Comparison of path planning methods for robot navigation in simulated agricultural environments

Juan P. Vasconez; Fernando Basoalto; Inesmar C. Briceno; Jenny M. Pantoja; Roberto A. Larenas; Jhon H. Rios; Felipe A. Castro

doi:10.1016/j.procs.2023.03.122

Comparison of path planning methods for robot navigation in simulated agricultural environments

Juan P. Vasconez, Fernando Basoalto, Inesmar C. Briceno, Jenny M. Pantoja, Roberto A. Larenas, Jhon H. Rios, Felipe A. Castro

Research output: Contribution to journal › Conference article › peer-review

5 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	898-903
Number of pages	6
Journal	Procedia Computer Science
Volume	220
DOIs	https://doi.org/10.1016/j.procs.2023.03.122
Publication status	Published - 2023
Event	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, Belgium Duration: 15 Mar 2023 → 17 Mar 2023

Keywords

Agriculture
Mobile robot
Path planning

ASJC Scopus subject areas

General Computer Science

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.procs.2023.03.122

Cite this

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title = "Comparison of path planning methods for robot navigation in simulated agricultural environments",

abstract = "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.",

keywords = "Agriculture, Mobile robot, Path planning",

author = "Vasconez, {Juan P.} and Fernando Basoalto and Briceno, {Inesmar C.} and Pantoja, {Jenny M.} and Larenas, {Roberto A.} and Rios, {Jhon H.} and Castro, {Felipe A.}",

note = "Publisher Copyright: {\textcopyright} 2023 Elsevier B.V.. All rights reserved.; 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 ; Conference date: 15-03-2023 Through 17-03-2023",

year = "2023",

doi = "10.1016/j.procs.2023.03.122",

language = "English",

volume = "220",

pages = "898--903",

journal = "Procedia Computer Science",

issn = "1877-0509",

publisher = "Elsevier B.V.",

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TY - JOUR

T1 - Comparison of path planning methods for robot navigation in simulated agricultural environments

AU - Vasconez, Juan P.

AU - Basoalto, Fernando

AU - Briceno, Inesmar C.

AU - Pantoja, Jenny M.

AU - Larenas, Roberto A.

AU - Rios, Jhon H.

AU - Castro, Felipe A.

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - Agriculture

KW - Mobile robot

KW - Path planning

UR - http://www.scopus.com/inward/record.url?scp=85164495986&partnerID=8YFLogxK

U2 - 10.1016/j.procs.2023.03.122

DO - 10.1016/j.procs.2023.03.122

M3 - Conference article

AN - SCOPUS:85164495986

SN - 1877-0509

VL - 220

SP - 898

EP - 903

JO - Procedia Computer Science

JF - Procedia Computer Science

T2 - 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

Y2 - 15 March 2023 through 17 March 2023

ER -

Comparison of path planning methods for robot navigation in simulated agricultural environments

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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