Výsledky vyhledávání - "Machine Learning for Robot Control"

  1. 1

    What Matters in Language Conditioned Robotic Imitation Learning Over Unstructured Data Autor Mees, Oier, Hermann, Lukas, Burgard, Wolfram

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.10.2022
    Vydáno v IEEE robotics and automation letters (01.10.2022)
    “…A long-standing goal in robotics is to build robots that can perform a wide range of daily tasks from perceptions obtained with their onboard sensors and…”
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  2. 2

    CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks Autor Mees, Oier, Hermann, Lukas, Rosete-Beas, Erick, Burgard, Wolfram Burgard

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.07.2022
    Vydáno v IEEE robotics and automation letters (01.07.2022)
    “…General-purpose robots coexisting with humans in their environment must learn to relate human language to their perceptions and actions to be useful in a range…”
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  3. 3

    Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments Autor Mittal, Mayank, Yu, Calvin, Yu, Qinxi, Liu, Jingzhou, Rudin, Nikita, Hoeller, David, Yuan, Jia Lin, Singh, Ritvik, Guo, Yunrong, Mazhar, Hammad, Mandlekar, Ajay, Babich, Buck, State, Gavriel, Hutter, Marco, Garg, Animesh

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.06.2023
    Vydáno v IEEE robotics and automation letters (01.06.2023)
    “…We present Orbit , a unified and modular framework for robot learning powered by Nvidia Isaac Sim. It offers a modular design to easily and efficiently create…”
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  4. 4

    Model-Based Meta-Reinforcement Learning for Flight With Suspended Payloads Autor Belkhale, Suneel, Li, Rachel, Kahn, Gregory, McAllister, Rowan, Calandra, Roberto, Levine, Sergey

    ISSN: 2377-3766, 2377-3766
    Vydáno: IEEE 01.04.2021
    Vydáno v IEEE robotics and automation letters (01.04.2021)
    “…Transporting suspended payloads is challenging for autonomous aerial vehicles because the payload can cause significant and unpredictable changes to the…”
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  5. 5

    Real-Time Neural MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms Autor Salzmann, Tim, Kaufmann, Elia, Arrizabalaga, Jon, Pavone, Marco, Scaramuzza, Davide, Ryll, Markus

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.04.2023
    Vydáno v IEEE robotics and automation letters (01.04.2023)
    “…Model Predictive Control (MPC) has become a popular framework in embedded control for high-performance autonomous systems. However, to achieve good control…”
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  6. 6

    CPG-RL: Learning Central Pattern Generators for Quadruped Locomotion Autor Bellegarda, Guillaume, Ijspeert, Auke

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.10.2022
    Vydáno v IEEE robotics and automation letters (01.10.2022)
    “…In this letter, we present a method for integrating central pattern generators (CPGs), i.e. systems of coupled oscillators, into the deep reinforcement…”
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  7. 7

    A Lifelong Learning Approach to Mobile Robot Navigation Autor Liu, Bo, Xiao, Xuesu, Stone, Peter

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.04.2021
    Vydáno v IEEE robotics and automation letters (01.04.2021)
    “…This letter presents a self-improving lifelong learning framework for a mobile robot navigating in different environments. Classical static navigation methods…”
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  8. 8

    Learning Variable Impedance Control via Inverse Reinforcement Learning for Force-Related Tasks Autor Zhang, Xiang, Sun, Liting, Kuang, Zhian, Tomizuka, Masayoshi

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.04.2021
    Vydáno v IEEE robotics and automation letters (01.04.2021)
    “…Many manipulation tasks require robots to interact with unknown environments. In such applications, the ability to adapt the impedance according to different…”
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  9. 9

    Safe-Control-Gym: A Unified Benchmark Suite for Safe Learning-Based Control and Reinforcement Learning in Robotics Autor Yuan, Zhaocong, Hall, Adam W., Zhou, Siqi, Brunke, Lukas, Greeff, Melissa, Panerati, Jacopo, Schoellig, Angela P.

