基于自适应动态窗口改进细菌趋化算法的UAV三维路径规划

An Improved Bacterial Chemotaxis Algorithm for Three-dimensional UAV Path Planning Based on Adaptive Dynamic Window

针对UAV三维路径规划问题,提出一种自适应三维动态窗口(self_3D_DWA)改进细菌趋化(3D_IBF)算法的混合三维路径规划算法(3D_IBASDWA).该算法在二维动态窗口和标准细菌趋化算法基础上,结合全局和局部路径规划,既能计算出复杂环境中全局最优解,又能实现局部抗干扰动态避障.此外,该算法还引进Logistics混沌策略进一步优化细菌趋化算法全局路径计算,从而规划出具有较高计算精度和较快收敛速度的参考路径.接着,基于参考路径,UAV通过自身携带的传感器实时感知动态障碍物,并利用自适应三维动态窗口算法实现局部抗干扰动态避障.仿真实验证明基于改进算法的UAV三维空间路径规划在计算精度、收敛速度和动态避障等方面都有明显提升.

A hybrid three-dimensional path planning algorithm(3D_IBASDWA)is proposed as a solution to the path planning problem of unmanned aerial vehicles(UAVs)in three-dimensional space based on an adaptive dynamic window(self_3D_DWA)and an improved bacterial chemotaxisalgorithm(3D_IBF).The enhanced algorithm integrates the two-dimensional dynamic window and bacterial chemotaxis algorithms with global and local path planning,enabling the resolution of both global optimal solutions and the circumvention of local dynamic obstacles with disturbances.Additionally,the logistics chaos strategy is incorporated into the global path optimization process based on the bacterial chemotaxis algorithm,thereby enhancing the precision of calculations and accelerating the convergence rate in path planning.Moreover,the sensors are employed to ascertain the presence of dynamic obstacles for the UAV based on the obtained path.The three-dimensional dynamic window self-adaptive algorithm is employed for the circumvention of dynamic obstacles.The simulation results demonstrate the efficacy of the enhanced algorithm in terms of precision in calculation,rapid convergence,and the avoidance of dynamic obstacles.