An integrated multi-sensor data fusion algorithm and autopilot implementation in an uninhabited surface craft
An integrated multi-sensor data fusion algorithm and autopilot implementation in an uninhabited surface craft
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DOI：
10.1016/j.oceaneng.2011.11.001
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发表时间：
2012
影响因子：
5
通讯作者：
W. Naeem;R. Sutton;Tao-rang Xu
中科院分区：
文献类型：
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作者：
W. Naeem;R. Sutton;Tao-rang Xu
无人水面车辆（usv）能够在不危及人类生命的情况下完成民用和国防部门的困难和具有挑战性的任务。他们夜以继日地工作的能力使他们非常适合处理需要立即处理的事情。这些问题包括但不限于地雷对策、测量石油泄漏的程度和确定化学物质排放的来源。为了上述各种目的，在过去十年中出现了一些USV方案。施普林格USV就是本文重点研究的一个项目。本文的目的是报告在施普林格船上测试其先进导航、制导和控制（NGC）子系统时获得的实验数据的结果。为这些系统开发的算法基于软计算方法。提出了一种新的数据融合导航算法，并将其与改进的最优控制器相结合。给出并分析了单路点和多路点跟踪、固定和时变参考轴承等不同情况下的实验结果。结果表明，尽管存在建模不确定性和外部干扰，所提出的NGC系统仍能提供令人满意的结果。
Unmanned surface vehicles (USVs) are able to accomplish difficult and challenging tasks both in civilian and defence sectors without endangering human lives. Their ability to work round the clock makes them well-suited for matters that demand immediate attention. These issues include but not limited to mines countermeasures, measuring the extent of an oil spill and locating the source of a chemical discharge. A number of USV programmes have emerged in the last decade for a variety of aforementioned purposes. Springer USV is one such research project highlighted in this paper. The intention herein is to report results emanating from data acquired from experiments on the Springer vessel whilst testing its advanced navigation, guidance and control (NGC) subsystems. The algorithms developed for these systems are based on soft-computing methodologies. A novel form of data fusion navigation algorithm has been developed and integrated with a modified optimal controller. Experimental results are presented and analysed for various scenarios including single and multiple waypoints tracking and fixed and time-varying reference bearings. It is demonstrated that the proposed NGC system provides promising results despite the presence of modelling uncertainty and external disturbances.