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
Veröffentlicht: IEEE 02.10.2023Veröffentlicht in 2023 IEEE 4th KhPI Week on Advanced Technology (KhPIWeek) (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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Robot Arm Movement Control by Model-based Reinforcement Learning using Machine Learning Regression Techniques and Particle Swarm Optimization
Veröffentlicht: IEEE 18.01.2023Veröffentlicht in 2023 Third International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP) (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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Robot Control Optimization Using Reinforcement Learning
ISSN: 0921-0296, 1573-0409Veröffentlicht: Dordrecht Kluwer 01.03.1998Veröffentlicht 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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Deep Reinforcement Learning for Robot Batching Optimization and Flow Control
ISSN: 2351-9789, 2351-9789Veröffentlicht: Elsevier B.V 2020Veröffentlicht 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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Optimal control of a two‐wheeled self‐balancing robot by reinforcement learning
ISSN: 1049-8923, 1099-1239Veröffentlicht: Bognor Regis Wiley Subscription Services, Inc 01.04.2021Veröffentlicht in International journal of robust and nonlinear control (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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Neural Networks Enhanced Optimal Admittance Control of Robot-Environment Interaction Using Reinforcement Learning
ISSN: 2162-237X, 2162-2388, 2162-2388Veröffentlicht: United States IEEE 01.09.2022Veröffentlicht in IEEE transaction on neural networks and learning systems (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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Optimal balancing control of bipedal robots using reinforcement learning
Veröffentlicht: IEEE 01.06.2016Veröffentlicht in 2016 12th World Congress on Intelligent Control and Automation (WCICA) (01.06.2016)“… The balance control a bipedal robot in the presence of external disturbances is still a challenge …”
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Agile Legged Robots Through Reinforcement Learning and Optimal Control
ISBN: 9798384094050Veröffentlicht: 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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Online parameter adaptive control of mobile robots based on deep reinforcement learning under multiple optimisation objectives
ISSN: 2517-7567, 1873-9601, 2517-7567, 1873-961XVeröffentlicht: Dordrecht John Wiley & Sons, Inc 01.12.2024Veröffentlicht 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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An Admittance Parameter Optimization Method Based on Reinforcement Learning for Robot Force Control
ISSN: 2076-0825, 2076-0825Veröffentlicht: Basel MDPI AG 01.09.2024Veröffentlicht 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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Self-optimization composite dynamic control for trajectory tracking of robot manipulators via deep reinforcement learning
ISSN: 2330-7706, 2330-7714Veröffentlicht: 10.07.2025Veröffentlicht in Journal of control and decision (10.07.2025)Volltext
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Optimization Control of Attitude Stability for Hexapod Robots Based on Reinforcement Learning
ISSN: 2169-3536, 2169-3536Veröffentlicht: Piscataway IEEE 2024Veröffentlicht 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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Decentralized Reinforcement Learning Robust Optimal Tracking Control for Time Varying Constrained Reconfigurable Modular Robot Based on ACI and Q-Function
ISSN: 1024-123X, 1563-5147Veröffentlicht: Cairo, Egypt Hindawi Publishing Corporation 01.01.2013Veröffentlicht 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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Reinforcement Learning Control of an Aerial Robot Based on a Tuned Proximal Policy Optimization in Takeoff and Hover Phases
ISSN: 2572-6889Veröffentlicht: IEEE 15.11.2022Veröffentlicht in Digest book (International Conference on Robotics and Mechatronics. Online) (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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Value Iteration-Based Adaptive Fuzzy Backstepping Optimal Control of Modular Robot Manipulators via Integral Reinforcement Learning
ISSN: 1562-2479, 2199-3211Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2024Veröffentlicht 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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Adaptive Prescribed-Time Optimal Control for Flexible-Joint Robots via Reinforcement Learning
ISSN: 2168-2216, 2168-2232Veröffentlicht: IEEE 01.04.2025Veröffentlicht in IEEE transactions on systems, man, and cybernetics. Systems (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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Student-t policy in reinforcement learning to acquire global optimum of robot control
ISSN: 0924-669X, 1573-7497Veröffentlicht: New York Springer US 01.12.2019Veröffentlicht 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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Adaptive Optimal Control of Four-Wheel Omni Robot using Reinforcement Learning
ISSN: 2325-0925Veröffentlicht: IEEE 26.08.2021Veröffentlicht in International Conference on System Science and Engineering (Online) (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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Inferring Human-Robot Performance Objectives During Locomotion Using Inverse Reinforcement Learning and Inverse Optimal Control
ISSN: 2377-3766, 2377-3766Veröffentlicht: Piscataway IEEE 01.04.2022Veröffentlicht 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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Fault Estimate and Reinforcement Learning Based Optimal Output Feedback Control for Single-Link Robot Arm Model
ISSN: 1816-093X, 1816-0948Veröffentlicht: Hong Kong International Association of Engineers 01.01.2025Veröffentlicht 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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