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Will we see humanoid robots in homes and businesses in the next few years?

CrossFormers introduce a transformer-based policy that can control a wide variety of robots across different tasks, including manipulation,

The Short Version Read 'Octo: An Open-Source Generalist Robot Policy' from UC Berkeley, Stanford, Carnegie Mellon, and Google DeepMind. Shift from task-specific learning to a flexible, generalist approach for training robots. Train on the diverse Open X-Embodiment dataset with its over 800,000 robot trajectories. Use Octo's transformer-based model to handle multiple robots, tasks, and environments without extensive retraining. Apply 'readout tokens' and 'action chunking' to p

Discover how variations in data collection impact imitation learning with the Aloha Kit. Explore experiments and access datasets on Hugging

Bi-ACT builds upon ACT with an approach that incorporates both position and force information.