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 journalConference articlepeer-review

4 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 languageEnglish
Pages (from-to)898-903
Number of pages6
JournalProcedia Computer Science
Volume220
DOIs
Publication statusPublished - 2023
Event14th 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 202317 Mar 2023

Keywords

  • Agriculture
  • Mobile robot
  • Path planning

ASJC Scopus subject areas

  • General Computer Science

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