HumanUp has been accepted by #RSS2025 looking forward to seeing you in LA this June!

How can we train robot policies without any robot data—just using two-view videos of humans manipulating tools? Check out our new paper: "Tool-as-Interface: Learning Robot Policies from Human Tool Usage through Imitation Learning" Honored to be a Best Paper Finalist at the

Sparsh-skin, our next iteration of general pretrained touch representations Skin like tactile sensing is catching up on the prominent vision-based sensors with the explosion of new dexteorus hands A crucial step in leveraging full hand sensing; work led by Akash Sharma 🧵👇

Our paper, "One-Shot Real-to-Sim via End-to-End Differentiable Simulation and Rendering", was recently published at IEEE RA-L. Our method turns a single RGB-D video of a robot interacting with the environment, along with the tactile measurements, into a generalizable world model.

This was a key feature in enabling DexterityGen, our teleop that can support tasks like using a screw driver Led by Zhao-Heng Yin, now open source

Soaking up the sun at the Robotics: Science and Systems conference in Los Angeles this weekend? Stop by the Hello Robot booth to say hi and get a hands on look at Stretch! Hope to see you there 😎 roboticsconference.org

🚀 #RSS2025 sneak peek! We teach robots to shimmy objects with fingertip micro-vibrations precisely—no regrasp, no fixtures. 🎶⚙️ Watch Vib2Move in action 👇 vib2move.github.io #robotics #dexterousManipulation

Workshop on Mobile Manipulation in #RSS2025 kicking off with a talk from Jeannette Bohg! Come by EEB 132 if you’re here in person, or join us on Zoom (link on the website)

How can we build mobile manipulation systems that generalize to novel objects and environments? Come check out MOSART at #RSS2025! Paper: arxiv.org/abs/2402.17767 Project webpage: arjung128.github.io/opening-articu… Code: github.com/arjung128/stre…

Come by the Google DeepMind booth at Robotics: Science and Systems conference in LA! We’re demoing Gemini Robotics On-Device live, come check it out

🚀 Introducing RIGVid: Robots Imitating Generated Videos! Robots can now perform complex tasks—pouring, wiping, mixing—just by imitating generated videos, purely zero-shot! No teleop. No OpenX/DROID/Ego4D. No videos of human demonstrations. Only AI generated video demos 🧵👇

How do you build a robot that can open unfamiliar objects in new places? This study put mobile manipulation systems through 100+ real-world tests and found that perception, not precision, is the real challenge.🤖 ▶️youtube.com/watch?v=QcbMnE… 📑arjung128.github.io/opening-articu…

Don’t miss out on our #CoRL2025 paper 👉 tool-as-interface.github.io Tool-as-Interface: Learning Robot Policies from Observing Human Tool Use Robots learn robust and generalizable manipulation skills directly from human tool-use videos, bridging the embodiment gap without

Bored of working on toy tasks in the lab? We are solving robot manipulation at massive real world scales with Vulcan at Amazon I am at #CoRL2025 and my team is looking for PhD research interns, postodcs, and scientists aboutamazon.com/news/operation…

💾 Data from across the country. 🚁 No access to the drone. 🤖 Still works, zero-shot. UMI-on-Air makes large-scale data collection → real-world deployment possible.

What if robots could decide when to see and when to feel like humans? We built a system that lets them. Multi-Modal Policy Consensus learns to balance vision 👁️ and touch ✋. 🌐 Project: policyconsensus.github.io 1/N

I rarely get to share the specific embodiments I work with every day, but I'm thrilled to finally see this one go public Meet Amazon's newest robotic system: Blue Jay!

We are excited to release MoMaGen, a data generation method for multi-step bimanual mobile manipulation. MoMaGen turns 1 human-teleoped robot trajectory into 1000s of generated trajectories automatically.🚀 Website: momagen.github.io arXiv: arxiv.org/abs/2510.18316

Synthesizing robot data in simulation is a promising way for scaling up. While most prior work focuses on static manipulation, check out our new work MoMaGen led by Chengshu Li Mengdi Xu Arpit Bahety Hang Yin , where we extend data synthesis to mobile manipulation. MoMaGen

Thrilled to share our work AlphaOne🔥 at EMNLP 2025 2025, Junyu Zhang and I will be presenting this work online, and please feel free to join and talk to us!!! 📆Date: 8:00-9:00, Nov 7, Friday (Beijing Standard Time, UTC+8) 📺Session: Gather Session 4