#robotlearning результаты поиска
Last week, I had the amazing opportunity to attend the 2025 Conference on Robot Learning (CoRL) in South Korea 🇰🇷. Incredible talks, demos, and made great connections with researchers and innovators from around the world. #CoRL2025 #RobotLearning #AI 🧵
Robots in our group are finally moving! Excited to share the first #RobotLearning project from my group led by Han Qi and @hcy1n: Control-oriented Clustering of Visual Latent Representation In classical robotics, "perception" and "control" are separated with an explicit state…
Many recent #robotlearning works, such as Hi-robot, Gemini-Robotics, Helix, etc., use different types of hierarchical planning. In this lecture, I review hierarchical #reinforcementlearning for humanoid control, before discussing how these methods are used in recent works.
🚀 Nvidia and the University of Texas at Austin just dropped some next-level robot training software called DrEureka. 🦾 It’s got GPT-4 or another chatbot pre-installed, and then it hooks up with a robot in virtual space to teach it new tricks. 🤖✨ #TechRevolution #RobotLearning
Releasing my next set of lectures from my class on #Robotlearning. Last week's topic was scaling #BehaviorCloning
🌏 I will be traveling to the US to attend the Conference on Robot Learning #CoRL23 where I am part of 4 contributed papers👇. Excited to meet with the #robotlearning community again and chat about cool new research directions and future collaborations. @QUTRobotics
In my next lecture on #robotlearning, I cover generalization across sequences and robots. This generalization across sequences of actions or states is a challenging, data-intensive process that requires experience across various robots and tasks.
🤖#RoboticsAI #RobotLearning! Are we targeting the right robotic tasks? Industrial or home application? Let's dive deep at the CoRL’23 Workshop, Nov 6, 8:30am-12:30pm EST, Hub 1 @corl_conf, Atlanta. Don't miss the flaming debate at 11:50am! 🔥 sites.google.com/view/corl23-ta…
#RobotLearning lecture update. These next lectures cover deep #qlearning fundamentals quickly and then get into the challenges of training #largemodels, maintaining the contraction property with target networks, network structure, and better optimizers.
I'm excited about today's talk at the @MontrealRobots #robotlearning seminar @Mila_Quebec. We have @keerthanpg talking about her recent work at @GoogleDeepMind!
Excited to share our baseline agents playing against each other! Can't wait to see the agents of the challenge participants! Big thanks @Jan_R_Peters @davide_tateo @hbouammar for their help! Join our robot #AirHockeyChallenge and show your #RobotLearning skills! 🏒🤖
Today we are excited to kick off the Air Hockey Challenge! 🏑🥅🦾 We’ve been working on air hockey for several years now, and are opening up our simulator and robots for a competition! There’s a total of €6k in prize money for the best agents, kindly provided by @Huawei! [1/3]
Honored for the early career keynote at #CoRL2024 last week—unforgettable milestone! Grateful to the community for the recognition. From a small lab in Greece to leading my own group @TUDarmstadt, this journey fuels me to push #RobotLearning further. #ERCStG SIREN is the start!🦾
Finally finished my slides for the International Symposium on #RobotLearning tomorrow morning at the @UTokyo_News_en. Looking forward to covering two recent projects as examples of the role of #ReinforcementLearning in the age of Gemini, ChatGPT and friends. Thank you…
📢 The CoRL 2025 accepted papers are now live on OpenReview! Check out the list of exciting contributions in robot learning: openreview.net/group?id=robot… #CoRL2025 #RobotLearning
How can policies be trained from offline data and scaled to larger models? In this #robotlearning lecture, I cover common methods for training policies from fixed data and discuss recent research on scaling these methods to #largemodels and #largedatasets.
Honored to contribute to the robotics community as an Associate Editor for #RobotLearning at #ICRA2026 in Vienna. Excited to see great work coming through. Good luck to all the authors!
Deep policy gradients are used to train the largest #LLM models and are the main #reinforcementlearning algorithm in sim2real transfer. In my next set of lectures on #robotlearning I cover the basics of policy gradients to the methods used to train #AlphaStar (in part 2).
Cool demo on upside-down object re-orientation presented by the team from German Aerospace Center (DLR). #Robotlearning #ReinforcementLearning #AI #CoRL2024
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