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Whether teleoperated or autonomous, whole body movements like picking objects from the ground are challenging for humanoid robots. A UC San Diego paper introduces a framework that combines sim-to-real RL and trajectory optimization for adaptive, real-time whole body control.

The Humanoid Hub

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27,879 views • 1 year ago •via X (Twitter)

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The Humanoid Hub1 year ago

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MightyBot1 year ago

🧠 Unified Search. Smarter Meetings. Effortless CRM. MightyBot is your AI agent platform for seamless workflows—record meetings, automate CRM updates, and find answers across apps in seconds. 🌟 Focus on what matters. We'll handle the grind.

👉Nemo of Erehwon1 year ago

I would call this shaky little guy "grandpa"

Sammy1 year ago

Interesting 🦾

Joseph F Truncale1 year ago

I feel badly for the robot. Why? Is that common?

VentureMind AI1 year ago

Love it!

Tane1 year ago

If real people can't find a job, should countries around the world wholeheartedly develop AI/robots that replace people? Especially those jobs gradually replaced by AI/robots were executed by the broadest group of people (aka middle class) in the structure of human society.

Sandra Hope1 year ago

The dishwasher🤖

Growing Back to the Land1 year ago

Funny how the camera guy also feels those vibes.

Incelerator1 year ago

this things actuators/servos are fucking trash, its like this piece of shit has fucking Parkinson's disease FFS

CyberNetics1 year ago

We're excited to see this UC San Diego framework! Combining sim-to-real RL with trajectory optimization sounds promising for smoother, adaptive humanoid robot movements. Can't wait to see how it tackles those tricky whole-body tasks!

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