On the public citation graph

A New Autonomous Method of Drone Path Planning Based on Multiple Strategies for Avoiding Obstacles with High Speed and High Density

https://doi.org/10.3390/drones8050205
0 signed · 49 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

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

inferredcites →https://doi.org/10.1007/s10846-019-01073-3openalex-snapshot
Towards Real-Time Path Planning through Deep Reinforcement Learning for a UAV in Dynamic Environments
inferredcites →https://doi.org/10.1007/s12555-020-0979-3openalex-snapshot
Global and Local Moth-flame Optimization Algorithm for UAV Formation Path Planning Under Multi-constraints
inferredcites →https://doi.org/10.1007/s40430-023-04570-7openalex-snapshot
UAV 3D online track planning based on improved SAC algorithm
inferredcites →https://doi.org/10.1016/j.asoc.2021.107376openalex-snapshot
Safety-enhanced UAV path planning with spherical vector-based particle swarm optimization
inferredcites →https://doi.org/10.1016/j.cie.2021.107230openalex-snapshot
Path planning optimization of indoor mobile robot based on adaptive ant colony algorithm
inferredcites →https://doi.org/10.1016/j.dt.2022.01.006openalex-snapshot
Improved lazy theta∗ algorithm based on octree map for path planning of UAV
inferredcites →https://doi.org/10.1016/j.eswa.2024.123481openalex-snapshot
A novel state transition algorithm with adaptive fuzzy penalty for multi-constraint UAV path planning
inferredcites →https://doi.org/10.1016/j.isatra.2020.11.017openalex-snapshot
On obstacle avoidance path planning in unknown 3D environments: A fluid-based framework
inferredcites →https://doi.org/10.1016/j.neucom.2020.03.063openalex-snapshot
Adaptive neuro-fuzzy PID controller based on twin delayed deep deterministic policy gradient algorithm
inferredcites →https://doi.org/10.1016/j.neucom.2023.03.054openalex-snapshot
Action decoupled SAC reinforcement learning with discrete-continuous hybrid action spaces
inferredcites →https://doi.org/10.1016/j.oceaneng.2019.106299openalex-snapshot
A knowledge-free path planning approach for smart ships based on reinforcement learning
inferredcites →https://doi.org/10.1016/j.oceaneng.2020.107043openalex-snapshot
The review unmanned surface vehicle path planning: Based on multi-modality constraint
inferredcites →https://doi.org/10.1016/j.oceaneng.2023.113632openalex-snapshot
A path planning approach for unmanned surface vehicles based on dynamic and fast Q-learning
inferredcites →https://doi.org/10.1016/j.simpat.2023.102815openalex-snapshot
An obstacle avoidance approach for UAV path planning
inferredcites →https://doi.org/10.1017/s0373463318001005openalex-snapshot
Voronoi-Visibility Roadmap-based Path Planning Algorithm for Unmanned Surface Vehicles
inferredcites →https://doi.org/10.1088/1361-6501/ad1977openalex-snapshot
A novel unmanned aerial vehicle path planning approach: sand cat optimization algorithm incorporating learned behaviour
inferredcites →https://doi.org/10.1109/access.2020.2990153openalex-snapshot
Bi-Directional Adaptive A* Algorithm Toward Optimal Path Planning for Large-Scale UAV Under Multi-Constraints
inferredcites →https://doi.org/10.1109/access.2023.3303109openalex-snapshot
Collision-Free Trajectory Following With Augmented Artificial Potential Field Using UAVs
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/icras.2019.8809005openalex-snapshot
A Path Planning Approach Based on Q-learning for Robot Arm
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.2022.3166110openalex-snapshot
D3PG: Dirichlet DDPG for Task Partitioning and Offloading With Constrained Hybrid Action Space in Mobile-Edge Computing
inferredcites →https://doi.org/10.1109/jsyst.2019.2917786openalex-snapshot
Formation Obstacle Avoidance: A Fluid-Based Solution
inferredcites →https://doi.org/10.1109/lra.2022.3146918openalex-snapshot
Multi-Objective Path-Based D* Lite
inferredcites →https://doi.org/10.1109/lra.2022.3191855openalex-snapshot
Trajectory Planning for UAVs Based on Interfered Fluid Dynamical System and Bézier Curves
inferredcites →https://doi.org/10.2316/j.2019.206-0216openalex-snapshot
SOFT ACTOR-CRITIC REINFORCEMENT LEARNING FOR ROBOTIC MANIPULATOR WITH HINDSIGHT EXPERIENCE REPLAY
inferredcites →https://doi.org/10.23919/usnc/ursi49741.2020.9321625openalex-snapshot
A UAV Path Planning Method Based on Deep Reinforcement Learning
inferredcites →https://doi.org/10.3390/act11020052openalex-snapshot
Autonomous Vehicle Path Planning Based on Driver Characteristics Identification and Improved Artificial Potential Field
inferredcites →https://doi.org/10.3390/aerospace10060562openalex-snapshot
UAV Path Planning Based on Improved Artificial Potential Field Method
inferredcites →https://doi.org/10.3390/drones7050323openalex-snapshot
A Disaster Relief UAV Path Planning Based on APF-IRRT* Fusion Algorithm
inferredcites →https://doi.org/10.3390/drones8020060openalex-snapshot
Dynamic Scene Path Planning of UAVs Based on Deep Reinforcement Learning
inferredcites →https://doi.org/10.3390/electronics12224576openalex-snapshot
Unmanned Aerial Vehicle Path-Planning Method Based on Improved P-RRT* Algorithm
inferredcites →https://doi.org/10.3390/electronics9020250openalex-snapshot
Trajectory Planning Algorithm of UAV Based on System Positioning Accuracy Constraints
inferredcites →https://doi.org/10.35833/mpce.2021.000394openalex-snapshot
Mixed Deep Reinforcement Learning Considering Discrete-continuous Hybrid Action Space for Smart Home Energy Management
inferredcites →https://doi.org/10.3934/mbe.2022371openalex-snapshot
An autonomous agent for negotiation with multiple communication channels using parametrized deep Q-network

