目的 针对低空物流配送中无人机在复杂三维环境下存在路径冗余、能耗偏高、避障效率不足及载货飞行平稳性欠佳等问题,提出一种考虑载货平稳性约束的三维路径规划优化方法。方法 模拟低空物流配送典型场景,构建包含柱状障碍物和球形障碍物的综合三维低空环境模型,提出融合布谷鸟搜索机制的改进灰狼优化算法。采用Cat混沌映射与反向学习策略提升初始种群质量,引入非线性动态权重平衡全局搜索与局部开发,并结合柯西变异算子增强跳出局部最优能力;同时利用三次B样条曲线对路径进行平滑处理。结果 仿真结果表明,所提方法在路径长度、收敛稳定性及避障性能等方面均优于各对比方法。与表现最优的现有方法相比,路径长度进一步缩短3.8%,最大加速度变化率降低51.3%,表明生成路径在连续性和转角变化上更加平缓,有助于减小飞行过程中的动态冲击,提高货物运输稳定性。结论 所提方法可在保证避障安全和降低能耗的同时,提高路径平滑性与载货飞行平稳性,对易损类货物的低空物流配送路径优化具有参考价值。
Abstract
To address the problems of path redundancy, high energy consumption, insufficient obstacle-avoidance efficiency, and poor cargo flight stability of unmanned aerial vehicles in complex three-dimensional environments during low-altitude logistics distribution, the work aims to propose a 3D path planning optimization method considering cargo stability constraints. A representative low-altitude logistics distribution scenario was simulated, and a comprehensive three-dimensional low-altitude environment model containing cylindrical and spherical obstacles was constructed. An improved grey wolf optimization algorithm integrated with a cuckoo search mechanism was then proposed. Cat chaotic mapping and opposition-based learning were employed to improve the quality of the initial population, nonlinear dynamic weights were introduced to balance global exploration and local exploitation and a Cauchy mutation operator was incorporated to enhance the ability to escape local optima. Meanwhile, cubic B-spline curves were used to smooth the planned path. Simulation results showed that the proposed method outperformed all comparison methods in terms of path length, convergence stability, and obstacle-avoidance performance. Compared with the best-performing existing method, the proposed method further reduced path length by 3.8% and maximum jerk by 51.3%, indicating that the generated path was smoother in continuity and turning-angle variation, which helped reduce dynamic impact during flight and improve cargo transport stability. The proposed method can improve path smoothness and cargo flight stability while ensuring obstacle-avoidance safety and reducing energy consumption, and thus provides a useful reference for path optimization in low-altitude logistics distribution of fragile goods.
关键词
低空物流 /
无人机 /
三维路径规划 /
载货飞行平稳性
Key words
low-altitude logistics /
unmanned aerial vehicle /
3D path planning /
cargo flight stability
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基金
天津市自然科学基金重点项目（24JCZDJC00350）; 天津市重点研发计划（24YFZCSN00010）; 天津市津南区“揭榜挂帅”科技计划项目（2025JB06）; 天津市大学生创新创业训练项目（202510069008）
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