🚀 Introducing N2M! In mobile manipulation, the performance of a manipulation policy is very sensitive to the robot’s initial pose. N2M guides the robot to a suitable pose for executing the manipulation policy. N2M comes with 5 key features - Check them out in the posts below!

Come see what robot learning can do for surgical automation! We’re excited to host the first Workshop on Automating Robotic Surgery with an amazing lineup of speakers. 🗓️ Sept. 27 09:30AM - 12:30PM 📍 Floor 3F, Room E7 🌐 https://t.co/Lp10McSvb2 #CoRL2025 #CoRL @corl_conf

Humanoids 🤖 will do anything humans can do. But are state-of-the-art algorithms up to the challenge? Introducing HumanoidBench, the first-of-its-kind simulated humanoid benchmark with 27 distinct whole-body tasks requiring intricate long-horizon planning and coordination. 🧵👇

Access to *diverse* training data is a major bottleneck in robot learning. We're releasing DROID, a large-scale in-the-wild manipulation dataset. 76k trajectories, 500+ scenes, multi-view stereo, language annotations etc Check it out & download today! 💻: https://t.co/JsbBZIxzZA

Looking for a challenging manipulation benchmark? Introducing FurnitureBench 🪑🛠️, a reproducible real-world furniture assembly benchmark (#RSS2023 @RoboticsSciSys)! It features * 8 furniture models * 200+ hours of expert demonstrations * FurnitureSim: Isaac Gym simulator 🧵👇

Having humans annotate data to pre-train robots is expensive and time-consuming! Introducing SPRINT: A pre-training approach using LLMs and offline RL to equip robots w/ many language-annotated skills while minimizing human annotation effort! URL: https://t.co/KuxuUeaXmA 🧵👇