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-3-031-92314-2_6openalex-snapshot
Reinforcement Learning for Drone Path Planning: A Bibliometric Analysis
inferred← citeshttps://doi.org/10.1007/s10846-026-02442-5openalex-snapshot
Rerouting UAVs in a Dynamic Environment Based on an Optimized Interfered Fluid Dynamical System
inferred← citeshttps://doi.org/10.1007/s42496-026-00314-7openalex-snapshot
Optimizing Unmanned Aerial Vehicle Path finding in Complex Urban Airspaces: A Hybrid Genetic Algorithm with Bidirectional and Greedy Initialization
inferred← citeshttps://doi.org/10.1109/access.2025.3547885openalex-snapshot
Variable Action Set-Based Monte Carlo Tree Search Algorithm for AAV Autonomous Collision Avoidance
inferred← citeshttps://doi.org/10.1109/incet64471.2025.11140157openalex-snapshot
Approximation of an Autonomous Navigation System in UAVs Based on Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/isitia71267.2026.11642298openalex-snapshot
Integrated AVO IFDS Methods for Quadcopter Path Planning and Obstacle Avoidance Under Wind Disturbances
inferred← citeshttps://doi.org/10.1109/tts.2025.3615244openalex-snapshot
Trust and Privacy in Commercial and Recreational Drone Navigation
inferred← citeshttps://doi.org/10.1142/s2301385025500669openalex-snapshot
Advancements in UAV Path Planning: A Deep Reinforcement Learning Approach with Soft Actor-Critic for Enhanced Navigation
inferred← citeshttps://doi.org/10.2478/amns-2024-3279openalex-snapshot
Research on automatic UAV path planning technology for complex terrain under neural network perspective
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/aerospace11100788openalex-snapshot
Design and Experimental Validation of an Adaptive Multi-Layer Neural Network Observer-Based Fast Terminal Sliding Mode Control for Quadrotor System
inferred← citeshttps://doi.org/10.3390/drones8080367openalex-snapshot
ERRT-GA: Expert Genetic Algorithm with Rapidly Exploring Random Tree Initialization for Multi-UAV Path Planning
inferred← citeshttps://doi.org/10.3390/drones8090516openalex-snapshot
UAV Autonomous Navigation Based on Deep Reinforcement Learning in Highly Dynamic and High-Density Environments
inferred← citeshttps://doi.org/10.62762/cjif.2024.596648openalex-snapshot
A High-Efficiency Two-Layer Path Planning Method for UAVs in Vast Airspace
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.