NVIDIA at CoRL 2024

November 6–9
Science Congress Center Munich
Munich, Germany

    Discover What’s Possible With NVIDIA Robotics

    The Conference on Robot Learning (CoRL) is an annual international conference focusing on the intersection of robotics and machine learning. Explore the work to see how NVIDIA Research collaborates with CoRL members to deliver AI breakthroughs across the community.

    News and Announcements at CoRL 2024

    NVIDIA Advances Robot Learning With AI and Simulation Tools

    New humanoid robot learning workflows and AI world model development tools can help robotics developers accelerate their work on AI-enabled robots.

    Read the Blog

    Hugging Face and NVIDIA to Accelerate Open-Source AI Robotics Research and Development

    Hugging Face’s LeRobot open-source frameworks combined with NVIDIA technologies will enable researchers and developers to drive advances across industries.

    Read the Announcement

    State-of-the-Art Multimodal Generative AI Model Development With NVIDIA NeMo

    Accelerate petabytes of video data processing by up to 7X with NVIDIA NeMo™ Curator, and get high-quality, high-compression tokenization with up to 12X faster, accurate visual reconstruction with Cosmos™ tokenizers.

    Learn More

    Advancing Humanoid Robot Sight and Skill Development

    Discover the latest NVIDIA Project GR00T workflows that can help create more intelligent, adaptive, and capable humanoid robots.

    Explore the Workflows

    Building a Large-Scale Dexterous Hand Dataset for Humanoid Robots

    Using NVIDIA Isaac Sim™, Galbot developed a comprehensive dataset for dexterous robotic grasps that can be applied to any dexterous robotic hand.

    Dive Into the Dataset

    Training Humanoids for Real-World Roles

    Fourier is developing advanced humanoid robots that can be integrated in real-world applications where precision and agility are critical.

    Read the Spotlight

    NVIDIA Research at CoRL

    NVIDIA’s accepted papers at CoRL 2024 feature a range of groundbreaking research in the field of robotics. From humanoids to policy, explore the work NVIDIA is bringing to the CoRL community. 

    *Denotes equal contribution to the paper.

    ReMEmbR: Building and Reasoning Over Long-Horizon Spatio-Temporal Memory for Robot Navigation

    Abrar Anwar, John Welsh, Joydeep Biswas, Soha Pouya, Yan Chang

    SkillMimicGen: Automated Demonstration Generation for Efficient Skill Learning and Deployment

    Caelan Garrett*, Ajay Mandlekar*, Bowen Wen, Dieter Fox

    Avoid Everything: Model-Free Collision Avoidance With Expert-Guided Fine-Tuning

    Adam Fishman, Aaron Walsman, Mohak Bhardwaj, Wentao Yuan, Balakumar Sundaralingam, Byron Boots, Dieter Fox

    RoboPoint: A Vision-Language Model for Spatial Affordance Prediction for Robotics

    Wentao Yuan, Jiafei Duan, Valts Blukis, Wilbert Pumacay, Ranjay Krishna, Adithyavairavan Murali, Arsalan Mousavian, Dieter Fox

    DiffusionSeeder: Seeding Motion Optimization With Diffusion for Rapid Motion Planning

    Raven Huang, Balakumar Sundaralingam, Arsalan Mousavian, Adithyavairavan Murali, Ken Goldberg, Dieter Fox

    NOD-TAMP: Generalizable Long-Horizon Planning With Neural Object Descriptors

    Shuo Cheng, Caelan Garrett*, Ajay Mandlekar*, Danfei Xu

    Discovering Robotic Interaction Modes With Discrete Representation Learning

    Liquan Wang, Ankit Goyal, Haoping Xu, Animesh Garg

    Manipulate-Anything: Automating Real-World Robots Using Vision-Language Models

    Jiafei Duan, Wentao Yuan, Wilbert Pumacay, Yi Ru Wang, Kiana Ehsani, Dieter Fox, Ranjay Krishna

    DextrAH-G: Pixels-to-Action Dexterous Arm-Hand Grasping With Geometric Fabrics

    Tyler Ga Wei Lum*, Martin Matak*, Viktor Makoviychuk, Ankur Handa, Arthur Allshire, Tucker Hermans, Nathan D. Ratliff*, Karl Van Wyk*

    Multi-Task Interactive Robot Fleet Learning With Visual World Models

    Huihan Liu, Yu Zhang, Vaarij Betala, Evan Zhang, James Liu, Crystal Ding, Yuke Zhu

    Harmon: Whole-Body Motion Generation of Humanoid Robots From Language Descriptions

    Zhenyu Jiang, Yuqi Xie, Jinhan Li, Ye Yuan, Yifeng Zhu, Yuke Zhu

    OKAMI: Teaching Humanoid Robots Manipulation Skills Through Single Video Imitation

    Jinhan Li, Yifeng Zhu, Yuqi Xie, Zhenyu Jiang, Mingyo Seo, Georgios Pavlakos, Yuke Zhu

