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UAV Autonomous Navigation Based on Deep Reinforcement Learning in Highly Dynamic and High-Density Environments

https://doi.org/10.3390/drones8090516
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s10846-023-01819-0openalex-snapshot
DRL-based Path Planner and its Application in Real Quadrotor with LIDAR
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UAV 3D online track planning based on improved SAC algorithm
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Autonomous navigation of UAV in multi-obstacle environments based on a Deep Reinforcement Learning approach
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Model-guided Reinforcement Learning Enclosing for UAVs with Collision-free and Reinforced Tracking Capability
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Use of a drone-based sensor as a field-ready technique for short-term concentration mapping of air pollutants: A modeling study
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UAV based long range environment monitoring system with Industry 5.0 perspectives for smart city infrastructure
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UAV navigation in high dynamic environments: A deep reinforcement learning approach
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Machine learning approach for truck-drones based last-mile delivery in the era of industry 4.0
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AI-based UAV navigation framework with digital twin technology for mobile target visitation
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Computational approaches for solving two-echelon vehicle and UAV routing problems for post-disaster humanitarian operations
inferredcites →https://doi.org/10.1016/j.neucom.2024.128423openalex-snapshot
Recent progress, challenges and future prospects of applied deep reinforcement learning : A practical perspective in path planning
inferredcites →https://doi.org/10.1088/1361-6501/ad2663openalex-snapshot
Improve exploration in deep reinforcement learning for UAV path planning using state and action entropy
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A framework for improving UAV decision of autonomous navigation from training to application migration under perceptual uncertainty
inferredcites →https://doi.org/10.1109/access.2024.3375083openalex-snapshot
UAV Path Planning Based on the Average TD3 Algorithm With Prioritized Experience Replay
inferredcites →https://doi.org/10.1109/jiot.2020.2973193openalex-snapshot
Deep-Reinforcement-Learning-Based Autonomous UAV Navigation With Sparse Rewards
inferredcites →https://doi.org/10.1109/jiot.2023.3327753openalex-snapshot
A State-Decomposition DDPG Algorithm for UAV Autonomous Navigation in 3-D Complex Environments
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State-of-the-Art and Future Research Challenges in UAV Swarms
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On the Optimal Mounting Angle for a Spinning LiDAR on a UAV
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A Review of Small UAV Navigation System Based on Multisource Sensor Fusion
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Path Planning for Unmanned Aerial Vehicle via Off-Policy Reinforcement Learning With Enhanced Exploration
inferredcites →https://doi.org/10.1109/tg.2018.2849942openalex-snapshot
Learning to Navigate Through Complex Dynamic Environment With Modular Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/tim.2023.3265741openalex-snapshot
Deep Reinforcement Learning of UAV Tracking Control Under Wind Disturbances Environments
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A Hierarchical Reinforcement Learning Algorithm Based on Attention Mechanism for UAV Autonomous Navigation
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inferredcites →https://doi.org/10.1109/tvt.2022.3218855openalex-snapshot
A UAV Navigation Approach Based on Deep Reinforcement Learning in Large Cluttered 3D Environments
inferredcites →https://doi.org/10.1155/2023/6654130openalex-snapshot
Representation Enhancement-Based Proximal Policy Optimization for UAV Path Planning and Obstacle Avoidance
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Multi-Drone Optimal Mission Assignment and 3D Path Planning for Disaster Rescue
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VizNav: A Modular Off-Policy Deep Reinforcement Learning Framework for Vision-Based Autonomous UAV Navigation in 3D Dynamic Environments
inferredcites →https://doi.org/10.3390/drones8050205openalex-snapshot
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inferredcites →https://doi.org/10.3390/drones8070320openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.1801.01290openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.1802.09477openalex-snapshot
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-031-91992-3_36openalex-snapshot
Visual Positioning of the UAV in Conditions of Impossibility of Using External Navigation Signals
inferred← citeshttps://doi.org/10.1007/978-3-031-96199-1_5openalex-snapshot
Autonomous Navigation in Swarm of UAVs Using Spatio Temporal Data and Constrained-Reinforcement Learning
inferred← citeshttps://doi.org/10.1007/s44443-026-01132-4openalex-snapshot
Three-dimensional path planning algorithm for UAV based on CL-PER-ID3QN
inferred← citeshttps://doi.org/10.1016/j.aei.2026.104596openalex-snapshot
Robust UAV navigation under perception uncertainty: a spatiotemporal transformer-enhanced reinforcement learning approach
inferred← citeshttps://doi.org/10.1016/j.jnlest.2025.100303openalex-snapshot
Multi-UAV path planning for multiple emergency payloads delivery in natural disaster scenarios
inferred← citeshttps://doi.org/10.1016/j.measurement.2026.121377openalex-snapshot
