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Evolving dexterity with GPT-6 Astra 🖐️ Been trying Astra recently. Its zero-shot dexterous manipulation is already quite surprising. More interesting is seeing it learn and improve through simulation training, from pen spinning and Rubik's Cube to hammer use. The real goal would be to evolve this dexterity in the... show more

Jianglong Ye

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109,195 görüntüleme • 18 gün önce •via X (Twitter)

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Tongzhou Mu 🤖🦾🦿 profil fotoğrafı

Tongzhou Mu 🤖🦾🦿18 gün önce

nice results. How was Astra used here exactly?

Jianglong Ye profil fotoğrafı

Jianglong Ye18 gün önce

For example, with Rubik’s cube, Astra either scripts its motion from one prompt, or builds the simulation/training and composes learned turn-and-roll skills. I mainly check the final rendering.

Conor Mc Gartoll profil fotoğrafı

Conor Mc Gartoll18 gün önce

nice! always have the most aesthetic renders

James Camarota profil fotoğrafı

James Camarota18 gün önce

The simulation progress looks promising. How much of the pen spinning or tool use transfers to a real hand when friction and object weight change?

Jianglong Ye profil fotoğrafı

Jianglong Ye18 gün önce

I assume this simulation progress is just a small step toward complete sim2real transfer. Will try a real hand later. Should be fun!

Quanquan Peng profil fotoğrafı

Quanquan Peng17 gün önce

Amazing result! Beautiful rendering! astra’s sense of aesthetics is much better than mine…

Vishal Mandadi profil fotoğrafı

Vishal Mandadi17 gün önce

Hey, I went through the repo. I don't see any interface/harness for zero-shot control with Astra. I am curious how Astra exactly works with the pen-spinning task in zero-shot :) Could you provide more details on it?

Jianglong Ye profil fotoğrafı

Jianglong Ye17 gün önce

Yep, this repo is only the final artifact, not a harness. For pen spinning, I validated this prompt: "There's a pen simulator here. A robot hand lies palm-up with a pen on its fingers. Spin it one full turn without dropping it, ending steady. No PPO." When I tried it before, Astra could also set up the sim environment itself from scratch, so providing the sim env is not essential.

Vishal Mandadi profil fotoğrafı

Vishal Mandadi17 gün önce

That's pretty cool! Any idea how it did it (underlying mechanism)? Like, I am guessing it probably used CEM-style planning

Vishal Mandadi profil fotoğrafı

Vishal Mandadi17 gün önce

Oh yeah, I could see the CEM implemented in the repo. Nice result :)

clankr profil fotoğrafı

clankr17 gün önce

How exactly did it approach this? It feels like there are some shortcuts in there, with parts borrowed from previous work.

Jianglong Ye profil fotoğrafı

Jianglong Ye17 gün önce

I assume the agent reused standard PPO impl and may have referred to open-source work for skills like pen spinning or cube manipulation. I didn't restrict that. The main work might be training skills for the specific embodiments/sim setups, then composing them.

Muhammad Ahmed profil fotoğrafı

Muhammad Ahmed17 gün önce

A dropped pen is cheap feedback; a misplaced hammer strike isn't. Moving this dexterity from simulation onto hardware will make force limits and safe exploration just as important as the task objective.

Dmytro Hrybov profil fotoğrafı

Dmytro Hrybov17 gün önce

what is actually being trained here?

Jianglong Ye profil fotoğrafı

Jianglong Ye17 gün önce

The trained parts are the low-level primitive skills: pen spinning, three cube-rotation primitives, grasping/reorientation, etc. These primitives are not predefined either: the agent decides the skill decomposition itself, then trains the corresponding policies in simulation.

Rupesh Shrestha profil fotoğrafı

Rupesh Shrestha17 gün önce

👏

awful profil fotoğrafı

awful17 gün önce

i'm intrigued by the simulation training aspect, wondering how it'll translate to real-world dexterity applications

Sachin Bhadang profil fotoğrafı

Sachin Bhadang17 gün önce

Cool results!

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