【摘要】 无人机在水环境监测中,受其物理性能和风险因素影响无法一次性的对所有区域进行监测,充分发挥无人机的使用效率变得极为重要。提出了无人机在水环境监测中的最优航迹规划问题,建立了该问题的数学模型,在此基础上提出了一种基于遗传—模拟退火优化算法,采用网格空间表示与方向编码相结合的方法减小了计算量。仿真实验结果表明:该方法能够得到比遗传算法更优的解,可以有效解决无人机在水环境监测中的航迹规划问题。更多还原

【Abstract】 In water environmental monitoring,unmanned aerial vehicle(UAV) can not monitor all the areas at a time due to the influence of its physical properties and risk factor.So it’s extremely important to bring the service efficiency of the UAV into full play.The optimal path planning problem of the UAV for water environmental monitoring is presented and a mathematic model of the problem is built up.On the basis of this,a geneticsimulation annealing algorithm is presented.The computational amount is decreased,a method combined of both grid space indication and directional code is adopted.The simulation test result indicates that this method can get a better solution than genetic algorithm and it can resolve the path planning problem of the UAV for water environmental monitoring effectively.更多还原