Energy-Efficient UAV Delivery Optimization via Clustering and Layered Path Planning

This paper introduces an innovative framework for optimizing vertical drone delivery systems by integrating clustering techniques and layer creation methodologies. Building on the foundational concepts of energy optimization and operational efficiency highlighted in the existing literature, we propose a comprehensive model that addresses the complexities of last mile logistics in urban environments. Our approach employs clustering to group customers based on proximity and demand, allowing for more efficient routing strategies that minimize energy consumption. In addition, we introduce a layered delivery system that facilitates altitude management and obstacle avoidance to ensure efficient and compliant drone navigation. Through extensive numerical experiments, the model shows significant improvements in delivery efficiency and energy utilization, demonstrating its adaptability to varying payload conditions and environmental constraints. The findings underscore the potential of this framework to advance sustainable urban logistics and inform future research in multi-drone and multidepot delivery systems.