Comparison of path planning methods for robot navigation in simulated agricultural environments
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Fecha
2023-03
Autores
Vasconez, Juan P.
Basoalto, Fernando
Briceno, Inesmar C.
Pantoja, Jenny M.
Larenas, Roberto A.
Rios, Jhon H.
Castro, Felipe A.
Profesor/a Guía
Facultad/escuela
Idioma
en
Título de la revista
ISSN de la revista
Título del volumen
Editor
Elsevier B.V.
Nombre de Curso
Licencia CC
CC BY-NC-ND 4.0 DEED Attribution-NonCommercial-NoDerivs 4.0 International
Licencia CC
https://creativecommons.org/licenses/by-nc-nd/4.0/
Resumen
Path planning is a research topic that is still being studied for the area of mobile robotics. However, path-planning algorithms for mobile robot applications depend strongly on the environment and its complexity. In this work, we implemented three different path-planning algorithms for a simulated agricultural process. The selected algorithms are Breadth First search (BFS), Depth first search (DFS), and A∗. We compare and evaluate such algorithms by using different accuracy metrics. The results demonstrate that the A∗path planning method outperforms the other methods considering processing time, travel time, distance, and battery consumption. © 2023 Elsevier B.V.. All rights reserved.
Notas
Indexación: Scopus
Palabras clave
Agriculture, Mobile robot, Path planning
Citación
Procedia Computer Science. Volume 220, Pages 898 - 903. 2023. 14th International Conference on Ambient Systems, Networks and Technologies Networks, ANT 2023 and The 6th International Conference on Emerging Data and Industry 4.0, EDI40 2023.Leuven. 15 March 2023through 17 March 2023. Code 189712
DOI
10.1016/j.procs.2023.03.122