Bimanual Manipulation Explained: Why Two Arms Are Harder Than One
I use ALOHA's cup-opening task to explain why bimanual manipulation demands coordinated motion, timing, force, training data, and feedback.
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Articles
Explore practical guides and perspectives on humanoid robot training data and embodied AI, including collection methods, simulation, evaluation, licensing, hardware, and the datasets shaping modern robot learning.
34 Articles · Page 2 of 3
Robotics Is Moving Beyond VLA: The Closed Loop Comes Next
A VLA can tell a robot what to do. One shoelace attempt shows why prediction before action, feedback during it, and learning after failure must work together.
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Physical AI Training Data: Why Humanoid Robots Need More Than Video
Physical AI training data needs more than video: humanoid robots also need actions, touch, failures, body state, and evidence from the real machine.
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Applications of Humanoid Robots: What Is Working in 2026
An evidence-ranked guide to humanoid robot applications in factories, warehouses, homes, healthcare, services, hazardous work and space.
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What Is a Humanoid Robot? Definition, History and Future
What is a humanoid robot? Learn how human-like robots work, where they are used, their history, current trends, limitations, and where the field is heading.
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Robot Learning Tutorial, Simplified for Programmers
A programmer-first guide to LeRobot datasets, classical control, reinforcement and imitation learning, generative policies, async inference, and VLAs.
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What Is Embodied AI? How AI Learns Through Action
Embodied AI explained through the feedback loop between perception and action, with a clear view of what today's robots can and cannot do.
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What Is Egocentric Data? How First-Person Video Trains Robots
A signal-by-signal comparison of head-mounted video, tracked human capture, and robot-mounted first-person data for humanoid robot training.
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Claude Plays Robotics. The Trash Can Still Wins.
Anthropic's Claude robotics study shows a model becoming physically consequential before it becomes physically reliable.
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NVIDIA SimFoundry and the Next Real-to-Sim Data Loop
An analysis of NVIDIA Research's SimFoundry, its single-video real-to-sim pipeline, digital cousins, reported sim-to-real results, and the provenance questions behind generated simulation data.
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Humanoid and Egocentric Data Marketplaces: Where to Source Physical AI Training Data
A practical map of humanoid robot, egocentric video, LeRobot, teleoperation, and physical AI data marketplaces, vendors, open datasets, and commercial licensing caveats.
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Synthetic Data Generation for Robot Training Data: Methods, Uses, Advantages, and Disadvantages
A practical guide to synthetic data generation for robot training, covering domain randomization, synthetic demonstrations, procedural scenes, synthetic labels, generative augmentation, sim-to-real risks, and buyer diligence.
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