Optimizing Drone Navigation Using Shortest Path Algorithms

Abstract

In modern agriculture, the use of agricultural drones (UAV) has gained significant popularity due to their ability to efficiently monitor and manage vast farmlands. To optimize the drone’s route for tree inspection and pesticide spraying, we propose a novel approach that involves manual collection of tree coordinates (latitude and longitude values) using a mobile device. The collected data is then used to generate a detailed map of the agricultural area. To ensure efficient drone operation, we employ the Haversine method to calculate the distances between trees accurately. This technique accounts for the curvature of the earth, providing precise distance measurements based on the coordinates spherical nature. Subsequently, we utilize Dijkstra’s algorithm and Travelling Salesman Problem algorithm to compute the shortest path between the trees, ensuring that the drone follows an optimized route during its spraying mission. In this research, we present the implementation details and results of our proposed methodology. The experimental evaluation demonstrates the superiority of our approach over traditional methods in terms of minimizing drone travel distance and optimizing data collection.