eess.SY(2025-05-12)

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支柱一:机器人控制 (Robot Control) (3) 支柱二:RL算法与架构 (RL & Architecture) (1)

🔬 支柱一:机器人控制 (Robot Control) (3 篇)

#题目一句话要点标签🔗
1 Leveraging Reinforcement Learning and Koopman Theory for Enhanced Model Predictive Control Performance 结合Koopman理论与强化学习,提升模型预测控制性能 MPC model predictive control reinforcement learning
2 Integrated Localization and Path Planning for an Ocean Exploring Team of Autonomous Underwater Vehicles with Consensus Graph Model Predictive Control 提出基于共识图模型预测控制的水下机器人协同定位与路径规划方法 MPC model predictive control
3 Finite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics 提出基于有限样本可达集的GP动力学安全控制方法,提升实用性。 MPC model predictive control

🔬 支柱二:RL算法与架构 (RL & Architecture) (1 篇)

#题目一句话要点标签🔗
4 Multi-Objective Reinforcement Learning for Energy-Efficient Industrial Control 提出基于多目标强化学习的工业控制方法,实现节能优化。 reinforcement learning

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