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I'm so excited to announce I will be joining @Cornell_CS as an assistant professor next fall!
I can't wait to launch my lab and start building robots with human-level dexterity and adaptability. 🤖🏃🤹
Preston Culbertson
@pdculbert
Assistant professor, @Cornell_CS. Learning, perception, and control for building more dynamic robots.
- We got the humanoid recipe (human demo → retarget → RL) to work for dexterous hands. Key idea: use interaction-preserving retargeting, not just IK. @yunhai got tool use (including scissors!) on real hands from one human demo. Good retargeting → surprisingly natural motion.Can robots learn contact-rich tool use, like operating a pair of scissors✂️ or turning a screwdriver🪛, from human data? Introducing REGRIND: a minimalist retargeting-guided RL recipe for dexterous manipulation. 🌐 yunhaifeng.com/REGRIND/ 📄 Paper + code on the site! 🧵👇
- So cool to see the loco-manipulation stack we developed at RAI out in the wild! Congrats to @simonlc_ and the team for the awesome demo. This ability to adapt RL policies using test-time reward spec + MPC/search is really cool / basically why we built judo.See Spot perform dynamic whole-body manipulation. Using a combination of reinforcement learning (RL) and sampling-based control, the robot is able to autonomously drag, roll, and stack tires weighing 15 kg (33 lb), well above its maximum arm lift capacity. Learn more about
- Join us in Ithaca this October for NERC! Submissions are due this Tuesday, Sept 2 - excited to see everyone at Cornell in a few weeks.Reminder: Poster and Rising Star submissions for NERC 2025 are due next Tuesday, Sep 2! Submit now for a great opportunity to share your research with robotics faculty and peers. 🔗 openreview.net/group?id=NERC%… 📅 Deadline: Sep 2
- 🥋 We're excited to share judo: a hackable toolbox for sampling-based MPC (SMPC), data collection, and more, designed to make it easier to experiment with high-performance control. Try it: pip install judo-rai
