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"Gr00t" vs "Pi0" vs "Pi0 Fast". I compared top open-source robotic models, and here's a detailed overview based on our own experience:

RoboVerse RoboVerse: Towards a Unified Platform, Dataset and Benchmark for Scalable and Generalizable Robot Learning github.com/RoboVerseOrg/R…

Despite great advances in learning dexterity, hardware remains a major bottleneck. Most dexterous hands are either bulky, weak or expensive. I’m thrilled to present the RUKA Hand — a powerful, accessible research tool for dexterous manipulation that overcomes these limitations!

🚀 RoboVerse has been accepted to RSS 2025 and is now live on arXiv: arxiv.org/abs/2504.18904 ✨ Also be selected in HuggingFace Daily: huggingface.co/papers/2504.18… 🛠️ Explore our open-source repo: github.com/RoboVerseOrg/R… We're actively developing and adding new features daily — come

🚀Check out our new work, FastTD3, a reinforcement learning algorithm that is simple, efficient, and highly capable. It achieves truly remarkable performance across challenging RL tasks.

FastTD3: "Minimum innovation, maximum results" Not the paper we had planned to write, but one of the works I am most proud of. We wanted to make sure our baseline (TD3) was a very solid baseline, so we added a few things that are already known to help in RL (large,

Everyday human data is robotics’ answer to internet-scale tokens. But how can robots learn to feel—just from videos?📹 Introducing FeelTheForce (FTF): force-sensitive manipulation policies learned from natural human interactions🖐️🤖 👉 feel-the-force-ftf.github.io 1/n

There is a raging debate over sensory modes and redundancy How much is enough and is sensory overload an issue Perhaps the key is redundant modes are the fabric that hold actions together to solve long term planning Think fascia

Again the power of tactile sensing and multi-finger hands comes through. This is the future of dexterous manipulation!

Introducing ViTacFormer: Next-Level Dexterous Manipulation with Active Vision and High-Resolution Touch by Haoran Geng #AI #Robotics #MachineLearning #ArtificialIntelligence #ML #Innovation cc: Sen. Sally Eaves Andreas Mueller Marcus Borba