Fuzzy logic-based differential evolution for energy-efficient UAV path planning

Abstract

Unmanned aerial vehicles (UAVs) are emerging as a critical tool in various real-world applications. However, the path planning of UAVs is still challenging. Since UAVs need to fly to several task spots and complete tasks at each spot, the energy consumption of not only UAV flight but also task execution (such as data collection and processing) should be considered, as it may vary across different spots. Therefore, this paper develops a new path planning model for UAVs and proposes a novel fuzzy logic based differential evolution algorithm that provides efficient path planning while ensuring minimal energy consumption.