I will be at #CoRL2023 next week 🤖 Let's connect if you're attending!

ANYmal Parkour live! Still very mind-blowing to see it on site! ETH Zurich D-MAVT, ETH Zurich Robotic Systems Lab

Realsense 搭載型🐕犬ロボ🤣

Unitree GO2 robot dog with a handstand demo at #CoRL2023 #robotics Conference on Robot Learning

How can we extract insights from behavior modulated by multiple complex factors? 🐭🪰🤖🏃 Check out our #NeurIPS2023 Spotlight Paper where we present a SSL method for learning multiscale representations of behavior! Machine Learning at Georgia Tech Google DeepMind Link: multiscale-behavior.github.io 🧵

We also tested our method on 🤖 simulated quadruped robots walking over procedurally generated terrains, and found that BAMS captures information about terrain type, morphology, policy, etc.

『すずめの戸締まり』に登場する3本脚の椅子を再現したロボット設計，強化学習による歩容生成の論文を公開しました！ 来週アメリカで開催されるRoboSoft2024にて発表します！ website - shin0805.github.io/chair-type-tri… #すずめの戸締まり

We're proud to showcase some recent real-time work with 3D / 4D Gaussian splatting. In January of 2024 we acquired a full 3DGS commercial license with Inria to allow us to offer 4DGS services to clients around the world. We've spent the last 10 months developing our custom

Programming is changing so fast... I'm trying VS Code Cursor + Sonnet 3.5 instead of GitHub Copilot again and I think it's now a net win. Just empirically, over the last few days most of my "programming" is now writing English (prompting and then reviewing and editing the

『マルチモーダル二足歩行ロボット』 モジュラー設計によりフットエンドを簡単に切り替えることができる youtu.be/9Lypkwll6tM #bipedal #robot #Wheeled_Legged #SelfBalancing #locomotion #Python #Sim2Real #OpenSource #SDK #TRON1 #LimXDynamics

you want humanoids? i want this

🚀 Diffusion Policy is great, but how can we achieve category-level generalization? 🤖 Our answer: use explicit 3D and semantic representation to enable category-level generalization capabilities in our recent work GenDP. 🔗 robopil.github.io/GenDP/ #CoRL2024 👇 Threads (1/9)

I'm excited to share Jacta: A Versatile Planner for Learning Dexterous and Whole-body Manipulation. We use sampling-based planning to bootstrap policy learning methods for manipulation tasks. My friend, Jan Brüdigam is presenting the work today at CoRL! jacta-manipulation.github.io

Introducing 🧞Genie 2 🧞 - our most capable large-scale foundation world model, which can generate a diverse array of consistent worlds, playable for up to a minute. We believe Genie 2 could unlock the next wave of capabilities for embodied agents 🧠.

Reinforcement learning is used to speed the production of behavior for the Boston Dynamics Atlas humanoid robot.  At the heart of the learning process is a physics-based simulator that generates training data for a variety of maneuvers.

Abandoned open source repos should be maintained by AI agents

🥋 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

Using reinforcement learning we have expanded the range of techniques the Ultra Mobile Vehicle (UMV) uses to handle terrain and obstacles, including hops, out-of-plane balance, and level-ground flips. Millions of physics-based simulations provide training data to support

Sane Human based on the full video, it looks like it's just running through a sequence of fighting actions as he's disrupting it