Three-Dimensional Path Planning for Unmanned Aerial Vehicles Based on Multi-Strategy Improved Spider Wasp Optimization
Yanan Hu, Zhenni Peng, Xintong Yang, Zhicheng Ling · Journal of Physics Conference Series · 2025
Abstract Aiming at the issues of slow search speed, limited local search capability and easy to become trapped in local optimum of Spider Wasp Optimization (SWO) in the trajectory planning algorithm of Unmanned Aerial Vehicles (UAVs), this paper proposes an Improved Spider Wasp Optimization (ISWO).The initialization of the population in the ISWO algorithm using chaotic mapping techniques enhances uniformity and diversity of initial solutions, preventing premature convergence and facilitating thorough exploration of the search space. This unpredictability helps avoid local optima traps. Additionally, the adaptive weight factor adjusts the equilibrium between exploration and exploitation founded on the optimization state, allowing efficient transitions between broad and focused searches. The Cauchy variant optimization enables larger jumps in the search space, aiding in escaping local optima and exploring distant areas for better solutions. Together, these improvements lead to faster convergence, reduced planning time, and better solution quality in complex optimization problems.