UC San Diego researchers develop an AI-enabled robot capable of learning and performing a Waltz by mirroring the movements of its human partner. This breakthrough showcases the potential of AI-powered robots to learn from human actions in a more organic and adaptable manner.
Researchers from the University of California, San Diego have developed an AI-powered robot capable of performing a Waltz by imitating the movements of its human partner. Remarkably, the robot successfully executed the ballroom dance without stepping on its partner's toes. To create this dancing marvel, the team first designed an AI model trained on human motion capture videos. This model was then integrated into two bipedal Unitree G1 robots.
Utilizing another model, these robots could analyze the motions of humans in front of them and replicate those movements precisely. The result is a humanoid robot capable of seamlessly walking, dodging, squatting, and dancing by simply copying human actions.While robotics researchers often showcase their creations performing impressive stunts, from intricate dance routines to daring parkour moves, most of these demonstrations rely on pre-programmed, highly choreographed scripts. This latest development, however, aims to teach robots to learn movements in a more organic and adaptable manner. To achieve this, the researchers began with a powerful AI brain, ExBody2, trained on a vast database of human motion capture data. ExBody2 was trained in a simulated environment using reinforcement learning until it developed a comprehensive understanding of how to articulate and move various parts of a robot body. The ExBody2 model was then implemented into a pair of robots equipped with an additional model that processed real-world physical data captured by the robots' cameras. This allowed the robot to quickly compare the movements it observed with its pre-existing training data.Videos of the robot in action demonstrate its impressive capabilities: pacing outdoors, sidestepping like an athlete, drawing circles with its arms, squatting, and even throwing punches. Some demonstrations showcase a researcher performing initial movements, followed by the robot accurately repeating the motion after a brief delay. Researchers highlight the adaptability of this approach, as it allows the robot to learn new movements without requiring extensive retraining for each new action. This mirroring capability could significantly accelerate robot training and reduce development costs. Furthermore, it paves the way for creating robots capable of interacting with humans in a more natural and intuitive manner, bringing us closer to the vision of general robot intelligence
Artificial Intelligence Robotics Humanoid Robots Motion Capture Dance Learning Adaptation
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