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.