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🚀 Thrilled to present ViSafe, a vision-only airborne collision avoidance system that achieved drone-to-drone avoidance at 144 km/h. In an era of congested airspace and growing autonomy, reliable self-separation is paramount 🧵👇

Basking in the glow of Commencement 🎓✨ During the 127th Commencement ceremony, a class of 6,741 Carnegie Mellon graduates emerged, ready to solve complex challenges and drive transformative change. Congratulations to the Class of 2025! #TartanProud

🚧 High-quality, diverse data is a major bottleneck in robot learning. 🌎🤲 DexWild offers a fast, scalable way to collect human demonstrations in-the-wild — unlocking real-world generalization for robots! #CMUrobotics

Appleseed labs, a team from Kantor Lab, won the Excellence in Regenerative Agriculture award at the 2025 Farm Robotics Challenge! 🌽🏆👏 Their reforestation robot showed special commitment to environmental sustainability + ecosystem health. Learn more: loom.ly/dw8v3h0

On my way ✈️ to ATL for IEEE ICRA! LeCAR Lab at CMU will present 8 conference papers (including DIAL-MPC as the Best Paper Finalist) and one RA-L paper. Details: lecar-lab.github.io Hope to meet old & new friends and chat about building generalist 🤖 with agility 🚀

Congrats to Jiaoyang Li (Jiaoyang Li) on receiving the NSF CAREER award! Her work, “Environment Optimization for Large-Scale Multi-Agent Coordination: Models, Methods, and Applications” reimagines how environments are designed for robots! Learn more👇 loom.ly/6etJMLc

Congrats to Ioannis Gkioulekas for receiving the 2025 Bodossaki Distinguished Young Scientist award in "Applied Sciences and Technologies: Artificial Intelligence" 🏆 The award recognizes scholars of Greek descent for significant scientific progress! ⬇️ loom.ly/vZ70tv4

Humanoids can run, parkour, dance, and fight nowadays, but can it serve🍺☕️ just like wheeled robots? It could be hard - we found that the default G1 controller yields an average end-effector acceleration ~0.5G (human-level is ~0.05G)! Check-out👇to see how we reduce this

Robots may struggle in cluttered scenes due to challenging occlusions 🤖🚧 RaySt3R is a new foundation model that predicts the full 3D geometry from a single view! 👇👇 #CMUrobotics

Say ahoy to 𝚂𝙰𝙸𝙻𝙾𝚁⛵: a new paradigm of *learning to search* from demonstrations, enabling test-time reasoning about how to recover from mistakes w/o any additional human feedback! 𝚂𝙰𝙸𝙻𝙾𝚁 ⛵ out-performs Diffusion Policies trained via behavioral cloning on 5-10x data!

Shortcut models enable scaling offline RL, both at train-time at test-time! We beat so many other algorithms on so many tasks we had to stick most of the results in the appendix 😅. Very proud of Nicolas Espinosa Dice for spearheading this project, check out his thread!