Unsupervised Learning-Based Data Collection Planning with Dubins Vehicle and Constrained Data Retrieving Time
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00380506" target="_blank" >RIV/68407700:21230/24:00380506 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-67159-3_2" target="_blank" >https://doi.org/10.1007/978-3-031-67159-3_2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-67159-3_2" target="_blank" >10.1007/978-3-031-67159-3_2</a>
Alternative languages
Result language
angličtina
Original language name
Unsupervised Learning-Based Data Collection Planning with Dubins Vehicle and Constrained Data Retrieving Time
Original language description
In remote data collection from sampling stations, a vehicle must be within sufficient distance from a particular station for a predefined minimal time to retrieve required data from the site. The planning task is to find a cost-efficient data collection plan to retrieve data from all the stations. For a fixed-wing aerial vehicle flying with a constant forward velocity, the problem is to determine the shortest feasible path that visits every sensing site and ensure the vehicle is within a reliable communication distance from the station for a sufficient period. We propose to formulate the planning problem as a variant of the Close Enough Dubins Traveling Salesman Problem with Time Constraints (CEDTSP-TC) that is heuristically solved by unsupervised learning of the Growing Self-Organizing Array (GSOA) modified to address the constrained minimal data retrieving time. The proposed method is compared with a baseline based on a sampling-based decoupled approach, and the results support the feasibility of both proposed solvers in random instances.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA22-05762S" target="_blank" >GA22-05762S: Towards Optimal Solution of Robotic Routing Problems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond
ISBN
978-3-031-67158-6
ISSN
2367-3370
e-ISSN
2367-3389
Number of pages
11
Pages from-to
11-21
Publisher name
Springer Nature Switzerland AG
Place of publication
Basel
Event location
Mittweida
Event date
Jul 10, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001322509700002