基于 ROS与融合算法的室内无人机路径规划研究

针对四旋翼无人机在室内环境下路径规划效率低、缺乏实用性等问题,提出一种基于融合改进算法的路径规划方法。 首先引入室内混合约束,使用动态加权对传统 A* 算法的评价函数进行重构;其次根据不同地图区域方位角自适应调整邻域 搜索方式;然后考虑无人机实际尺寸影响,设定安全半径,并用Floyd算法对路径做拐点冗余处理;最后融合改进 A* 算法与 改进 DWA 算法,实现了四旋翼无人机的室内自主路径规划和避障。MATLAB 不同仿真环境下的结果表明,改进后算法搜索 节点数和转弯角度分别平均减少63.1%和58.9%,保证全局路径最优的同时,提升了搜索效率与路径安全性。经 ROS 操作 系统的实验结果验证,融合算法在避障效果与运动平稳性等方面具备明显优势,可应用于室内复杂场景下无人机的路 径规划。

Research on indoor UAV path planning based on fusion algorithm

Aiming at the problems of low efficiency and lack of practicality of path planning for quadcopter UAV in indoor environments,a path planning method based on the fusion improvement algorithm is proposed.Firstly,indoor mixing constraints are introduced and dynamic weighting is used to reconstruct the evaluation function of the traditional A* algorithm.Secondly,the neighborhood search method is adaptively adjusted according to the azimuthal angle of different map areas;then the safety radius is set considering the influence of the actual size of the UAV and the path is redundantly processed at the inflection points using Floyd''s algorithm.Finally,indoor autonomous path planning and obstacle avoidance are realized by integrating the improved A"algorithm and the improved DWA algorithm.The results in different simulation environments of MATLAB show that the number of search nodes and the turning angle of the improved algorithm are reduced by an average of 63.1%and 58.9%,respectively,which ensures the optimization of the global path and improves the searching efficiency and the path safety at the same time.As verified by the experimental results of ROS operating system,the fusion algorithm has obvious advantages in obstacle avoidance effect and smoothness of movement,and can be applied to the path planning of UAVs in indoor complex scenes.