Loading video...

Video Failed to Load

Go Home

First attempt at folding a shirt 😱 - Neural network predicts future motors position from camera inputs - Cameras of iPhone and Macbookpro - Robot arms cost 300$ each - Training over 100 examples takes half a day on Apple silicon Do it yourself with ⭐

233,634 views • 1 year ago •via X (Twitter)

11 Comments

Remi Cadene's profile picture
Remi Cadene1 year ago

See our tutorial to assemble and train your robot at home!

Deepak Kushwaha's profile picture
Deepak Kushwaha1 year ago

This is very intresting ! Next wave in robotics should allow people to customize actions of thier robots and help in daily chores !

Ruairi's profile picture
Ruairi1 year ago

Can it do the ironing too? That would be worth replicating

Remi Cadene's profile picture
Remi Cadene1 year ago

Haha, some future versions that are more capable will be able to do ironing!

Ryan's profile picture
Ryan1 year ago

Now do a fitted sheet 😜

Remi Cadene's profile picture
Remi Cadene1 year ago

Haha needs two mobile robots for that

sierra catalina's profile picture
sierra catalina1 year ago

you should give it a shirt board! these are used heavily in retail apparel merchandising & are what give t-shirt piles in clothing stores those perfect, crispy folds. amazing work!! the future is so darn exciting.

Remi Cadene's profile picture
Remi Cadene1 year ago

Cheater! 😂

Rob Ghilduta's profile picture
Rob Ghilduta1 year ago

Very impressive! Curious how robust this is, what happens if you start with the left shoulder partially folded?

Ashish Sheth's profile picture
Ashish Sheth1 year ago

Wife can spend more time shopping if she has this!! What else?

Remi Cadene's profile picture
Remi Cadene1 year ago

Haha and you too can eventually spend time shopping beautiful things with her ^^

Related Videos

This guy connected a computer vision model to dual robotic manipulators on his desk and the system now folds shirts in 47 seconds per garment without any human intervention after loading Automated laundry folding is one of those problems that sounds trivial until you realize fabric has no rigid structure and every wrinkle changes the optimal fold path You need the robot to detect garment boundaries through visual segmentation, identify sleeve edges and collar positions on randomly oriented fabric, generate dynamic reference coordinates that shift with garment size, synchronize two independent robotic arms to pull opposing fabric edges without tearing, and execute all of this without a conveyor belt or fixed staging area Most people assume you need a commercial folding machine or at least a rigid frame to hold clothes in place This guy just bolted two robot arms to a workbench, ran a Flask server with a Laundrobot vision library, and built a preset selection interface that handles nine garment types The setup was minimal: a Python backend processing camera frames, a segmentation model running inference locally, two manipulators with soft grippers, and a heads-up display showing red and blue anchor points overlaid on live fabric The system scans the garment, the vision pipeline outputs coordinates like 284.262 and 965.262, the dashboard waits for a RUN command, and the arms fold the item in two geometric steps The robot picks up shirts, pants, towels, and socks from any position on the desk with zero calibration and zero pre-staging It is the same principle robotic pick-and-place systems use in factories but instead of metal parts it is handling deformable textiles that compress and slide unpredictably The arms have no concept of what clean laundry means to a human They think they are executing waypoint trajectories but the output is getting transformed into neatly stacked garments that take zero cognitive load from the operator If a household generates 14 loads of laundry per month and folding takes eleven minutes per load this is how you reclaim 154 minutes without outsourcing or spending four figures on hardware This is the cleanest domestic automation I have seen: one desk, two arms, one camera, and between them a folding operation that runs while you do anything else

Blaze

24,557 views • 1 month ago

I don’t know if we live in a Matrix, but I know for sure that robots will spend most of their lives in simulation. Let machines train machines. I’m excited to introduce DexMimicGen, a massive-scale synthetic data generator that enables a humanoid robot to learn complex skills from only a handful of human demonstrations. Yes, as few as 5! DexMimicGen addresses the biggest pain point in robotics: where do we get data? Unlike with LLMs, where vast amounts of texts are readily available, you cannot simply download motor control signals from the internet. So researchers teleoperate the robots to collect motion data via XR headsets. They have to repeat the same skill over and over and over again, because neural nets are data hungry. This is a very slow and uncomfortable process. At NVIDIA, we believe the majority of high-quality tokens for robot foundation models will come from simulation. What DexMimicGen does is to trade GPU compute time for human time. It takes one motion trajectory from human, and multiplies into 1000s of new trajectories. A robot brain trained on this augmented dataset will generalize far better in the real world. Think of DexMimicGen as a learning signal amplifier. It maps a small dataset to a large (de facto infinite) dataset, using physics simulation in the loop. In this way, we free humans from babysitting the bots all day. The future of robot data is generative. The future of the entire robot learning pipeline will also be generative. 🧵

Jim Fan

165,246 views • 1 year ago