On the public citation graph

Path Following of a Water-Jetted USV Based on Maneuverability Tests

0 signed · 41 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1002/9781119575016openalex-snapshot
Handbook of Marine Craft Hydrodynamics and Motion Control
inferredcites →https://doi.org/10.1002/9781119994138openalex-snapshot
Handbook of Marine Craft Hydrodynamics and Motion Control
inferredcites →https://doi.org/10.1007/s11804-010-1033-2openalex-snapshot
Development and missions of unmanned surface vehicle
inferredcites →https://doi.org/10.1016/j.arcontrol.2016.04.018openalex-snapshot
Unmanned surface vehicles: An overview of developments and challenges
inferredcites →https://doi.org/10.1016/j.ifacol.2018.09.458openalex-snapshot
A Two Layered Optimal Approach towards Cooperative Motion Planning of Unmanned Surface Vehicles in a Constrained Maritime Environment
inferredcites →https://doi.org/10.1016/j.oceaneng.2016.09.001openalex-snapshot
Development of the USV ‘JingHai-I’ and sea trials in the Southern Yellow Sea
inferredcites →https://doi.org/10.1109/ccra.2016.7811411openalex-snapshot
Design and control of an unmanned surface vehicle for environmental monitoring applications
inferredcites →https://doi.org/10.1109/oceans.2000.881292openalex-snapshot
Evolution of the autonomous surface craft AutoCat
inferredcites →https://doi.org/10.1109/tcst.2014.2306774openalex-snapshot
Integral LOS Path Following for Curved Paths Based on a Monotone Cubic Hermite Spline Parametrization
inferredcites →https://doi.org/10.1201/9781315099132-70openalex-snapshot
Optimal Path Planning of an Unmanned Surface Vehicle in a Real- Time Marine Environment using a Dijkstra Algorithm
inferredcites →https://doi.org/10.1243/14750902jeme80openalex-snapshot
The design of a navigation, guidance, and control system for an unmanned surface vehicle for environmental monitoring
inferredcites →https://doi.org/10.1515/pomr-2017-0001openalex-snapshot
Path Following Control of the Underactuated USV Based On the Improved Line-of-Sight Guidance Algorithm
inferredcites →https://doi.org/10.19693/j.issn.1673-3185.01605openalex-snapshot
喷水推进和泵喷推进的概念:共性、特性及区别
inferredcites →https://doi.org/10.3182/20120919-3-it-2046.00065openalex-snapshot
Relative Velocity Control and Integral LOS for Path Following of Underactuated Surface Vessels
inferredcites →https://doi.org/10.3390/s19183939openalex-snapshot
Assessment of the Steering Precision of a Hydrographic Unmanned Surface Vessel (USV) along Sounding Profiles Using a Low-Cost Multi-Global Navigation Satellite System (GNSS) Receiver Supported Autopilot
inferredcites →https://doi.org/10.3390/s20020439openalex-snapshot
Iterative Learning-Based Path and Speed Profile Optimization for an Unmanned Surface Vehicle
inferredcites →https://doi.org/10.3390/s20030832openalex-snapshot
Accuracy of Trajectory Tracking Based on Nonlinear Guidance Logic for Hydrographic Unmanned Surface Vessels
inferredcites →https://doi.org/10.5875/ausmt.v1i2.122openalex-snapshot
Multifunctional Inshore Survey Platform with Unmanned Surface Vehicles

What points at this work

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

inferred← citeshttps://doi.org/10.2139/ssrn.4673979openalex-extracted
inferred← citeshttps://doi.org/10.1007/978-981-95-9354-5_5openalex-snapshot
Path Following Method for Curved Waterways Based on Electronic Navigational Charts
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2021.109575openalex-snapshot
Free-running tests on a self-propelled submersible multi-state vehicle model
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2024.117185openalex-snapshot
Predictive trajectory tracking control for the USV in networked environments with communication constraints
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2024.117993openalex-snapshot
Distributed prescribed-time cooperative formation tracking control of networked unmanned surface vessels under directed graph
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2024.118282openalex-snapshot
Seakeeping investigations of a cross-domain vehicle with the capability of high-speed cruising in waves
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2025.121338openalex-snapshot
Integrating deep Q-networks, convolutional neural networks, and artificial potential fields for enhanced search path planning of unmanned surface vessels
inferred← citeshttps://doi.org/10.1088/1742-6596/2301/1/012029openalex-snapshot
Research Progress of Test Methods for Unmanned Surface Vehicle in Complex Sea Conditions
inferred← citeshttps://doi.org/10.1109/access.2020.3046130openalex-snapshot
Adaptive Backstepping Sliding Mode Tracking Control for Underactuated Unmanned Surface Vehicle With Disturbances and Input Saturation
inferred← citeshttps://doi.org/10.1109/sceecs64059.2025.10940979openalex-snapshot
Design and Testing of Unmanned Surface Vehicle with Water Sampling Mechanism for measuring Water Quality
inferred← citeshttps://doi.org/10.1109/tiv.2024.3437735openalex-snapshot
Multi-USV Cooperative Formation Control via Deep Reinforcement Learning With Deceleration
inferred← citeshttps://doi.org/10.1177/1045389x221105056openalex-snapshot
Controllability analysis and intelligent control of magnetorheological whole-satellite under small amplitude and medium-high frequency vibration
inferred← citeshttps://doi.org/10.13000/jfmse.2024.2.36.1.21openalex-snapshot
A Study on Ship Path Following System Utilizing a Small Model Boat
inferred← citeshttps://doi.org/10.1371/journal.pone.0290246openalex-snapshot
A trajectory tracking control system for paddle boat in intelligent aquaculture
inferred← citeshttps://doi.org/10.3390/automation3010002openalex-snapshot
Development and Performance Measurement of an Affordable Unmanned Surface Vehicle (USV)
inferred← citeshttps://doi.org/10.3390/en13215637openalex-snapshot
Assessment of the Steering Precision of a Hydrographic USV along Sounding Profiles Using a High-Precision GNSS RTK Receiver Supported Autopilot
inferred← citeshttps://doi.org/10.3390/en15072441openalex-snapshot
Determination of the Minimum Safe Distance between a USV and a Hydro-Engineering Structure in a Restricted Water Region Sounding
inferred← citeshttps://doi.org/10.3390/jmse11010152openalex-snapshot
Experimental Investigation of High Speed Cross-Domain Vehicles with Hydrofoil
inferred← citeshttps://doi.org/10.3390/jmse11010153openalex-snapshot
Trajectory Planning of USV: On-Line Computation of the Double S Trajectory Based on Multi-Scale A* Algorithm with Reeds–Shepp Curves
inferred← citeshttps://doi.org/10.3390/jmse12122188openalex-snapshot
The Path Tracking Control of Unmanned Surface Vehicles Based on an Improved Non-Dominated Sorting Genetic Algorithm II-Based Multi-Objective Nonlinear Model Predictive Control Method
inferred← citeshttps://doi.org/10.3390/jmse12122321openalex-snapshot
Research on Path-Following Technology of a Single-Outboard-Motor Unmanned Surface Vehicle Based on Deep Reinforcement Learning and Model Predictive Control Algorithm
inferred← citeshttps://doi.org/10.3390/jmse9030257openalex-snapshot
Unmanned Marine Vehicles
inferred← citeshttps://doi.org/10.7551/mitpress/9407.003.0006openalex-snapshot
Unmanned Marine Vehicles
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.