山东理工大学学报（自然科学版）2026，Vol.40Issue(4)：50-57,63,9.
细胞型脉冲神经P系统结合GWO的多无人机航迹规划
Multi-UAV path planning based on cell-like spiking neural P systems combined with GWO
摘要
Abstract
In response to the issue of multi-UAV trajectory estimation within acceptable accuracy and time constraints in complex three-dimensional environments,a new multi-UAV trajectory planning algorithm based on a Cell-like Spiking Neural P System combined with a hybrid Grey Wolf Optimization(CSP-GWO)algorithm is proposed.This work leverages the membrane system framework to simulate the parallel operation scenarios of multiple UAVs,while the proposed algorithm utilizes parallelism to model the social hierarchy and behavior of the grey wolf optimizer.A novel fuzzy variant of the hierarchical op-erator is introduced into the grey wolf optimizer to simulate the hunting process,enhancing the algorithm's exploratory capability and ensuring convergence speed.Testing on IEEE CEC benchmark functions vali-dates the optimization and robustness of the proposed method.Additionally,CSP-GWO is used to plan more feasible and stable trajectory paths for three different scales of UAVs,ensuring minimal trajectory costs and shortest simulation time,thereby demonstrating the effectiveness of CSP-GWO in the multi-UAV trajectory planning problem.关键词
细胞型脉冲神经P系统/航迹规划/多无人机/灰狼优化算法Key words
cell-like spiking neural P system/trajectory planning/multi-UAV/grey wolf optimization al-gorithm分类
信息技术与安全科学引用本文复制引用
倪龙,许家昌..细胞型脉冲神经P系统结合GWO的多无人机航迹规划[J].山东理工大学学报（自然科学版）,2026,40(4):50-57,63,9.基金项目
南方林业与生态应用技术国家工程实验室开放基金项目(2023NFLY08) （2023NFLY08）
安徽省自然科学基金面上项目(2308085MF218) （2308085MF218）
安徽省高等学校自然科学研究基金重大项目(2022AH040113) （2022AH040113）
