Suchergebnisse - Optimization and Optimal Control Reinforcement Learning Machine Learning for Robot Control

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    2-DOF Robot Optimal Control via Artificial Neural Network Reinforcement Learning von Romasevych, Yuriy, Loveikin, Viatcheslav

    Veröffentlicht: IEEE 02.10.2023
    “… In the study optimal control problem a 2-DOF robot is stated. Criterion, which must be minimized, reflected RMS of drives power and length of the load trajectory in the "x- y" plane …”
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    Tagungsbericht
  2. 2

    Robot Arm Movement Control by Model-based Reinforcement Learning using Machine Learning Regression Techniques and Particle Swarm Optimization von Mueangprasert, Meta, Chermprayong, Pisak, Boonlong, Kittipong

    Veröffentlicht: IEEE 18.01.2023
    “… The robot arm movement control is important in the use of robot arms. This paper presents model-based reinforcement learning (MBRL …”
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    Tagungsbericht
  3. 3

    Robot Control Optimization Using Reinforcement Learning von Song, Kai-Tai, Sun, Wen-Yu

    ISSN: 0921-0296, 1573-0409
    Veröffentlicht: Dordrecht Kluwer 01.03.1998
    Veröffentlicht in Journal of intelligent & robotic systems (01.03.1998)
    “… This paper proposes a reinforcement learning control approach for overcoming such drawbacks …”
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    Journal Article
  4. 4

    Deep Reinforcement Learning for Robot Batching Optimization and Flow Control von Hildebrand, Max, Andersen, Rasmus S., Bøgh, Simon

    ISSN: 2351-9789, 2351-9789
    Veröffentlicht: Elsevier B.V 2020
    Veröffentlicht in Procedia manufacturing (2020)
    “… Robot batching is an optimization problem found in many industrial applications. Current state-of-the-art approaches utilize a combination of heuristic based parameters and statistical analysis …”
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    Journal Article
  5. 5

    Optimal control of a two‐wheeled self‐balancing robot by reinforcement learning von Guo, Linyuan, Rizvi, Syed Ali Asad, Lin, Zongli

    ISSN: 1049-8923, 1099-1239
    Veröffentlicht: Bognor Regis Wiley Subscription Services, Inc 01.04.2021
    “… Summary This article concerns optimal control of the linear motion, tilt motion, and yaw motion of a two‐wheeled self‐balancing robot (TWSBR …”
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    Journal Article
  6. 6

    Neural Networks Enhanced Optimal Admittance Control of Robot-Environment Interaction Using Reinforcement Learning von Peng, Guangzhu, Chen, C. L. Philip, Yang, Chenguang

    ISSN: 2162-237X, 2162-2388, 2162-2388
    Veröffentlicht: United States IEEE 01.09.2022
    “… In this paper, an adaptive admittance control scheme is developed for robots to interact with time-varying environments …”
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    Journal Article
  7. 7

    Optimal balancing control of bipedal robots using reinforcement learning von Fang Peng, Lijia Ding, Zhijun Li, Chenguang Yang, Chun-Yi Su

    Veröffentlicht: IEEE 01.06.2016
    “… The balance control a bipedal robot in the presence of external disturbances is still a challenge …”
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    Tagungsbericht
  8. 8

    Agile Legged Robots Through Reinforcement Learning and Optimal Control von Yang, Yuxiang

    ISBN: 9798384094050
    Veröffentlicht: ProQuest Dissertations & Theses 01.01.2024
    “… Traditional optimal control methods, which rely on predefined physics models to optimize motor commands, can precisely track desired motions but cannot plan for complex, long-horizon trajectories due …”
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    Dissertation
  9. 9

    Online parameter adaptive control of mobile robots based on deep reinforcement learning under multiple optimisation objectives von Sui, Xiuli, Chen, Haiyong

    ISSN: 2517-7567, 1873-9601, 2517-7567, 1873-961X
    Veröffentlicht: Dordrecht John Wiley & Sons, Inc 01.12.2024
    Veröffentlicht in Cognitive computation and systems (01.12.2024)
    “… Fixed control parameters and various optimisation objectives significantly limit the robot control performance …”
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    Journal Article
  10. 10

    An Admittance Parameter Optimization Method Based on Reinforcement Learning for Robot Force Control von Hu, Xiaoyi, Liu, Gongping, Ren, Peipei, Jia, Bing, Liang, Yiwen, Li, Longxi, Duan, Shilin

    ISSN: 2076-0825, 2076-0825
    Veröffentlicht: Basel MDPI AG 01.09.2024
    Veröffentlicht in Actuators (01.09.2024)
    “… control method, which combines classical adaptive control and machine learning methods to make them use their respective advantages in different stages of training and, ultimately, achieve better performance …”
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    Journal Article
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    Optimization Control of Attitude Stability for Hexapod Robots Based on Reinforcement Learning von Ji, Shujie, Wei, Wu, Liu, Xiongding, Wu, Junqi

