FS-PPS: A Fermat’s Spiral based Path Planning Scheme for Data Collection in UWSNs

Wang, Ziheng; Liu, Chunfeng; Zhao, Zhao; Yu, Tao; Qu, Wenyu

doi:10.1109/cscwd54268.2022.9776081

Cited by 1 publication

(2 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To find the optimal solution, they harnessed the power of ant colony optimization techniques. Furthermore, the communication range has been taken into account by research in [91]. Their contribution includes the proposal of an AUV-assisted data collection approach centered on Fermat's spiral (FS-PPS).…”

Section: Meta-heuristic Methodsmentioning

confidence: 99%

“…Building upon the work in [82], researchers of [48] extended this line of research by incorporating data from AUV deployments and incorporating more advanced acoustic communication models. In addressing scenarios where event-generated data dynamically occur, a scheme known as the on-demand path-planning scheme (OD-PPS) was developed by researchers of [91]. This scheme employs local search techniques to maximize the completeness of collected data.…”

Section: Heuristic and Direct Searchmentioning

confidence: 99%

See 1 more Smart Citation

Unlocking the Ocean 6G: A Review of Path-Planning Techniques for Maritime Data Harvesting Assisted by Autonomous Marine Vehicles

Zhao,

Bai

2024

JMSE

View full text Add to dashboard Cite

Seamless integration of both terrestrial and non-terrestrial networks is crucial to providing full-dimensional wireless and ubiquitous coverage, particularly catering to those engaged in marine activities. Compared to terrestrial networks, wireless communications in the marine domain are still not satisfactory for ubiquitous connectivity. Featuring agile maneuverability and strong adaptive capability, autonomous marine vehicles (AMVs) play a pivotal role in enhancing communication coverage by relaying or collecting data. However, path planning for maritime data harvesting is one of the most critical issues to enhance transmission efficiency while ensuring safe sailing for AMVs; yet it has rarely been discussed under this context. This paper provides a comprehensive and holistic overview of path-planning techniques custom-tailored for the purpose of maritime data collection. Specifically, we commence with a general portrayal of fundamental models, including system architectures, problem formulations, objective functions, and associated constraints. Subsequently, we summarize the various algorithms, methodologies, platforms, tools, coding environments, and their practical implementations for addressing these models. Furthermore, we delve into the burgeoning applications of path planning in the realm of maritime data harvesting and illuminate potential avenues for upcoming research endeavors. We believe that future research may focus on developing techniques to adapt more intricate and uncertain scenarios, such as sensor failures, inaccurate state estimations, complete modeling of communication channels, ocean dynamics, and application of heterogeneous systems.

show abstract

Section: Meta-heuristic Methodsmentioning

confidence: 99%