应急测绘无人机资源多目标优化调度方法

发布时间：2018-07-06 09:37

本文选题：应急测绘 + 无人机调度　；参考：《武汉大学学报(信息科学版)》2017年11期

【摘要】：应急测绘中的无人机调度存在时空环境约束复杂、调度方案多样的特点,现有调度主要以人为经验判断为主,方案粗放不可靠,难以综合考虑应急过程中复杂多变的因素,结果的精准性与可靠性较低。为实现灾后应急测绘的快速响应,提出了一种无人机资源的快速调度方法,综合考虑应急测绘任务需求、优先级、时间窗、作业区域地理环境和无人机测绘资源能力等约束条件,构建了以任务成果收益效率最大化、任务完成率最大化以及调度风险最小化等为多优化目标的应急测绘无人机资源调度模型,并运用蚁群算法实现对模型的求解。实验结果验证了调度方法的有效性。
[Abstract]:UAV scheduling in emergency mapping has the characteristics of complex spatio-temporal environment constraints and diverse scheduling schemes. The existing scheduling is mainly based on human experience judgment, and the scheme is not reliable, so it is difficult to comprehensively consider the complex and changeable factors in the emergency process. The accuracy and reliability of the results are low. In order to realize the rapid response of post-disaster emergency mapping, a rapid scheduling method of UAV resources is proposed, which takes into account the needs, priorities, time windows of emergency mapping tasks. Based on the constraints of geographical environment and UAV mapping resources, the maximum efficiency of mission results is constructed. The task completion rate maximization and scheduling risk minimization are multi-optimization objectives for emergency mapping UAV resource scheduling model. Ant colony algorithm is used to solve the model. Experimental results demonstrate the effectiveness of the scheduling method.
【作者单位】：武汉大学测绘遥感信息工程国家重点实验室;西南交通大学地球科学与环境工程学院;武汉大学科学技术发展研究院;四川测绘地理信息局测绘技术服务中心;
【基金】：国家自然科学基金(41471320,41571390,41501463) 四川省测绘地理信息局局科技支撑项目(J2014ZC11)~~
【分类号】：P231

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