Guardado en:
| Autores principales: | Lin, Haoxin, Zhou, Junjie, Xu, Daheng, Yu, Yang |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2604.04401 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Autonomous Vehicle Lateral Control Using Deep Reinforcement Learning with MPC-PID Demonstration
por: Wu, Chengdong, et al.
Publicado: (2025)
por: Wu, Chengdong, et al.
Publicado: (2025)
Toward 6-DOF Autonomous Underwater Vehicle Energy-Aware Position Control based on Deep Reinforcement Learning: Preliminary Results
por: Boré, Gustavo, et al.
Publicado: (2025)
por: Boré, Gustavo, et al.
Publicado: (2025)
MPC-Inspired Reinforcement Learning for Verifiable Model-Free Control
por: Lu, Yiwen, et al.
Publicado: (2023)
por: Lu, Yiwen, et al.
Publicado: (2023)
A Safe Reinforcement Learning driven Weights-varying Model Predictive Control for Autonomous Vehicle Motion Control
por: Zarrouki, Baha, et al.
Publicado: (2024)
por: Zarrouki, Baha, et al.
Publicado: (2024)
Hovering Flight of Soft-Actuated Insect-Scale Micro Aerial Vehicles using Deep Reinforcement Learning
por: Hsiao, Yi-Hsuan, et al.
Publicado: (2025)
por: Hsiao, Yi-Hsuan, et al.
Publicado: (2025)
Heterogeneous Multi-Agent Reinforcement Learning for Zero-Shot Scalable Collaboration
por: Guo, Xudong, et al.
Publicado: (2024)
por: Guo, Xudong, et al.
Publicado: (2024)
Enhancing Safety in Mixed Traffic: Learning-Based Modeling and Efficient Control of Autonomous and Human-Driven Vehicles
por: Wang, Jie, et al.
Publicado: (2024)
por: Wang, Jie, et al.
Publicado: (2024)
Optimization of the Model Predictive Control Meta-Parameters Through Reinforcement Learning
por: Bøhn, Eivind, et al.
Publicado: (2021)
por: Bøhn, Eivind, et al.
Publicado: (2021)
Adaptive Gain Scheduling using Reinforcement Learning for Quadcopter Control
por: Timmerman, Mike, et al.
Publicado: (2024)
por: Timmerman, Mike, et al.
Publicado: (2024)
A Tutorial on Gaussian Process Learning-based Model Predictive Control
por: Wang, Jie, et al.
Publicado: (2024)
por: Wang, Jie, et al.
Publicado: (2024)
Risk-Aware Safe Reinforcement Learning for Control of Stochastic Linear Systems
por: Esmaeili, Babak, et al.
Publicado: (2025)
por: Esmaeili, Babak, et al.
Publicado: (2025)
An Iterative LQR Controller for Off-Road and On-Road Vehicles using a Neural Network Dynamics Model
por: Nagariya, Akhil, et al.
Publicado: (2020)
por: Nagariya, Akhil, et al.
Publicado: (2020)
Model-Free versus Model-Based Reinforcement Learning for Fixed-Wing UAV Attitude Control Under Varying Wind Conditions
por: Olivares, David, et al.
Publicado: (2024)
por: Olivares, David, et al.
Publicado: (2024)
Flying Quadrotors in Tight Formations using Learning-based Model Predictive Control
por: Chee, Kong Yao, et al.
Publicado: (2024)
por: Chee, Kong Yao, et al.
Publicado: (2024)
Learning Local Control Barrier Functions for Hybrid Systems
por: Yang, Shuo, et al.
Publicado: (2024)
por: Yang, Shuo, et al.
Publicado: (2024)
Online Control-Informed Learning
por: Liang, Zihao, et al.
Publicado: (2024)
por: Liang, Zihao, et al.
Publicado: (2024)
DOA: A Degeneracy Optimization Agent with Adaptive Pose Compensation Capability based on Deep Reinforcement Learning
por: Li, Yanbin, et al.
Publicado: (2025)
por: Li, Yanbin, et al.
Publicado: (2025)
A Model-Based Approach to Imitation Learning through Multi-Step Predictions
por: Balim, Haldun, et al.
Publicado: (2025)
por: Balim, Haldun, et al.
Publicado: (2025)
Priority-Driven Control and Communication in Decentralized Multi-Agent Systems via Reinforcement Learning
por: Guo, Qingyun, et al.
Publicado: (2026)
por: Guo, Qingyun, et al.
Publicado: (2026)
Real-time Control of Electric Autonomous Mobility-on-Demand Systems via Graph Reinforcement Learning
por: Singhal, Aaryan, et al.
Publicado: (2023)
por: Singhal, Aaryan, et al.
Publicado: (2023)
Multi-Step Deep Koopman Network (MDK-Net) for Vehicle Control in Frenet Frame
por: Abtahi, Mohammad, et al.
Publicado: (2025)
por: Abtahi, Mohammad, et al.
Publicado: (2025)
Learning Efficient Flocking Control based on Gibbs Random Fields
por: Zhang, Dengyu, et al.