    SPIRE: Synergistic Planning, Imitation, and Reinforcement Learning for Long-Horizon Manipulation

    Zihan Zhou, Animesh Garg, Dieter Fox, Caelan Reed Garrett, Ajay Mandlekar

    Gentle Manipulation of Tree Branches: A Contact-Aware Policy Learning Approach

    Jay Jacob, Shizhe Cai, Paulo Vinicius Koerich Borges, Tirthankar Bandyopadhyay, Fabio Ramos

    RAM: Retrieval-Based Affordance Transfer for Generalizable Zero-Shot Robotic Manipulation

    Yuxuan Kuang, Junjie Ye, Haoran Geng, Jiageng Mao, Congyue Deng, Leonidas Guibas, He Wang, Yue Wang

    Tokenize the World into Object-level Knowledge to Address Long-tail Events in Autonomous Driving

    Thomas Tian, Boyi Li, Xinshuo Weng, Yuxiao Chen, Edward Schmerling, Yue Wang, Boris Ivanovic, Marco Pavone

    Promptable Closed-Loop Traffic Generation

    Shuhan Tan, Boris Ivanovic, Yuxiao Chen, Boyi Li, Xinshuo Weng, Yulong Cao, Philipp Kraehenbuehl, Marco Pavone

    Guided Reinforcement Learning for Robust Multi-Contact Loco-Manipulation

    Jean Pierre Sleiman, Mayank Mittal, Marco Hutter

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    NVIDIA’s workshops at CoRL 2024 feature a range of groundbreaking research in the field of robotics. From humanoids to policy, explore the work NVIDIA is bringing to the CoRL community.

    3rd Workshop on Language and Robot Learning: Language as an Interface

    Spotlight talk: ReMEmbR: Building and Reasoning Over Long-Horizon Spatio-Temporal Memory for Robot Navigation

    Learning Robot Fine and Dexterous Manipulation: Perception and Control

    CoRoboLearn: Advancing Learning for Human-Centered Collaborative Robots

    Differentiable Optimization at All Scales: Simulation, Estimation, Learning, and Control

    Learning Effective Abstractions for Planning (LEAP) 

    1st Workshop on X-Embodiment Robot Learning 

    Workshop on Whole-Body Control and Bimanual Manipulation: Applications in Humanoids and Beyond

    A World Built by Robots: Workshop on Learning Robotic Assembly of Industrial and Everyday Objects

    SAFE-ROL: Safe and Robust Robot Learning for Operation in the Real World

    Lifelong Learning for Household Robots

    Morphology-Aware Policy and Design Learning Workshop (MAPoDeL)

    Mastering Robot Manipulation in a World of Abundant Data)

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    NVIDIA Research

    Discover our most recent AI research and the new capabilities deep learning brings to visual and audio applications. Explore the latest innovations and see how you can bring them into your own work.

    Explore Here

    Explore NVIDIA Robotics Solutions

    Isaac ROS

    NVIDIA Isaac™ ROS is built on the open-source ROS 2 software framework. This means the millions of developers in the ROS community can take advantage of NVIDIA-accelerated libraries and AI models to accelerate their development and deployment workflows.

    Learn About Isaac ROS

    Isaac Perceptor

    Isaac Perceptor is a workflow built on Isaac ROS that lets you quickly build robust autonomous mobile robots (AMRs) that can perceive, localize, and operate in unstructured environments like warehouses or factories.

    Discover Isaac Perceptor

    Isaac Manipulator

    The Isaac Manipulator workflow is built on Isaac ROS, letting you build AI-enabled robot arms—or manipulators—that can seamlessly perceive, understand, and interact with their environments.

    Check Out Isaac Manipulator

    Isaac Sim

    NVIDIA Isaac Sim™ is a reference application enabling developers to design, simulate, test, and train AI-based robots and autonomous machines in a physically based virtual environment.

    Explore Isaac Sim

    NVIDIA Robotics Developer Resources and Community

    Documentation

    Explore the NVIDIA Isaac ROS document hub for key resources, like a getting started guide, reference workflows, packages, and more.

    See Isaac ROS Documentation

    Training

    NVIDIA offers extensive robotics training and resources to enhance your expertise in AI and related technologies. 

    Get Started

    Forums

    Dive into the NVIDIA robotics community to connect, ask questions, and receive expert advice and tailored recommendations.

    Dive Into Forums

    Livestream

    Participate in our regular robotics livestreams to interact with a vibrant community of developers and industry experts.

    Join Our Livestream

    Like No Place You’ve Ever Worked

    Working at NVIDIA, you’ll solve some of the world’s hardest problems and discover never-before-seen ways to improve the quality of life for people everywhere. From healthcare to robots, self-driving cars to blockbuster movies, you’ll experience it all. Plus, there’s a growing list of new opportunities every single day. Explore all of our open roles, including internships and new college graduate positions.

    Learn more about our current job openings, as well as university jobs.

    Explore Here

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