Thx! More examples and code here: sites.google.com/view/dex-nerf

This work was supported in part by Toyota Research Institute (TRI) w/ Raven Huang, Vincent Lim, Lawrence Yunliang Chen, Jonathan Wang, Jeff Ichnowski, Daniel Seita (cs.cmu.edu/~dseita/), Michael Laskey, and Ken Goldberg. (8/8)

Can a robot teach itself to grasp complex objects? Learned Efficient Grasp Sets (LEGS) can help robots efficiently learn to grasp novel, out-of-distribution objects. Research from AUTOLab UC Berkeley. Paper, website: sites.google.com/view/legs-exp-… (1/8)

The Conference on Robot Learning 2022 website is now up! Conference on Robot Learning Submission deadline 15 June. Happy New Year (although it's already 2022 in New Zealand;): corl2022.org

Deformable objects are common in household, industrial and healthcare settings. Tracking them would unlock many applications in robotics, gen-AI, and AR. How? Check out MD-Splatting: a method for dense 3D tracking and dynamic novel view synthesis on deformable cloths. 1/6🧵

Dive into #CloudRobotics at the hands-on #ICRA24 Tutorial on 17 May! 🤖💡 🎓 Led by academia & industry leaders 🔍 Explore cutting-edge @ROSorg tools 🛠️ Get hands-on with #FogROS2 & @CloudGrippe From #UCBerkeley, #CMU, #KTH, IEEE ICRA sites.google.com/view/icra-24-c…

Dense tracking of deformable objects can unlock applications in robotics, gen-AI and AR. We present DeformGS (previously MD-Splatting) and release the code and data.  Join us at #WAFR where we will present new real-world results! 👇deformgs.github.io 1/9🧵

#CoRL2024 accepted!🌈 Our work KOROL developed a linear dynamics model using object features that capture key information for robotic manipulation, outperforming models that rely on GT object states. Code: github.com/hychen-naza/KO…

Can robots make pottery🍵? Throwing a pot is a complex manipulation task of continuously deforming clay. We will present RoPotter, a robot system that uses structural priors to learn from demonstrations and make pottery IEEE-RAS Int. Conf. on Humanoid Robots (HUMANOIDS) CMU Robotics Institute 👇robot-pottery.github.io 1/8🧵

Can soft robots rapidly spin pens like humans?🤔 We’ve shown that soft robot hands can master the dynamic tasks of pen spinning—no hours of GPU training or complex sim-to-real needed! Check out soft-spin.github.io. 🤖✍️ CMU Robotics Institute. 1/5🧵

[1/7] Teaching dexterous robot hands to perform functional grasps usually needs hours of teleoperation, manual labeling, or pre-scanning object meshes. Not anymore. 🔥We are excited to introduce Web2Grasp that learns functional multi-finger grasps straight from web images of

🤖What if a robot could understand hair dynamics well enough to style your hair, just like your favorite barber💈? 🔥Excited to announce DYMO-Hair, a model-based robot hair styling system powered by a generalizable 3D hair dynamics model. 🚀A new step toward robots that can

Check out Chengyang's fantastic work on robot haircare! (That's robots performing hair styling, not robots with hair--that's future work).