This project, which combines hardware design with learning-based controllers was a monumental effort led by @anyazorin.bsky.social and Irmak Guzey. More links and information about RUKA are below:

Website: ruka-hand.github.io
Assembly Instructions: ruka.gitbook.io/instructions

This would be funny! 😂

This project was an almost solo effort from @haldarsiddhant.bsky.social. And as always, this project is fully opensourced.

Project page: point-policy.github.io
Paper: arxiv.org/abs/2502.20391

The overall algorithm is simple:
1. Extract key points from human videos.
2. Train a transformer policy to predict future robot key points.
3. Convert predicted key points to robot actions.

Point Policy uses sparse key points to represent both human demonstrators and robots, bridging the morphology gap. The scene is hence encoded through semantically meaningful key points from minimal human annotations.

It should be accessible in EU now!

AnySense is built to empower researchers with better tools for robotics. Try it out below.

Download on App store: apps.apple.com/us/app/anyse...
Open-source code on GitHub: github.com/NYU-robot-le...
Website: anysense.app

AnySense is led by @raunaqb.bsky.social with several from NYU.

With this 'wild' robot data, data collected by AnySense can then be used to train multimodal policies! In the video above, we use the Robot Utility Models framework to train Visuo-Tactile policies for a whiteboard erasing task. You can use it for so much more though!

Thanks Tucker! The timing of this is great given the uncertainty with other funding mechanisms.