基于能量优化的无人机喷施规划组合算法研究
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

国家重点研发计划项目(2017YFD0701001)、国家自然科学基金项目(31771682)、广东省重大科技计划项目(2017B010116003)和广州市科技计划项目(201807010039)


Research and Implementation of Combination Algorithms about UAV Spraying Planning Based on Energy Optimization
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    针对目前无人机喷施规划并未达到能量利用率最大化的问题,以总航程最短、有效载荷和安全作业为作业目标,研究了一种基于能量优化的无人机喷施规划组合算法。利用栅格法对工作区域进行划分,得到全覆盖航线后,通过设置补给点,合理地分配各架次的返航点和有效载荷,从航线和载荷上降低无人机的能量消耗率,提高了作业效率。所设计的配套地面站软件对算法进行仿真,结果表明,在同等作业条件下,采用本组合算法进行无人机喷施规划,相比于传统以药液或能量耗尽为返航依据、偶有迫降或坠机危险的喷施规划,航程规划得到的能量节省率达16.25%,载荷规划得到的能量节省率为18.92%。田间对比试验表明,经过算法规划的作业比未经算法规划的作业节省了2725m的返航航程,航程节省率为23.7%;节省载荷1L,载荷节省率为16.7%。本组合算法能保证无人机在能量满足安全条件的情况下进行作业,证实了算法的节能性和安全性。

    Abstract:

    Aiming at the current situation that the planning of unmanned aerial vehicle (UAV) spraying has not reached the maximum energy utilization rate, target for the shortest total path, payload and safe operation, a combined algorithm of UAV spraying planning based on energy optimization was researched. Using grid method to divide working area, after getting full coverage, the return points can be distributed rationally and the payloads of sorties by setting up supply points, which reduced energy consumption rate of UAV from route and path and improved operational efficiency. The simulation results of the algorithm by the designed mating software of earth station showed that under the same operating conditions, compared with traditional spraying planning which based on drug or energy exhaustion but had occasional forced landing or crash risk, using the combination algorithms to plan the spraying of UAV can save rate of range planning about 16.25% and that of load planning about 18.92%. From the field contrast test, the algorithmplanned operation saved 2725m returning flying range compared with the nonalgorithmplanned operation. The savings rate of flying range was 23.7%. And it can save load about 1L, which meant that the saving rate of load was 16.7%. In summary, this combinational algorithm can save energy effectively and ensure that only when their energy satisfied the safeguard requirement, UAV would operate, and it furtherly verified the energy saving and security of the algorithm.

    参考文献
    相似文献
    引证文献
引用本文

李继宇,罗慧莹,朱长威,李一凡,汤峰.基于能量优化的无人机喷施规划组合算法研究[J].农业机械学报,2019,50(10):106-115.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2019-03-11
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2019-10-10
  • 出版日期: 2019-10-10