    ISSN: 2169-3536, 2169-3536
    Veröffentlicht: Piscataway IEEE 2024
    Veröffentlicht in IEEE access (2024)
    “… To enhance the attitude stability of hexapod robots on rough terrain, this paper introduces a layered modular motion control method, termed reinforcement learning integrated with foot impedance …”
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    Journal Article
  13. 13

    Decentralized Reinforcement Learning Robust Optimal Tracking Control for Time Varying Constrained Reconfigurable Modular Robot Based on ACI and Q-Function von Dong, Bo, Li, Yuanchun

    ISSN: 1024-123X, 1563-5147
    Veröffentlicht: Cairo, Egypt Hindawi Publishing Corporation 01.01.2013
    Veröffentlicht in Mathematical problems in engineering (01.01.2013)
    “… A novel decentralized reinforcement learning robust optimal tracking control theory for time varying constrained reconfigurable modular robots based on action-critic-identifier (ACI …”
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    Journal Article
  14. 14

    Reinforcement Learning Control of an Aerial Robot Based on a Tuned Proximal Policy Optimization in Takeoff and Hover Phases von Esfandiari, Mohamadamin, Amiri Atashgah, M. A.

    ISSN: 2572-6889
    Veröffentlicht: IEEE 15.11.2022
    “… This paper is dedicated to the implementation of a control system for a flying robot based on reinforcement learning (RL …”
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    Tagungsbericht
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    Value Iteration-Based Adaptive Fuzzy Backstepping Optimal Control of Modular Robot Manipulators via Integral Reinforcement Learning von Dong, Bo, Jiang, Hucheng, Cui, Yiming, Zhu, Xinye, An, Tianjiao

    ISSN: 1562-2479, 2199-3211
    Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2024
    Veröffentlicht in International journal of fuzzy systems (01.06.2024)
    “… The integral reinforcement learning (IRL) is integrated into the VI algorithm, which solves the optimal tracking control issue without system drift dynamics …”
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    Journal Article
  16. 16

    Adaptive Prescribed-Time Optimal Control for Flexible-Joint Robots via Reinforcement Learning von Xie, Shiyu, Sun, Wei, Sun, Yougang, Su, Shun-Feng

    ISSN: 2168-2216, 2168-2232
    Veröffentlicht: IEEE 01.04.2025
    “… ) robot systems utilizing the reinforcement learning (RL) strategy. The uniqueness of this method lies in its ability to ensure optimal tracking performance for n-link …”
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    Journal Article
  17. 17

    Student-t policy in reinforcement learning to acquire global optimum of robot control von Kobayashi, Taisuke

    ISSN: 0924-669X, 1573-7497
    Veröffentlicht: New York Springer US 01.12.2019
    Veröffentlicht in Applied intelligence (Dordrecht, Netherlands) (01.12.2019)
    “… optimum for tasks to be learned. The actor-critic algorithm is one of the policy-gradient methods in reinforcement learning, and is proved to learn the policy converging on one of the local optima …”
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    Journal Article
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    Adaptive Optimal Control of Four-Wheel Omni Robot using Reinforcement Learning von Khac, Tuan Nguyen, Thai Huu, Nguyen, Van, Minh Nguyen, Bui Trung, Tuyen

    ISSN: 2325-0925
    Veröffentlicht: IEEE 26.08.2021
    “… This paper develops an optimal adaptive traction control structure based on reinforcement learning for a 4-wheel Omni robot in the condition in which a part of the model is known …”
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    Tagungsbericht
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    Inferring Human-Robot Performance Objectives During Locomotion Using Inverse Reinforcement Learning and Inverse Optimal Control von Liu, Wentao, Zhong, Junmin, Wu, Ruofan, Fylstra, Bretta L, Si, Jennie, Huang, He Helen

    ISSN: 2377-3766, 2377-3766
    Veröffentlicht: Piscataway IEEE 01.04.2022
    Veröffentlicht in IEEE robotics and automation letters (01.04.2022)
    “… , we validated the effectiveness of two solution approaches to solving the inverse problem using inverse reinforcement learning (IRL …”
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    Journal Article
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    Fault Estimate and Reinforcement Learning Based Optimal Output Feedback Control for Single-Link Robot Arm Model von Liu, Sihan, Yan, Hailong, Zhao, Lixia, Gao, Dongxiang

    ISSN: 1816-093X, 1816-0948
    Veröffentlicht: Hong Kong International Association of Engineers 01.01.2025
    Veröffentlicht in Engineering letters (01.01.2025)
    “… This paper presents an optimal output feedback tracking control scheme for a single-link robot arm (SLRA …”
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    Journal Article