Comparison of path planning methods for robot navigation in simulated agricultural environments
Juan Pablo Vásconez, Fernando Basoalto, Inesmar C. Briceño, Jenny M. Pantoja, Roberto A. Larenas, Jhon H. Rios, Felipe A. Castro
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.