Publicado: (2025)
por: Zhang, Dengyu, et al.
Publicado: (2025)
LAPP: Large Language Model Feedback for Preference-Driven Reinforcement Learning
por: Jian, Pingcheng, et al.
Publicado: (2025)
por: Jian, Pingcheng, et al.
Publicado: (2025)
Online Intention Prediction via Control-Informed Learning
por: Zhou, Tianyu, et al.
Publicado: (2026)
por: Zhou, Tianyu, et al.
Publicado: (2026)
DiAReL: Reinforcement Learning with Disturbance Awareness for Robust Sim2Real Policy Transfer in Robot Control
por: Malmir, Mohammadhossein, et al.
Publicado: (2023)
por: Malmir, Mohammadhossein, et al.
Publicado: (2023)
CBF-RL: Safety Filtering Reinforcement Learning in Training with Control Barrier Functions
por: Yang, Lizhi, et al.
Publicado: (2025)
por: Yang, Lizhi, et al.
Publicado: (2025)
AcL: Action Learner for Fault-Tolerant Quadruped Locomotion Control
por: Xu, Tianyu, et al.
Publicado: (2025)
por: Xu, Tianyu, et al.
Publicado: (2025)
Real Time Control of Tandem-Wing Experimental Platform Using Concerto Reinforcement Learning
por: Minghao, Zhang, et al.
Publicado: (2025)
por: Minghao, Zhang, et al.
Publicado: (2025)
Safe Reinforcement Learning with Minimal Supervision
por: Quessy, Alexander, et al.
Publicado: (2025)
por: Quessy, Alexander, et al.
Publicado: (2025)
Deep Reinforcement Learning for Advanced Longitudinal Control and Collision Avoidance in High-Risk Driving Scenarios
por: Chen, Dianwei, et al.
Publicado: (2024)
por: Chen, Dianwei, et al.
Publicado: (2024)
Robust Model Predictive Control Design for Autonomous Vehicles with Perception-based Observers
por: Niknejad, Nariman, et al.
Publicado: (2025)
por: Niknejad, Nariman, et al.
Publicado: (2025)
Learning Coverage Paths in Unknown Environments with Deep Reinforcement Learning
por: Jonnarth, Arvi, et al.
Publicado: (2023)
por: Jonnarth, Arvi, et al.
Publicado: (2023)
A Fast Initialization Method for Neural Network Controllers: A Case Study of Image-based Visual Servoing Control for the multicopter Interception
por: Ke, Chenxu, et al.
Publicado: (2025)
por: Ke, Chenxu, et al.
Publicado: (2025)
Learning Control Barrier Functions and their application in Reinforcement Learning: A Survey
por: Guerrier, Maeva, et al.
Publicado: (2024)
por: Guerrier, Maeva, et al.
Publicado: (2024)
Active Alignments of Lens Systems with Reinforcement Learning
por: Burkhardt, Matthias, et al.
Publicado: (2025)
por: Burkhardt, Matthias, et al.
Publicado: (2025)
Off Policy Lyapunov Stability in Reinforcement Learning
por: Gill, Sarvan, et al.
Publicado: (2025)
por: Gill, Sarvan, et al.
Publicado: (2025)
Contraction Theory for Nonlinear Stability Analysis and Learning-based Control: A Tutorial Overview
por: Tsukamoto, Hiroyasu, et al.
Publicado: (2021)
por: Tsukamoto, Hiroyasu, et al.
Publicado: (2021)
SigmaRL: A Sample-Efficient and Generalizable Multi-Agent Reinforcement Learning Framework for Motion Planning
por: Xu, Jianye, et al.
Publicado: (2024)
por: Xu, Jianye, et al.
Publicado: (2024)
Kernel-Based Optimal Control: An Infinitesimal Generator Approach
por: Bevanda, Petar, et al.
Publicado: (2024)
por: Bevanda, Petar, et al.
Publicado: (2024)
Learning a Stable, Safe, Distributed Feedback Controller for a Heterogeneous Platoon of Autonomous Vehicles
por: Shaham, Michael H., et al.
Publicado: (2024)
por: Shaham, Michael H., et al.
Publicado: (2024)
Ejemplares similares
-
Autonomous Vehicle Lateral Control Using Deep Reinforcement Learning with MPC-PID Demonstration
por: Wu, Chengdong, et al.
Publicado: (2025) -
Toward 6-DOF Autonomous Underwater Vehicle Energy-Aware Position Control based on Deep Reinforcement Learning: Preliminary Results
por: Boré, Gustavo, et al.
Publicado: (2025) -
MPC-Inspired Reinforcement Learning for Verifiable Model-Free Control
por: Lu, Yiwen, et al.
Publicado: (2023) -
A Safe Reinforcement Learning driven Weights-varying Model Predictive Control for Autonomous Vehicle Motion Control
por: Zarrouki, Baha, et al.
Publicado: (2024) -
Hovering Flight of Soft-Actuated Insect-Scale Micro Aerial Vehicles using Deep Reinforcement Learning
por: Hsiao, Yi-Hsuan, et al.
Publicado: (2025)