DDPG-enhanced ICP–PSO–ACO hybrid optimization for adaptive geomagnetic measurement and UAV navigation
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2025.123655openalex-snapshot
Gaussian enhanced deep reinforcement learning for USV navigation with scarce environmental priors
inferred← citeshttps://doi.org/10.1038/s41598-026-59923-8openalex-snapshot
Physics-constrained multimodal reinforcement learning for local UAV Navigation in complex static obstacle environments
inferred← citeshttps://doi.org/10.1049/aie2.70025openalex-snapshot
Waypoint Navigation of a 2D Drone in Stochastic Environment via Regularised Proximal Policy Optimisation
inferred← citeshttps://doi.org/10.1088/1361-6501/adb873openalex-snapshot
Study on the influence of airborne LiDAR measurement data representation method on DRL-based UAV navigation performance
inferred← citeshttps://doi.org/10.1109/access.2026.3719655openalex-snapshot
Intelligent Agent-Based Hierarchical Task Planning and Robust Control for Autonomous Multi-UAV Transmission Line Inspection
inferred← citeshttps://doi.org/10.1109/ci2a69097.2026.11577091openalex-snapshot
A Survey of Reinforcement Learning Methods for UAV Path Planning: Safety, Scalability and Real-World Challenges
inferred← citeshttps://doi.org/10.1109/cis-ram71614.2026.11668501openalex-snapshot
Teacher-Guided Asymmetric Reinforcement Learning for End-to-End Visual Navigation of UAVs
inferred← citeshttps://doi.org/10.1109/decon67170.2025.11447652openalex-snapshot
Hierarchical Mapping-Partitioning-Search with Attention-Weighted Communication for UAV Swarms in Search and Rescue Operations
inferred← citeshttps://doi.org/10.1109/ica65945.2025.11253808openalex-snapshot
Autonomous Unmanned Aerial Vehicle (UAV) Navigation Using Soft Actor-Critic (SAC) Algorithm with a Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/iccr67387.2025.11292251openalex-snapshot
An Adaptive Drone Navigation in Dynamic Terrains Using Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/icmlas67792.2026.11483799openalex-snapshot
Performance Evaluation of AI-Enabled Autonomous Drone Navigation Systems Using Computer Vision
inferred← citeshttps://doi.org/10.1109/icuas69441.2026.11598642openalex-snapshot
Conservative Cost-Aware SAC-Lagrangian for Safe UAV Autonomous Navigation
inferred← citeshttps://doi.org/10.1109/isaes66870.2025.11274379openalex-snapshot
Research on Positioning and Path Planning Technologies for UAVs in Low-Altitude Airspace
inferred← citeshttps://doi.org/10.1109/jiot.2026.3686066openalex-snapshot
Dynamic Target Assignment and Cooperative Decision-Making for UAV Swarms Based on Multiagent Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/lars69345.2025.11273007openalex-snapshot
Autonomous UAV Flight Navigation in Confined Spaces: A Reinforcement Learning Approach
inferred← citeshttps://doi.org/10.1109/wcnc65185.2026.11555351openalex-snapshot
Attention and Curiosity Based Reinforcement Learning Approach for Drone Collision Avoidance
inferred← citeshttps://doi.org/10.1145/3712335.3712381openalex-snapshot
Knowledge Graph of Unmanned Aerial Vehicle Reconnaissance Research
inferred← citeshttps://doi.org/10.1177/1088467x251408949openalex-snapshot
UAV autonomous navigation with hybrid maneuver modes: A hierarchical reinforcement learning method
inferred← citeshttps://doi.org/10.2139/ssrn.6331704openalex-snapshot
HyTraL: A Hybrid Transformer–LSTM Framework for Intelligent and Safe UAV Path Planning in Dynamic Environments
inferred← citeshttps://doi.org/10.26565/2304-6201-2025-68-05openalex-snapshot
Analysis of Modern Neural Network Methods for Visual Information Processing in High-Speed UAV Navigation Systems
inferred← citeshttps://doi.org/10.30572/2018/kje/170327openalex-snapshot
MEMORY-AUGMENTED REINFORCEMENT LEARNING FOR UAV NAVIGATION USING PPO-LSTM
inferred← citeshttps://doi.org/10.3390/act14090461openalex-snapshot
Research on Aerodynamic Force/Thrust Vector Combined Trajectory Optimization Method for Hypersonic Drones Based on Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.3390/app16147159openalex-snapshot
Enhanced Soft Actor–Critic with Dual-Path Channel Attention for UAV Autonomous Navigation in Complex Environments
inferred← citeshttps://doi.org/10.3390/biomimetics10080493openalex-snapshot
Research on Robot Obstacle Avoidance and Generalization Methods Based on Fusion Policy Transfer Learning
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Hierarchical Route Planning Framework and MMDQN Agent-Based Intelligent Obstacle Avoidance for UAVs
inferred← citeshttps://doi.org/10.3390/drones10080622openalex-snapshot
Egocentric Constraint Corridor: Deep Reinforcement Learning for Fixed-Wing UAV Navigation in Vertically Constrained Airspace
inferred← citeshttps://doi.org/10.3390/drones10090660openalex-snapshot
Shaping Gradient and Exploration-Noise Initialization, Not Reward Polarity, Determine Convergence in Deep Reinforcement Learning for Autonomous Quadrotor Navigation and Obstacle Avoidance
inferred← citeshttps://doi.org/10.3390/drones9070484openalex-snapshot
A Survey on UAV Control with Multi-Agent Reinforcement Learning
inferred← citeshttps://doi.org/10.3390/electronics14071330openalex-snapshot
Deep Reinforcement Learning for UAV Target Search and Continuous Tracking in Complex Environments with Gaussian Process Regression and Prior Policy Embedding
inferred← citeshttps://doi.org/10.3390/machines14020177openalex-snapshot
Reinforcement Learning for UAV Control: From Algorithms to Deployment Readiness
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A New Hybrid Reinforcement Learning with Artificial Potential Field Method for UAV Target Search
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Simulation-Driven Approach to Evaluate a Reinforcement Learning-Based Navigation System for Last-Mile Drone Logistics
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