Creating a "unified" policy for a robot is uniquely... challenging for two reasons: (a) data is scarce; (b) a single robot can only act sequentially. In PolyTask, we learn a single policy to solve many tasks in a lifelong fashion given *just 1 demonstration* for each task. 🧵show more

Evaluating policies on a real robot can be painful.... Can we use a world model to get a rough estimate of how good a policy is? Checkout "Evaluating Robot Policies in a World Model". Paper: Demo: Code:show more

A Rerun Viewer for the DROID Dataset! DROID: A... Large-Scale In-The-Wild Robot Manipulation Dataset is a robot manipulation dataset by Alexander Khazatsky et al. with 76k demonstration trajectories or 350h of interaction data, collected across 564 scenes and 86 tasks.show more

How can a visuomotor policy learn from internet videos?... We introduce Dreamitate, where a robot uses a fine-tuned video diffusion model to dream the future (top) and imitate the dream to accomplish a task (bottom). website: paper:show more

Teaching robots how to paint! 💅🏼 This painting robot,... for example, mimics human movements with precision to handle repetitive, and tiring tasks. A special device memorizes points in 3D space, which are then sent to the robot's control. The result? A robot that, after a single demonstration, can perform a given action. Keep in mind that it's taught as 'fixed'. 👨🏻‍🔧 That is, it will not be able to react to an anomaly or changing environment. But ultimately, with fewer workers available and many avoiding tough, dirty jobs, robots are helping industries stay efficient and safe. ♻️ RT to help 1 robot find a new workplace!show more

📢#𝗥𝗼𝗯𝗼𝗛𝗶𝘃𝗲 - a unified robot learning framework ✅Designed for... genralizn first robot-learning era ✅Diverse (500 envs, 8 domain) ✅Single flag for Sim<>Real ✅TeleOper Support ✅Multi-(Skill x Task) realworld dataset ✅pip install robohive 🧵👇show more

🤖Why is robot manipulation still an open challenge? This... video shows a kitting task -- packing multiple items into a single product. No robot today can do this autonomously. Big challenges = big opportunities for research and industry. #robotics #manipulation #automationshow more

Why is action chunking crucial for robot dexterity? 🤖... - We identify a natural tradeoff between temporal consistency and reactivity - New policy decoding technique that is *both* temporally consistent & fully reactive ICLR 2025 paper: A short thread 🧵show more

How can we more effectively leverage robot data from... different embodiments for skill transfer? Excited to share that our new work, RoVi-Aug, has been accepted to Conference on Robot Learning as an oral paper！ WIth RoVi-Aug, you can augment an existing robot dataset into a different robot and different viewpoints. A policy trained on the augmented dataset can zero-shot deploy on the unseen target robot with significantly different camera angles! 🧵👇 🔗 Check out our paper:show more

Turns out you can train humanoid hands without any... robot data. The idea in HUG is quite simple: (a) collect human data with smart glasses, (b) train a human manipulation model, (c) retarget to multi-fingered robot hands.show more

RLDX-1 a dexterity-first foundation model for robot hands, is... coming in a few days. It is interesting.show more

Skild AI's new S1 robot foundation model helps robots... learn previously unseen tasks from a single video demonstration. 🤖 See how NVIDIA technology supports S1 from training and simulation to real-world deployment. Learn more ➡️show more

Generalist robot policies need a benchmark that works across... any robot and any policy. 🦾 Introducing RoboLab, a high‑fidelity simulation benchmark built on NVIDIA Isaac and Omniverse to evaluate generalist robot policies in diverse, photoreal, physics‑based environments. Coming soon to the NVIDIA Isaac Lab‑Arena roadmap for large‑scale, robotic policy evaluation. 📖 #NationalRoboticsWeekshow more

US and Israel sending a joint message to Iran:... To grasp the sheer power of a B-52 nuclear bomber— Each one can carry 20 B83 bombs, unleashing 2,000 km² of devastation in a single strike. That’s just one bomber. For context, Tehran is only 730 km²show more

Long-horizon visual goals remain surprisingly hard for robot manipulation.... We introduce Act2Goal, a goal-conditioned policy that uses a visual world model to reason about progress toward a goal, and practice it autonomously in the real world.show more

Super excited about Hydra-0 from Hongyu Li and team!... The key idea is to use flow as a shared visual interface across embodiments/objects for controllable video generation, allowing a single generalist world model to learn from human, handheld-gripper, and robot interaction data. My favorite result is the video below: start from a real video of a human doing the task (left), extract the desired object flow, and condition the model on that flow (right). The model then hallucinates a plausible robot motion that could produce the same object motion. Very cool glimpse of how a generalist world model can bridge human demonstrations and robot control.show more

Check out this robot hexapod with a 25Kg payload... that can run for an hour on a single power tool battery. It is fully open source and runs #ROS Jazzy.show more

Controlled via a Bluetooth finger patch, BeetleBot, a beetle-inspired... soft robot, can perform various locomotive tasks and provide visual and sensory feedback for potential applications from biomedical assistance to environment exploration. Learn more in Science Advances:show more

MAKING AXIS TASKS FEEL EASY 👀🤖 I made a... quick video showing how to complete an Axis Robotics task step by step. The task gives you a clear goal, steps, controls and camera views to guide you. In this one, the goal is simple, Open the trash bin, pick up the onion, and place it inside. 🧅 Just follow the instructions, control the robot arm and complete the task. What I like is that even beginners can understand what they need to do. But the interesting part is what happens with these interactions after we complete them. Each completed task can contribute valuable robot training data, helping Physical Ai systems learn how to handle different objects and environments. Small tasks from the community can become useful data for teaching robots how to interact with the real world. That’s what makes Axis interesting to me.show more