摘要
无人机自身具有的航空特性和可以进行大面积巡查的特点,使得其在洪水、旱情、地震等自然灾害实时监测方面具备特别优势.在完成灾情巡查、生命迹象探测、通信中继和对地数据传输等协同任务时,需要对无人机进行任务分配与航迹规划.对于无人机巡查重点区域任务规划问题,基于分层规划思想建立了多旅行商数学模型,并使用遗传算法进行求解.首先分配重点区域之间的无人机任务,其次再规划重点区域内部无人机的路线,最后根据无人机的限制条件,在既定路线上进一步优化无人机路线.
Unmanned aerial vehicle （UAV） has the characteristics of aviation and large area inspection, which have special advantages in real-time monitoring of natural disasters such as flood, drought, and earthquake arid so on. In the process of disaster patrol, life detection, communication relay and ground data transmission, task assignment and path planning are needed for UAV. In order to solve the mission planning problem of unmanned aerial vehicles （UAV） patrolling key areas, a multi traveling salesman mathematical model is established based on the hierarchical planning idea, and the genetic algorithm is used to solve the problem. Firstly, the UAV mission between the key areas is assigned. Then the UAV route in the key area is planned. Finally, the UAV route is further optimized on the established route according to the constraints of the UAV.
作者
章超
李昀阳
杨思
白羽
Zhang Chao1, Li Yunyang1, Yang Si2, Bai Yu3(1. School of Civil and Traffic Engineering, Beijing University of Civil and Architecture, Beijing 100044 ; 2. School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture,Beijing 100044 3. School of Science, Beijing University of Civil and Architecture, Beijing 10004)
出处
《北京建筑大学学报》
2018年第1期70-75,共6页
Journal of Beijing University of Civil Engineering and Architecture
基金
国家自然科学基金项目(21576023
51406008)
"十三五"国家重点研发计划(2016YFC0700601)
关键词
无人机
分层规划
协同优化
unmanned aerial vehicle
hierarchical planning
collaborative optimization
