3D UAV Route Optimization in Complex Environments Using an Enhanced Artificial Lemming Algorithm

作者：Yuxuan Xie, Zhe Sun, Zhe Sun, Kai Yuan, Zhixin Sun, Zhixin Sun · 发表于：Symmetry · 年份：2025 · DOI：10.3390/sym17060946 · 被引用次数：7 · 研究领域：Robotic Path Planning Algorithms、Robotics and Sensor-Based Localization、UAV Applications and Optimization

The use of UAVs for logistics delivery has become a hot topic in current research, and how to plan a reasonable delivery route is the key to the problem. Therefore, this paper proposes a multi-environment logistics delivery route planning model that is based on UAVs, is characterized by a 3D environment model, and aims at the shortest delivery route with minimum flight undulation. In order to find the optimal route in various environments, a multi-strategy improved artificial lemming algorithm, which integrates the Cubic chaotic map initialization, double adaptive t-distribution perturbation, and population dynamic optimization, is proposed. The symmetric nature of the t-distribution ensures that the lemmings conduct extensive searches in both directions within the solution space, thus improving the convergence speed and preventing them from falling into local optimal solutions. Through data experiments and simulation analysis, the improved algorithm can be successfully applied to the 3D route planning model, and the route quality is superior.