We are finally releasing a new benchmark!! #RSS2023 Main highlights are: * For real-world * Reproducible (3D printing) * 9 furniture assembly long-horizon tasks * 200 hrs of demonstrations This apparently is my 3rd furniture-related benchmark.🥹 clvrai.github.io/furniture-b…

Very excited to start sharing some of the work we have been doing at Amazon FAR. In this work we present OmniRetarget, which can generate high-quality interaction-preserving data from human motions for learning complex humanoid skills. High-quality re-targeting really helps the reinforcement learning. Why? The control policy optimization landscape is much nicer for (near)feasible trajectories than for trajectories with artifacts like (e.g.) foot skating or ground penetration.

It's almost time for #CoRL 2025! A reminder that we're hosting the Data in Robotics workshop this Saturday Sept 27th. We have a packed schedule and are also attempting to livestream the event for those who can't attend in person.

We have our speakers: @JosephLim_AI @KarlPertsch @mayacakmak , Serena Booth, @JasonMa2020 @shahdhruv_ @MashaItkina We also have a great panel lined up from 3-3:40pm! @svlevine @yukez @MashaItkina @SudeepDasari @ashwinb96 @JasonMa2020 @shahdhruv_

Honored that our @RL_Conference paper won the Outstanding Paper Award on Empirical Reinforcement Learning Research! 📜Mitigating Suboptimality of Deterministic Policy Gradients in Complex Q-Functions 📎openreview.net/forum?id=H3jc… Grateful to my advisors @JosephLim_AI and @ebiyik_!

corl.org/home CoRL 2025 schedule is released now! Please note that the whole schedule is earlier than other times. The submission deadline: 4/28 The conference: 9/27-9/30 @corl_conf #corl2025

Do you work on robotics? Do you like robots? Then, visit Korea next year! We (@ryoo_michael @gupta_abhinav_ @SongShuran Haewon and more) are organizing CoRL 2025 in Seoul, Korea!! #CoRL @corl_conf #robotics

I've been historically bearish on skill-based RL and @Jesse_Y_Zhang consistently shows me I'm probably wrong. Come check out EXTRACT at 1600 at @corl_conf (poster #11) to see him yank semantically meaningful skills out offline data by leveraging PTLMs. arxiv.org/abs/2406.17768

This work was guided by Jesse's co-advisor's @ebiyik_ and @JosephLim_AI, but I think we all agree that Jesse is effectively running his own little lab. If you're thinking about hiring a postdoc in the area of RL for robotics, Jesse comes a ton of insight and mentoring experience!

My student @MinhoHeo will be giving a talk in 2hrs (11am KST today). #RSS2023 This work is also one of the best system paper finalists too! Come and check it out :)

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: clvrai.github.io/sprint/ 🧵👇

Excited to present PATO: Policy Assisted TeleOperation, our recent work on scaling robot data collection! PATO uses a policy trained on prior data to assist the user during data collection, making teleop easier and even allows to teleop multiple robots simultaneously. 🧵👇

Check out our #CoRL2022 paper on learning skill dynamics for model-based RL! We present a sample efficient RL algorithms by temporal abstraction (skills). @YoungwoonLee @lucy_x_shi (an undergrad who will graduate soon!)