多水下滑翔机海洋采样路径规划  

Path Planning of Multiple Underwater Gliders for Ocean Sampling

作　　者：朱心科[1,2,3] 俞建成[1] 王晓辉[1] 

机构地区：[1]中国科学院沈阳自动化研究所机器人学国家重点实验室,辽宁沈阳110016 [2]国家海洋局第二海洋研究所国家海洋局海底科学重点实验室,浙江杭州310012 [3]中国科学院研究生院,北京100049

出　　处：《信息与控制》2012年第4期433-438,共6页Information and Control

基　　金：中国科学院知识创新工程资助项目(KZCX2-YW-JS205);机器人学国家重点实验室创新课题资助项目(RLZ200810);机器人学国家重点实验室课题资助项目(2009-Z05);国家海洋局青年海洋科学基金资助项目(2011333);国家海洋局第二海洋研究所基本科研业务费专项资助项目(JT1001);浙江省自然科学基金资助项目(LQ12D06002)

摘　　要：提出了以时间为优化准则的多水下滑翔机海洋采样路径规划算法.首先,根据水下滑翔机的个数,通过空间聚类算法,把多水下滑翔机的路径规划问题转化为单水下滑翔机的路径规划问题;然后,利用2步CLK(chained Lin-Kernighan)算法,优化每一个采样子空间中的采样路径;设计了扩散算法,调节各个采样子空间的采样点,使得完成整个采样任务需要的时间最短;最后,以Sea-wing水下滑翔机为例,对上述方法进行了仿真验证,结果显示所提出的方法能够有效地降低采样作业的采样时间.An approach to path planning of the multiple underwater gliders for ocean sampling is presented based on the optimization criterion of sampling time. Firstly, according to the number of the gliders, the path planning problem of the multiple underwater gliders is transformed into a single glider path planning problem by the spatial clustering algorithm. Secondly, the two-step CLK （chained Lin-Kernighan） algorithm is applied to optimizing the sampling path in each sampling subspace. A diffusion algorithm is designed to adjust the sampling points among the sampling subspaces, which minimizes the sampling time of the whole sampling mission. Finally, taking the Sea-wing underwater glider as an example, the simula- tion experiments are carded out to verify the proposed methods. The results show that the methods can efficiently reduce the sampling time spent on the sampling task.

关 键 词：多水下滑翔机 路径规划 海洋采样 扩散算法 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]