Pretty cool that this works with only 15 min of data!
You can take a robot policy that doesn't do mobility and turn it into one that can move around (mobility + manipulation) with a very limited robot data.
We taught a robot how to move around in only 15 minutes.
That’s all the mobility data our Direct Video-Action-powered robot needed to accomplish a task that requires mobility and manipulation.
It's amazing how much you can scale up the output resolution and speed of image generation models without any re-training.
The trick here is to leverage the more local behavior of attention in later diffusion steps to accelerate attention within diffusion transformers.
📢🚀 Excited to share
AReA: Adaptive Receptive-Field Attention for Efficient High-Resolution Diffusion Transformers
Training-free, up to 6× the native resolution, up to 3.2× faster.
📄Paper: arxiv.org/abs/2610.17227
🌐Webpage: rajabi2001.github.io/area
🤗HF:
We gave our robots a sense of touch!
Excited to finally share this work with @AndrewEJXie, @leooeld, and the @rhoda_ai team!
Some technical details on the tactile sensor and robot policy: 🧵
What can a robot do without vision?
We gave our robot a sense of touch and showed it can recognize and retrieve objects with its cameras blindfolded.
Introducing Rhoda’s new tactile sensor—it feels pressure, texture, vibration, slip, and temperature, just like your fingertips.
There is a lot to appreciate in these demos—recovery from errors, the length and complexity of the demonstrations, and targeting actual, real-world tasks.
Continuing our RhodaAtWork series with another look at Direct Video-Action (DVA) in action.
This time, a single model handles multiple tasks across two home appliances: refrigerator EPS foam installation and washing machine drain hose routing.
Great to see more robot demonstrations from @RhodaAI — recovery behavior, challenging customer use cases, and reliable autonomous operation over extended periods of time.
More industries. More real customer work.
Introducing RhodaAtWork, a series on the customer workflows our robots are learning to handle across manufacturing and logistics.
First up: unpacking, scanning and stacking component reels for electronics manufacturing.
