Sumeet Singh
@Sumeet_Robotics
Research scientist at Google Brain Robotics in NYC. All views are my own.
Bạn có thể thích
We’re making robots more capable than ever in the physical world. 🤖 Gemini Robotics 1.5 is a levelled up agentic system that can reason better, plan ahead, use digital tools such as @Google Search, interact with humans and much more. Here’s how it works 🧵
Meet Gemini Robotics: our latest AI models designed for a new generation of helpful robots. 🤖 Based on Gemini 2.0, they bring capabilities such as better reasoning, interactivity, dexterity and generalization into the physical world. 🧵 goo.gle/gemini2-roboti…
A well reasoned and considered response.
My student sent me this list saying they have to improve themselves in many areas. Such a list can do more harm than good. While I appreciate author's intention to motivate one for greatness, I don't think it can be planned. But you can plan to be a "good researcher."
Instead of blindly trusting an LLM to plan a robot's next step, see how to use Conformal Prediction to ground its uncertainty and ask for help when needed. 👇
LLMs can generate plans and write robot code 📝 but they can also make mistakes. How do we get LLMs to 𝘬𝘯𝘰𝘸 𝘸𝘩𝘦𝘯 𝘵𝘩𝘦𝘺 𝘥𝘰𝘯'𝘵 𝘬𝘯𝘰𝘸 🤷 and ask for help? Read more on how we can do this (with statistical guarantees) for LLMs on robots 👇 robot-help.github.io
Presenting our robotic table wiping work today at 3pm, Pod 15 at #ICRA2023 ➡️ Come have a chat about reinforcement learning, trajectory optimization, and stochastic dynamics modeling
📢Excited to share our #ICRA2023 work on robotic table wiping via RL + optimal control! 📖 arxiv.org/abs/2210.10865 🎥 youtu.be/inORKP4F3EI 💡RL (for high-level planning) + trajectory optimization (for precise control) can solve complex tasks without on-robot data collection ⬇️
Read about Thomas' internship last summer!
Excited to share the work @thomas__lew , @Sumeet_Robotics, @robobenjie, many others @GoogleAI Robotics and I have been doing to make robots helpful for everyday tasks.
A summary of Google Robotics in 2022, including our work on novel trajectory optimizers and applications!
Glad to see our Performer-MPC, a 8.3M-parameter Transformer model with <10ms on-robot latency paired with Model Predictive Control, is mentioned by this Robotics@Google blog! ai.googleblog.com/2023/02/google… Check out our paper at cs.gmu.edu/~xiao/papers/p… @kchorolab @xf1280 @vikassindhwani
Great article on LLMs - MLE training is exactly lossy data compression! I know RLHF is changing the loss to maximize predicted human ratings, but it still feels like a bit like lipstick on a pig to me (although who doesnt like bbq now and then? ;) newyorker.com/tech/annals-of…
Check out the table-wiping robot from Thomas' internship! Great example of combining the strengths of RL and classical trajectory optimization for modularity, generalization, and efficient learning. Disclaimer: surface cleaner sold separately 🙃
📢Excited to share our #ICRA2023 work on robotic table wiping via RL + optimal control! 📖 arxiv.org/abs/2210.10865 🎥 youtu.be/inORKP4F3EI 💡RL (for high-level planning) + trajectory optimization (for precise control) can solve complex tasks without on-robot data collection ⬇️
I'm excited to present Single-Level Differentiable Contact Simulation. It's a novel formulation that unifies contact dynamics and collision detection in a single optimization problem. paper: arxiv.org/abs/2212.06764 code: github.com/simon-lc/Silic… video: youtu.be/oaGLTR13iF8
Work from our @GoogleAI team - training robots to play table tennis to better understand how they learn in dynamic + high-speed settings. One project achieved a 300+ hit rally, while another is focused on matching the precision of amateur human players 🏓 ai.googleblog.com/2022/10/table-…
Come check out this workshop on Monday at #RSS2022! I'll be presenting (poster + spotlight) our latest work on multiscale sensor fusion architectures for continuous-time control using Neural CDEs.
Our #RSS2022 workshop on "Overlooked Aspects of Imitation Learning" is this Monday June 27 - join us virtual or in-person! We have a wonderful lineup of speakers (@ancadianadragan @ankurhandos @chelseabfinn @LerrelPinto Mohi Khansari @shimon8282) See: tinyurl.com/2pjt86uk
United States Xu hướng
- 1. Auburn 46.1K posts
- 2. At GiveRep N/A
- 3. Brewers 65.5K posts
- 4. Cubs 56.7K posts
- 5. #SEVENTEEN_NEW_IN_TACOMA 33.3K posts
- 6. Georgia 68.4K posts
- 7. Gilligan's Island 4,836 posts
- 8. Utah 25.5K posts
- 9. #byucpl N/A
- 10. MACROHARD 4,375 posts
- 11. Arizona 42K posts
- 12. Kirby 24.3K posts
- 13. Wordle 1,576 X N/A
- 14. #AcexRedbull 4,268 posts
- 15. Michigan 63.2K posts
- 16. Boots 51.1K posts
- 17. #Toonami 2,993 posts
- 18. #BYUFootball 1,020 posts
- 19. mingyu 91.2K posts
- 20. Hugh Freeze 3,281 posts
Bạn có thể thích
-
Marco Pavone
@drmapavone -
Anirudha Majumdar
@Majumdar_Ani -
David Held
@davheld -
Anca Dragan
@ancadianadragan -
L4DC Conference
@l4dc_conf -
SISL
@SISLaboratory -
Rika Antonova
@contactrika -
Jeannette Bohg
@leto__jean -
Learning Systems and Robotics Lab (is hiring!)
@learnsyslab -
Boris Ivanovic
@iamborisi -
Guanya Shi
@GuanyaShi -
Roberto
@RobobertoMM -
Intelligent Autonomous Systems Group
@ias_tudarmstadt -
Georgia Chalvatzaki @ CoRL+Humanoids 2025
@GeorgiaChal -
Yuval Tassa
@yuvaltassa
Something went wrong.
Something went wrong.