多水下机器人自主海洋特征场跟踪研究  

Tracking strategy analysis with multi underwater vehicles for ocean feature

作　　者：张少伟[1,2] 俞建成[1] 张艾群[1] 赵文涛[1,2] 

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,沈阳110016 [2]中国科学院大学,北京100049

出　　处：《科学通报》2013年第S2期67-74,共8页Chinese Science Bulletin

基　　金：国家自然科学基金(61233013)资助

摘　　要：水下机器人作为可控性能良好的移动观测平台,为实现中小尺度海洋动态过程高分辨率精细观测与动态特征跟踪观测提供了必要的平台条件.本文首先介绍了一种多水下机器人海洋特征跟踪模型,然后基于此模型将队形控制策略与海洋特征场的估计相结合,基于扩展EKF方法建立了海洋特征实时估计模型,对海洋特征量进行实时估计.其次,利用海洋特征估计数据,设计了多水下机器人队形中心跟踪海洋特征等值线的策略及其控制率,并基于主从编队的队形控制模式提出了多个从机器人的队形形成和旋转策略,以应对变化的海洋特征场.最后,建立了近实时的多水下机器人海洋特征场跟踪观测的仿真平台,并通过使用真实海洋数据进行仿真实验验证了这种跟踪策略的有效性和可行性.Autonomous underwater vehicles(AUVs) are mobile platforms with excellent maneuverability, which are preferred for micro scale and meso scale ocean feature tracking in a near real time mode. With the feature extract analysis of ocean phenomena, autonomous control and tracking strategy of multi AUVs are designed for ocean feature tracking. Firstly, formation control is designed coordinately with the estimation of the ocean feature, and EKF(extended Klaman filter) is applied for ocean feature scalar estimation from the sample process noise and sample instrument noise. Secondly, the virtual leader-follow mode is utilized for multi AUVs formation control, and formation rotational is designed to adapt the variation of ocean phenomena. Lastly, the simulation platform is established for multi vehicles ocean feature tracking, and the simulation results are selected to verify the effectiveness of autonomous tracking strategy.

关 键 词：水下机器人 海洋特征 跟踪策略 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]