Hai Nguyen
@HaiNguy69482974Ph.D. Student on Robot Learning under Partial Observability @Northeastern / Applied Scientist Intern @Amazon / Ex-Intern @omron_sinicx / @CheveningAA Alumni
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#CoRL2024 OrbitGrasp: SE(3)-Equivariant Grasp Learning Led by @boce_hu Orbitgrasp maps each point in the cloud to a continuous grasp quality function using spherical harmonics. Our method outperforms all baselines across all settings and tasks. Presenting at Poster Session 1.
Please check out my final publication during my PhD. Happy to chat more at #CoRL2024, poster session 2.
#CoRL2024 Leveraging Mutual Information for Asymmetric Learning under Partial Observability led by @HaiNguy69482974 Addressing asymmetric learning under partial observability (state availability at training) by rewarding actions leads to histories that gain info about the state.
#CoRL2024 ThinkGrasp: A Vision-Language System for Strategic Part Grasping in Clutter by @RubyFreax A plug-and-play vision-language grasping system that uses GPT-4o’s advanced contextual reasoning for heavy clutter environment grasping strategies. Presenting at Poster Session 3.
#CoRL2024 IMAGINATION POLICY: Using Generative Point Cloud Models for Learning Manipulation Policies Led by @HaojieHuang13 A key-frame multi-task policy can generate key poses (imagine) and do manipulation precisely with sample efficiency. Presenting at Poster Session 4.
#CoRL2024 Equivariant Diffusion Policy Led by @Dian_Wang_ A sample efficient BC algorithm based on equi diffusion. It leverages symmetry to boost learning with 5x less training data and mastering complex tasks with <60 demos. Presenting at Oral Session 1 and Poster Session 2.
🤖 Excited for #RSS2024? Don’t miss our workshop on "Geometric and Algebraic Structure in Robot Learning"! Submit workshop papers (by 6/10 AOE) and dive into discussions on leveraging these structures for enhanced #robotics. 🚀🔍 Join us on 07/19 in Delft, Netherlands!
I wrote a survey covering decentralized training and execution methods for cooperative MARL. Hopefully, people find it useful. Any feedback is more than welcome! arxiv.org/abs/2405.06161
Happy to share a @ieee_ras_icra paper from my last summer internship in beautiful Tokyo at @omron_sinicx We learned the Peg-In-Hole from tactile feedback directly on a soft wrist in 3 hours by leveraging domain symmetry and demonstrations.
我々は、ICRA2024で柔軟なロボットの部品挿入の研究を発表します。手先の姿勢を観測できない部分観測な環境で、力覚を使用した学習を考えました。 部品の幾何的な対称性を考慮し効率的な強化学習も提案しました。インターン @HaiNguy69482974さん、OSX @Tdash_Kozさん、@cambel07さんとの研究です。
How can we combine the benefits of Fourier Transformation to further facilitate the efficiency of policy learning? In our Fourier Transporter (FouTran), we introduce a novel 3D Pick-Place Model with Bi-equivariance property. Paper: arxiv.org/pdf/2401.12046
#ICLR24 We proposed FourTran, a very sample-efficient 3D manipulation pick-place model. 1. It can learn a nontrivial 3D policy with less than 10 demos. 2. It represents 3D action distribution in Fourier Space. Check it in the Poster Session 4 at 4:30 PM Vienna time (10:30 EDT)
Happy to chat more on today's poster session from 4.15 to 5.00 pm at CoRL.
Happy to share our #CoRL23 paper about leveraging symmetry for POMDPs. We formulate group-invariant POMDPs that are symmetric in the history space. As expected, equivariant recurrent policies shine in solving them. For more, please see sites.google.com/view/equi-rl-p….
New #IROS2023 paper alert: A Bayesian-Adaptive RL with mixed observability assumption, training directly on hardware, greatly more sample-efficient >> RL methods. Joint w/ SammieKatt @YuchenXiao5 @cjdamato @LLPR_NEU Paper: arxiv.org/abs/2307.11954 Video: youtube.com/watch?v=H9xp60…
Delighted to announce the schedule of the Workshop on Symmetries in Robot Learning @RoboticsSciSys! Join the discussion with our incredible speakers @tesssmidt @haosu_twitr @GhaffariMaani @andyzeng_ @erikjbekkers @HughWang19 Can't wait to see you there! sites.google.com/view/rss23-sym.
Excited to announce the #RSS2023 Workshop on Symmetries in Robot Learning! Submit your work and join us to explore how symmetries can help in robotics with our incredible speakers @andyzengtweets @HughWang19 @haosu_twitr @tesssmidt @erikjbekkers Website: sites.google.com/view/rss23-sym.
We(@cjdamato) recently published MacroMARL(github.com/yuchen-x/Macro…), including both value-based and policy-gradient-based algorithms for multi-agent asynchronous learning and execution, as well as three macro-action-based multi-agent domains. To find more, please check it out!
Interested in partial observability? Come to my online poster session at @CoRL2022 (online session 2, Sunday, Dec 18, 7:30-8.00 AM, Auckland time, i.e., Saturday, Dec 17, 1:30 - 2:00 PM, EST time) w/ @RobotPlatt @cjdamato @DianWang1007 @AndreaBaisero @LLPR_NEU @HelpingHandsLab
Glad to share our #CoRL22 paper arxiv.org/abs/2211.01991 about using MDP solutions to efficiently learn POMDPs during offline training. We proposed a SAC-like agent that balances between acting like an MDP expert and for environment rewards.
Tmr(Thurs), 4-6pm, Hall J 613 #NeurIPS2022, my advisor Chris @cjdamato is going to present how we enable agents to asynchronously learn and execute. Please stop by to check the details and know more about the lab @LLPR_NEU Also, feel free to contact me for any questions!
I am very excited to share that our paper "Asynchronous Actor-Critic for Multi-Agent Reinforcement Learning" (arxiv.org/abs/2209.10113) has been accepted to #NeurIPS2022. A step towards asynchronous and hierarchical behaviors in real-world multi-agent/robot systems.
LLPR member Daniel Melcer shows decentralized shielding can be an effective solution for multi-agent RL and doesn’t require communication between agents #NeurIPS2022 Link to paper: openreview.net/pdf?id=JO9o3Dg…
Looking for an easy-to-read review paper on Grasp Learning? I just wrote one for Annual Reviews that I'm excited about. Check it out: arxiv.org/abs/2211.04895
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