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Coverage Path Planning Methods Focusing on Energy Efficient and Cooperative Strategies for Unmanned Aerial Vehicles
The coverage path planning (CPP) algorithms aim to cover the total area of interest with minimum overlapping. The goal of the CPP algorithms is to minimize the total covering path and execution time. Significant research has been done in robotics, particularly for multi-unmanned unmanned aerial vehi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8839296/ https://www.ncbi.nlm.nih.gov/pubmed/35161979 http://dx.doi.org/10.3390/s22031235 |
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author | Fevgas, Georgios Lagkas, Thomas Argyriou, Vasileios Sarigiannidis, Panagiotis |
author_facet | Fevgas, Georgios Lagkas, Thomas Argyriou, Vasileios Sarigiannidis, Panagiotis |
author_sort | Fevgas, Georgios |
collection | PubMed |
description | The coverage path planning (CPP) algorithms aim to cover the total area of interest with minimum overlapping. The goal of the CPP algorithms is to minimize the total covering path and execution time. Significant research has been done in robotics, particularly for multi-unmanned unmanned aerial vehicles (UAVs) cooperation and energy efficiency in CPP problems. This paper presents a review of the early-stage CPP methods in the robotics field. Furthermore, we discuss multi-UAV CPP strategies and focus on energy-saving CPP algorithms. Likewise, we aim to present a comparison between energy efficient CPP algorithms and directions for future research. |
format | Online Article Text |
id | pubmed-8839296 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88392962022-02-13 Coverage Path Planning Methods Focusing on Energy Efficient and Cooperative Strategies for Unmanned Aerial Vehicles Fevgas, Georgios Lagkas, Thomas Argyriou, Vasileios Sarigiannidis, Panagiotis Sensors (Basel) Review The coverage path planning (CPP) algorithms aim to cover the total area of interest with minimum overlapping. The goal of the CPP algorithms is to minimize the total covering path and execution time. Significant research has been done in robotics, particularly for multi-unmanned unmanned aerial vehicles (UAVs) cooperation and energy efficiency in CPP problems. This paper presents a review of the early-stage CPP methods in the robotics field. Furthermore, we discuss multi-UAV CPP strategies and focus on energy-saving CPP algorithms. Likewise, we aim to present a comparison between energy efficient CPP algorithms and directions for future research. MDPI 2022-02-06 /pmc/articles/PMC8839296/ /pubmed/35161979 http://dx.doi.org/10.3390/s22031235 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Fevgas, Georgios Lagkas, Thomas Argyriou, Vasileios Sarigiannidis, Panagiotis Coverage Path Planning Methods Focusing on Energy Efficient and Cooperative Strategies for Unmanned Aerial Vehicles |
title | Coverage Path Planning Methods Focusing on Energy Efficient and Cooperative Strategies for Unmanned Aerial Vehicles |
title_full | Coverage Path Planning Methods Focusing on Energy Efficient and Cooperative Strategies for Unmanned Aerial Vehicles |
title_fullStr | Coverage Path Planning Methods Focusing on Energy Efficient and Cooperative Strategies for Unmanned Aerial Vehicles |
title_full_unstemmed | Coverage Path Planning Methods Focusing on Energy Efficient and Cooperative Strategies for Unmanned Aerial Vehicles |
title_short | Coverage Path Planning Methods Focusing on Energy Efficient and Cooperative Strategies for Unmanned Aerial Vehicles |
title_sort | coverage path planning methods focusing on energy efficient and cooperative strategies for unmanned aerial vehicles |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8839296/ https://www.ncbi.nlm.nih.gov/pubmed/35161979 http://dx.doi.org/10.3390/s22031235 |
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