Optimal paths for UAV multi-express full delivery in 3D modeling

Abstract

The use of drones in logistics is steadily becoming more common as drone technology advances. As a result, logistics path planning has become a viable research topic. The majority of previous research has concentrated on low-load vehicle-borne UAVs. DJI recently produced a high payload civilian delivery UAV with a maximum capacity of 30 to 40 kg, paving the path for high payload UAVs and providing the criteria for this research. The goal of this research is to increase the efficiency of UAV delivery while also reducing energy consumption, as well as to investigate the path planning problem for large load UAVs in batches. Prior to choosing the ACO method to determine the best route for a single batch, the genetic algorithm is used to achieve the entire load for express delivery in batches. After this, the whole path is determined and supported. The output of the program is the correlation between the number of iterations and the single optimal route, which is then added to produce the overall path. After showing this, we infer that the sum of single ideal paths is the best total path, which maximizes efficiency and saves energy. The significance of this research is to provide some directions for thinking and help for the research of UAV logistics, and we hope to further develop UAV logistics technology to some extent under the premise of energy saving and time saving.