认知框架下远程AUV多波束测深主动定位算法研究

项目名称： 认知框架下远程AUV多波束测深主动定位算法研究

项目编号： No.51309066

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 水利工程

项目作者： 张强

作者单位： 哈尔滨工程大学

项目金额： 25万元

中文摘要： 远程AUV核心导航系统多为惯性基导航系统，此类导航系统的定位误差随时间累积,不适于远距离、大范围的水下准确定位。考虑到远程AUV的隐蔽性、远程性并受其能源和传感器约束，基于多波束测深信息的地形参考导航系统是抑制惯性基导航系统定位误差的可行方法。但目前该系统的水下远程应用还存在以下主要问题：一、先验海图中的可导航区通常较少,制约了地形参考导航系统的校正频率和定位精度；二、若导航区之间相距较远，地形参考导航系统又不能通过反复获取可导航性高的地形信息来抑制定位结果的发散,故鲁棒性较差。考虑到非结构化海底地形的高度相似性，极易导致多波束声纳对海底地形产生感知歧义，本项目拟在认知框架下构建可导航性约束的主动定位算法，研究海底地形信息的表达及其可导航性的实时评估算法以及导航区的获取策略与固化策略，使地形参考导航系统具有主动导航和主动感知的能力，提升远程AUV导航系统的精度、鲁棒性和智能水平。

中文关键词： 主动定位；智能体；视觉感知；远程水下机器人；多波束测深仪

英文摘要： Navigation system based on inertial sensors is normally adopted as the main navigation system of long range AUV, whereas such kind of navigation system is not suitable for long range, large scale accurate underwater positioning, just because of its accumulated positioning error. Considering the concealment performance, long endurance and constrained by the energy and sensors of long range AUV, the positioning error of inertial navigation system can be effectively reduced by Terrain-Referenced Navigation system (TRN) based on multibeam sonar. However, there are still some challenges faced by TRN when it is used in remote underwater navigation. First, the amount of navigation cells in a priori sea chart is normally small, which restricts the correction frequcncy and positioning accuracy of TRN. Second, if the distance between navigation cells is large, meanwhile the TRN cannot restrain the divergence of position error by repeatedly getting highly navigable terrain information, that all can reasonably make the TRN have poor robustness. Considering the comparatively high similarity of the unstructured undersea terrain which will easily induce aliasing to the terrain information perceived by multibeam sonar, this project will research on the TRN algorithm in a cognitive framework, including constructing the active po

英文关键词： active localization；agent；visual perception；long range AUV；multibeam echosounder