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.10.2022
    Vydáno v IEEE robotics and automation letters (01.10.2022)
    “…In recent years, both reinforcement learning and learning-based control-as well as the study of their safety , which is crucial for deployment in real-world…”
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  10. 10

    Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain Autor Xiao, Xuesu, Biswas, Joydeep, Stone, Peter

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.07.2021
    Vydáno v IEEE robotics and automation letters (01.07.2021)
    “…This letter presents a learning-based approach to consider the effect of unobservable world states in kinodynamic motion planning in order to enable accurate…”
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  11. 11

    K-mixup: Data augmentation for offline reinforcement learning using mixup in a Koopman invariant subspace Autor Jang, Junwoo, Han, Jungwoo, Kim, Jinwhan

    ISSN: 0957-4174, 1873-6793
    Vydáno: Elsevier Ltd 01.09.2023
    Vydáno v Expert systems with applications (01.09.2023)
    “…In this study, we propose a new data augmentation technique, Koopman-mixup (K-mixup), to improve the learning stability and final performance of offline…”
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  12. 12

    KNODE-MPC: A Knowledge-Based Data-Driven Predictive Control Framework for Aerial Robots Autor Chee, Kong Yao, Jiahao, Tom Z., Hsieh, M. Ani

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.04.2022
    Vydáno v IEEE robotics and automation letters (01.04.2022)
    “…In this letter, we consider the problem of deriving and incorporating accurate dynamic models for model predictive control (MPC) with an application to…”
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  13. 13

    Data-driven predictive control of nonholonomic robots based on a bilinear Koopman realization: Data does not replace geometry Autor Rosenfelder, Mario, Bold, Lea, Eschmann, Hannes, Eberhard, Peter, Worthmann, Karl, Ebel, Henrik

    ISSN: 0921-8890
    Vydáno: Elsevier B.V 01.12.2025
    Vydáno v Robotics and autonomous systems (01.12.2025)
    “…Advances in machine learning and the growing trend towards effortless data generation in real-world systems have led to an increasing interest for…”
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  14. 14

    Reinforcement Learning With Evolutionary Trajectory Generator: A General Approach for Quadrupedal Locomotion Autor Shi, Haojie, Zhou, Bo, Zeng, Hongsheng, Wang, Fan, Dong, Yueqiang, Li, Jiangyong, Wang, Kang, Tian, Hao, Meng, Max Q.-H.

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.04.2022
    Vydáno v IEEE robotics and automation letters (01.04.2022)
    “…Recently reinforcement learning (RL) has emerged as a promising approach for quadrupedal locomotion, which can save the manual effort in conventional…”
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  15. 15

    A stable method for task priority adaptation in quadratic programming via reinforcement learning Autor Testa, Andrea, Laghi, Marco, Bianco, Edoardo Del, Raiola, Gennaro, Hoffman, Enrico Mingo, Ajoudani, Arash

    ISSN: 0736-5845, 1879-2537
    Vydáno: Elsevier Ltd 01.02.2025
    “…In emerging manufacturing facilities, robots must enhance their flexibility. They are expected to perform complex jobs, showing different behaviors on the…”
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  16. 16

    Deep Koopman Operator With Control for Nonlinear Systems Autor Shi, Haojie, Meng, Max Q.-H.

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.07.2022
    Vydáno v IEEE robotics and automation letters (01.07.2022)
    “…Recently Koopman operator has become a promising data-driven tool to facilitate real-time control for unknown nonlinear systems. It maps nonlinear systems into…”
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  17. 17

    Learning-Based Balance Control of Wheel-Legged Robots Autor Cui, Leilei, Wang, Shuai, Zhang, Jingfan, Zhang, Dongsheng, Lai, Jie, Zheng, Yu, Zhang, Zhengyou, Jiang, Zhong-Ping

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.10.2021
    Vydáno v IEEE robotics and automation letters (01.10.2021)
    “…This letter studies the adaptive optimal control problem for a wheel-legged robot in the absence of an accurate dynamic model. A crucial strategy is to exploit…”
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  18. 18

    OmniDrones: An Efficient and Flexible Platform for Reinforcement Learning in Drone Control Autor Xu, Botian, Gao, Feng, Yu, Chao, Zhang, Ruize, Wu, Yi, Wang, Yu

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.03.2024
    Vydáno v IEEE robotics and automation letters (01.03.2024)
    “…In this letter, we introduce OmniDrones , an efficient and flexible platform tailored for reinforcement learning in drone control, built on Nvidia's Omniverse…”
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  19. 19

    InsertionNet - A Scalable Solution for Insertion Autor Spector, Oren, Castro, Dotan Di

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.07.2021
    Vydáno v IEEE robotics and automation letters (01.07.2021)
    “…Complicated assembly processes can be described as a sequence of two main activities: grasping and insertion. While general grasping solutions are common in…”
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  20. 20

    Learning Robust and Agile Legged Locomotion Using Adversarial Motion Priors Autor Wu, Jinze, Xin, Guiyang, Qi, Chenkun, Xue, Yufei

    ISSN: 2377-3766, 2377-3766
    Vydáno: Piscataway IEEE 01.08.2023
    Vydáno v IEEE robotics and automation letters (01.08.2023)
    “…Developing both robust and agile locomotion skills for legged robots is non-trivial. In this work, we present the first blind locomotion system capable of…”
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