深水机器人低成本导航系统的位置估计方法研究

依据6000米自治水下机器人及其长基线声学定位系统现有的导航设备,将测距声信标和机器人载体携带的低成本导航传感器:涡轮式计程仪,压力传感器以及TCM2电子罗盘测量的导航数据相融合,分别提出两种基于EKF的导航数据融合算法,对机器人的位置以及水流参数进行估计,解决复杂环境下的深水机器人位置估计问题.蒙特卡洛仿真实验和湖上试验数据后处理表明,设计的位置估计算法收敛快,精度高,计算时间小,能够满足深水机器人的导航需要.

The measurement data from low-cost sensors,which include turbine log,pressure sensor and TCM2 digital compass,are fused with range measurement results from acoustic beacons based on present navigation equipment of 6000 meters AUV and long base-line positioning system.Aiming at the navigation problem of the vehicle under complicated environment,two data fusion algorithms are presented based on the EKF for the estimation of the vehicle location and water current.Both Mont-Carlo simulation and post-processing of lake experiment data show that the designed position estimation algorithms are able to satisfy the requirements of navigation of dee Pwater vehicles.

国家自然科学基金(60775061)资助项目