Image de couverture de livre

Adaptive Gain Scheduling using Reinforcement Learning for Quadcopter Control

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Timmerman, Mike, Patel, Aryan, Reinhart, Tim
Format:	Preprint
Publié:	2024
Sujets:	Systems and Control Machine Learning Robotics
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Fault Tolerant Control of a Quadcopter using Reinforcement Learning
par: Habib, Muzaffar, et autres
Publié: (2025)

From Flies to Robots: Inverted Landing in Small Quadcopters with Dynamic Perching
par: Habas, Bryan, et autres
Publié: (2024)

Safe Control using Learned Safety Filters and Adaptive Conformal Inference
par: Huriot, Sacha, et autres
Publié: (2026)

Constraint-Aware Reinforcement Learning via Adaptive Action Scaling
par: Dawood, Murad, et autres
Publié: (2025)

Deep Reinforcement Learning-based Quadcopter Controller: A Practical Approach and Experiments
par: Do, Truong-Dong, et autres
Publié: (2024)

Adaptive Torque Control of Exoskeletons under Spasticity Conditions via Reinforcement Learning
par: Chavarrías, Andrés, et autres
Publié: (2025)

Optimization of the Model Predictive Control Meta-Parameters Through Reinforcement Learning
par: Bøhn, Eivind, et autres
Publié: (2021)

MPC-Inspired Reinforcement Learning for Verifiable Model-Free Control
par: Lu, Yiwen, et autres
Publié: (2023)

DOA: A Degeneracy Optimization Agent with Adaptive Pose Compensation Capability based on Deep Reinforcement Learning
par: Li, Yanbin, et autres
Publié: (2025)

AD-NODE: Adaptive Dynamics Learning with Neural ODEs for Mobile Robots Control
par: Yu, Shao-Yi, et autres
Publié: (2025)

Risk-Aware Safe Reinforcement Learning for Control of Stochastic Linear Systems
par: Esmaeili, Babak, et autres
Publié: (2025)

Adaptive Model-Predictive Control of a Soft Continuum Robot Using a Physics-Informed Neural Network Based on Cosserat Rod Theory
par: Licher, Johann, et autres
Publié: (2025)

Priority-Driven Control and Communication in Decentralized Multi-Agent Systems via Reinforcement Learning
par: Guo, Qingyun, et autres
Publié: (2026)

ReinVBC: A Model-based Reinforcement Learning Approach to Vehicle Braking Controller
par: Lin, Haoxin, et autres
Publié: (2026)

Autonomous Vehicle Lateral Control Using Deep Reinforcement Learning with MPC-PID Demonstration
par: Wu, Chengdong, et autres
Publié: (2025)

Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions
par: Long, Kehan, et autres
Publié: (2025)

Real-time Control of Electric Autonomous Mobility-on-Demand Systems via Graph Reinforcement Learning
par: Singhal, Aaryan, et autres
Publié: (2023)

Learning to Tune Pure Pursuit in Autonomous Racing: Joint Lookahead and Steering-Gain Control with PPO
par: Elgouhary, Mohamed, et autres
Publié: (2026)

APECS: Adaptive Personalized Control System Architecture
par: Juston, Marius F. R., et autres
Publié: (2025)

Robust Recovery Controller for a Quadrupedal Robot using Deep Reinforcement Learning
par: Lee, Joonho, et autres
Publié: (2019)

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning
par: Theile, Mirco, et autres
Publié: (2025)

DiAReL: Reinforcement Learning with Disturbance Awareness for Robust Sim2Real Policy Transfer in Robot Control
par: Malmir, Mohammadhossein, et autres
Publié: (2023)

Hovering Flight of Soft-Actuated Insect-Scale Micro Aerial Vehicles using Deep Reinforcement Learning
par: Hsiao, Yi-Hsuan, et autres
Publié: (2025)

Flying Quadrotors in Tight Formations using Learning-based Model Predictive Control
par: Chee, Kong Yao, et autres
Publié: (2024)

Safe Reinforcement Learning with Minimal Supervision
par: Quessy, Alexander, et autres
Publié: (2025)

Model-Free versus Model-Based Reinforcement Learning for Fixed-Wing UAV Attitude Control Under Varying Wind Conditions
par: Olivares, David, et autres
Publié: (2024)

Toward 6-DOF Autonomous Underwater Vehicle Energy-Aware Position Control based on Deep Reinforcement Learning: Preliminary Results
par: Boré, Gustavo, et autres
Publié: (2025)

Learning Coverage Paths in Unknown Environments with Deep Reinforcement Learning
par: Jonnarth, Arvi, et autres
Publié: (2023)

Active Alignments of Lens Systems with Reinforcement Learning
par: Burkhardt, Matthias, et autres
Publié: (2025)

Off Policy Lyapunov Stability in Reinforcement Learning
par: Gill, Sarvan, et autres
Publié: (2025)

Hamilton-Jacobi Reachability in Reinforcement Learning: A Survey
par: Ganai, Milan, et autres
Publié: (2024)

Provably Optimal Reinforcement Learning under Safety Filtering
par: Oh, Donggeon David, et autres
Publié: (2025)

Realistic Counterfactual Explanations for Machine Learning-Controlled Mobile Robots using 2D LiDAR
par: Remman, Sindre Benjamin, et autres
Publié: (2025)

Learning Control Barrier Functions and their application in Reinforcement Learning: A Survey
par: Guerrier, Maeva, et autres
Publié: (2024)

Goal Reaching with Eikonal-Constrained Hierarchical Quasimetric Reinforcement Learning
par: Giammarino, Vittorio, et autres
Publié: (2025)

Domain Adaptive Safety Filters via Deep Operator Learning
par: Manda, Lakshmideepakreddy, et autres
Publié: (2024)

Deep Reinforcement Learning with Enhanced PPO for Safe Mobile Robot Navigation
par: Taheri, Hamid, et autres
Publié: (2024)

Training Verifiably Robust Agents Using Set-Based Reinforcement Learning
par: Wendl, Manuel, et autres
Publié: (2024)

LAPP: Large Language Model Feedback for Preference-Driven Reinforcement Learning
par: Jian, Pingcheng, et autres
Publié: (2025)

End-to-End Reinforcement Learning for Torque Based Variable Height Hopping
par: Soni, Raghav, et autres
Publié: (2023)