot intelligence,” the researchers explained.
Mimicking Human Movements
The robot performed a variety of tasks to demonstrate its capabilities. It successfully put on a shoe and walked, played ping pong, threw boxing jabs, and even typed the coding phrase “Hello World” on a keyboard. Depending on the complexity of the task, HumanPlus achieved a success rate of 60-100%.
HumanPlus: A Robotic Hybrid
HumanPlus is constructed from a combination of components from different manufacturers. The base body is a Unitree Robotics H1, with mechanical hands and wrists from Inspire-Robots and Robotis. A Razer webcam serves as its main visual input. The total cost for this robot is approximately $107,945. Instructions for building a HumanPlus robot are available on GitHub.
Implications for the Future
This novel training method arrives amid growing interest in commercial humanoid robots. Companies like Figure and Agility Robots are already testing their products in manufacturing and logistics. Tesla’s Optimus robot, which can perform tasks like washing dishes, exemplifies the potential of these robots to take on household chores. Goldman Sachs predicts that the global humanoid robot market could reach $154 billion by 2035.
Robots that learn through mimicry could revolutionize various industries. Like new human employees, these robots could be trained to perform specific tasks in different sectors. Their adaptability also holds promise for accessibility-focused robots designed to assist people with disabilities.
The future of humanoid robots looks increasingly promising, with mimicry learning paving the way for more efficient, versatile, and capable machines.
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