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Anya Rossi

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A robot that sees the terrain and predicts its own future… up to 5 seconds ahead? This is real. ❗️Best Systems Paper finalist at #RSS2025 The team introduces a perceptive Forward Dynamics Model that helps legged robots safely navigate rough, complex environments: no manual tuning no rigid-body limits. Why this matters ✅ Predicts future robot states using both perception and proprioception ✅ Trained on years of sim + real data for strong sim-to-real performance ✅ Enables zero-shot navigation with minimal cost tuning ✅ Boosts success rates and safety on rough terrain like never before This isn’t just another planner, it’s a big step toward robust, adaptable locomotion. Paper: Project website:

A robot that sees the terrain and predicts its own future… up to 5 seconds ahead? This is real. ❗️Best Systems Paper finalist at #RSS2025 The team introduces a perceptive Forward Dynamics Model that helps legged robots safely navigate rough, complex environments: no manual tuning no rigid-body limits. Why this matters ✅ Predicts future robot states using both perception and proprioception ✅ Trained on years of sim + real data for strong sim-to-real performance ✅ Enables zero-shot navigation with minimal cost tuning ✅ Boosts success rates and safety on rough terrain like never before This isn’t just another planner, it’s a big step toward robust, adaptable locomotion. Paper: Project website:

43,896 views • 9 months ago

"Building Rome with Convex Optimization" has been accepted to #RSS2025! Try XM, our new structure from motion pipeline powered by GPU-accelerated convex semidefinite optimization: XM solves large-scale (nonconvex) global bundle adjustment problem via learned depth and a tight convex semidefinite relaxation. By implementing the Burer-Monteiro low-rank factorization algorithm in CUDA, XM can solve bundle adjustment problems with more than 10,000 images/views. Technical details in the paper: Kudos to Haoyu Han

"Building Rome with Convex Optimization" has been accepted to #RSS2025! Try XM, our new structure from motion pipeline powered by GPU-accelerated convex semidefinite optimization: XM solves large-scale (nonconvex) global bundle adjustment problem via learned depth and a tight convex semidefinite relaxation. By implementing the Burer-Monteiro low-rank factorization algorithm in CUDA, XM can solve bundle adjustment problems with more than 10,000 images/views. Technical details in the paper: Kudos to Haoyu Han

27,462 views • 1 year ago

A robot that sees the terrain and predicts its own future… up to 5 seconds ahead? This is real. ❗️Best Systems Paper finalist at #RSS2025 The team introduces a perceptive Forward Dynamics Model that helps legged robots safely navigate rough, complex environments: no manual tuning no rigid-body limits. Why this matters ✅ Predicts future robot states using both perception and proprioception ✅ Trained on years of sim + real data for strong sim-to-real performance ✅ Enables zero-shot navigation with minimal cost tuning ✅ Boosts success rates and safety on rough terrain like never before This isn’t just another planner, it’s a big step toward robust, adaptable locomotion. Thanks for sharing, Robotic Systems Lab! Paper: Project website:

A robot that sees the terrain and predicts its own future… up to 5 seconds ahead? This is real. ❗️Best Systems Paper finalist at #RSS2025 The team introduces a perceptive Forward Dynamics Model that helps legged robots safely navigate rough, complex environments: no manual tuning no rigid-body limits. Why this matters ✅ Predicts future robot states using both perception and proprioception ✅ Trained on years of sim + real data for strong sim-to-real performance ✅ Enables zero-shot navigation with minimal cost tuning ✅ Boosts success rates and safety on rough terrain like never before This isn’t just another planner, it’s a big step toward robust, adaptable locomotion. Thanks for sharing, Robotic Systems Lab! Paper: Project website:

Ilir Aliu - eu/acc

20,012 views • 11 months ago

"Generalization means being able to solve problems that the system hasn't been prepared for." Our latest work in #RSS2025 can automatically invent neural networks as state abstractions, which help robots generalize. Check it out here:

"Generalization means being able to solve problems that the system hasn't been prepared for." Our latest work in #RSS2025 can automatically invent neural networks as state abstractions, which help robots generalize. Check it out here:

19,240 views • 11 months ago

Sim2real is getting so mature that with great hardware (thanks Clemens Christoph Robert Katzschmann), you can get things running in just days 🤖 We are also demoing ORCA Dexterity trained with MuJoCo Playground at #RSS2025. Come by Associates Park at 12:30pm-2pm and 6:30pm-8pm! Robotics: Science and Systems

Sim2real is getting so mature that with great hardware (thanks Clemens Christoph Robert Katzschmann), you can get things running in just days 🤖 We are also demoing ORCA Dexterity trained with MuJoCo Playground at #RSS2025. Come by Associates Park at 12:30pm-2pm and 6:30pm-8pm! Robotics: Science and Systems

Carlo Sferrazza

16,137 views • 11 months ago

Best Systems Paper finalist at #RSS2025 🚀 Excited to share our work on a perceptive forward dynamics model for safe, platform-aware navigation. 📄 🌐 #Robotics #Planning #RSS

Best Systems Paper finalist at #RSS2025 🚀 Excited to share our work on a perceptive forward dynamics model for safe, platform-aware navigation. 📄 🌐 #Robotics #Planning #RSS

Robotic Systems Lab

14,935 views • 11 months ago

Command humanoids *directly* with natural language? Introducing LangWBC, a generative, end-to-end policy that turns natural language into real-world whole-body humanoid control! 💬→🦿Smooth, robust, surprisingly intuitive! See more 👉 #RSS2025

Command humanoids directly with natural language? Introducing LangWBC, a generative, end-to-end policy that turns natural language into real-world whole-body humanoid control! 💬→🦿Smooth, robust, surprisingly intuitive! See more 👉 #RSS2025

14,109 views • 1 year ago

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