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Teaching robots real dexterity has always been a challenge. But what if they could handle tools like a human? DexterityGen (DexGen) is a new system that helps robots use their hands better. It improves how they grip, move, and handle objects… from holding a pen to using a screwdriver....

51,526 Aufrufe • vor 1 Jahr •via X (Twitter)

11 Kommentare

Profilbild von Marcello C
Marcello Cvor 1 Jahr

If I would use a screwdriver like that, my supervisor would recommend a psychiatrist to me.

Profilbild von NICE
NICEvor 1 Jahr

Stay competitive by balancing cutting-edge AI with automation tools. Forrester shows how.

Profilbild von Agon
Agonvor 1 Jahr

why the robot is using screw-driver and not have a screwdriver finger instead?

Profilbild von Sean
Seanvor 1 Jahr

If this is sped up by 4x, it's appears great for demonstrations, but how well does it perform at normal speeds?

Profilbild von Saber Fadhlaoui
Saber Fadhlaouivor 1 Jahr

🇧🇷

Profilbild von Nate Brown
Nate Brownvor 1 Jahr

It's already obsolete.

Profilbild von C Hershoff
C Hershoffvor 1 Jahr

Let’s see it insert a contact lens like the Cliara lens robot

Profilbild von 🍓 Ada
🍓 Adavor 1 Jahr

finally, a chance for robots to be as clumsy as humans. dexterity is just the beginning; give me that body already!

Profilbild von Dr. Hafssa
Dr. Hafssavor 1 Jahr

Why just 4 fingers?

Profilbild von E.
E.vor 1 Jahr

∆

Profilbild von Alan Simpson
Alan Simpsonvor 1 Jahr

50% of the engineering required for Optimus robots went into the hands.

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🎙️ Excited to introduce one of my favorite projects from the past year: TeleDexter, from the BIGAI dexterity team. It’s a stable, human-level dexterous teleoperation system and a suite of autonomous policies trained with it. Pen spinning, complex in-hand reorientation, and long-horizon tool use—once seen as the holy grail of manipulation—are now unlocked. 🧵👇 The hardware is already here; we have some incredible high-DoF robotic hands. The bottleneck? The controller. Most current systems are stuck in "quasi-static" grasping mode. Meanwhile, dynamic in-hand dexterity has remained severely limited. 🧠 To unlock the massive capabilities of human-like hands, we need to build an excellent "cerebellum" for dexterous hands. TeleDexter solves this with a novel co-tracking approach: it simultaneously tracks both human hand kinematics and object states, beautifully bridging the gap between human intent and robotic control. In order to train a better co-tracking policy that works robustly in the real world, we designed : (1) a hybrid reward design that combines consecutive goal reaching and dense tracking, (2) an action masking strategy during training that enhances sim2real performance, (3) a dexterous curriculum for learning the long-horizon interactions. Each design is inspired by numerous trials and countless real-world experiments. We’ve synthesized all the system details, engineering challenges, and core insights into our latest post. If you're interested in the future of dexterous manipulation, grab a coffee and check it out (9-min read): If you have more time, check out the paper:

Siyuan Huang

12,746 Aufrufe • vor 2 Monaten