基于引力搜索算法的植保无人机三维路径规划方法

为了使植保无人机作业更加精准、高效与节能,研究了一种适用于三维地形的植保无人机路径规划方法。根据农田的规模、形状、高度起伏等地理环境信息,对其进行栅格化处理,建立三维环境模型;在此环境模型条件下,为无人机增加直行与回转机制,实现全覆盖路径仿真;通过提取仿真计算中每次植保作业飞行距离作为输入变量、非植保作业耗费时间作为输出函数,从而构建寻优模型;对寻优模型引入引力搜索算法,以输出函数最小为目标,对输入变量进行寻优,再通过仿真计算求出优化后的返航点位置。实例结果显示,在二维投影形状与尺寸相同的田地中,二维与三维路径规划方法之间的返航点位置存在偏差,证明了本文方法的必要性;在三维地形算例中,运用本文方法规划后的往返飞行距离总和与非植保作业时间分别为440.2 m与9 min,相比于未规划情况分别减少了90%与54%,相比于简单规划结果分别减少了23%与7%。在实际测试过程中,相比于未规划情况,规划后的路径飞行距离总和与非植保作业时间分别减少了11%和5%,验证了本文方法的合理性与可行性。

3D Path Planning Approach Based on Gravitational Search Algorithm for Sprayer UAV

In order to improve the field efficiency and reduce the operation cost, a research was conducted on the path planning method for the sprayer UAV in the field with 3D terrain. Firstly, aiming at building a 3D environment model, the grid method was selected to divide the field into small grids with the initialized properties. Secondly, the UAV was ordered to move from the current grid to the adjacent one with the highest probability. And therefore a coverage path which moved from one extreme of the field to the other in direction parallel to the crop rows alternately and turned at the boundary was identified. Thirdly, a mathematical model was established, of which the objective was to obtain the optimal return points with the minimum time in the non-spraying mode. Once the gravitational search algorithm was applied to solve the model, the planned path with return points would be outputted automatically by the proposed method. Furthermore, the proposed method was compared with the method for 2D terrain in a 700m×100m field, of which the result showed that there was deviation between the positions of the return points calculated by the different methods. And the same field was taken to test the performance of the proposed method, in which the proposed method was compared with simple path plan method and unplanned path respectively. Results showed that the advantages of the proposed method at the distance of the round trips was reduced by 23% and 90%, while the non-spraying time was reduced by 7% and 54%, respectively. After that, the proposed method was applied to a real field with 3D terrain. And the distance of the round trips and the non-spraying time were reduced by 11% and 5%, respectively in the experiment. Finally, the research result indicated that the proposed method was a reasonable, feasible and useful alternative to produce paths with less time for the sprayer UAV.