Optimised path planning of a UAV for inventory management applications

Abstract

Inventory management in warehouses is a crucial task in the logistics industry. Manual stocktaking in larger-scale warehouses can be time-consuming and labour-intensive. To automate this process, unmanned aerial vehicles (UAVs) have gained popularity due to their potential to offer safer, timeous, and more efficient solution. However, deploying drone systems can face challenges and therefore requires planning tasks such as path planning. This study investigates two commonly used UAV flight paths to identify the optimal path within a warehouse: zigzag and up-down flight paths. A Gazebo simulation was considered with a six-rotor UAV model to analyse the different flight paths. The accuracy of both path types is measured for comparison, and flight times were considered as a means for optimisation. The results indicated that the zigzag flight path is the most optimal with the shortest flight time. The study found that the zigzag path resulted in a 27.25% shorter estimated flight time compared to the up-down path.