提出了一种采用单目视觉和多超声传感器来识别门牌号的室内移动机器人全局自定位方法和导航策略。
This paper proposes a global self-localization method and navigation strategies for indoor mobile robot, based on monocular vision and multi-sonar sensors to recognize the doorplate.
研究了应用线性网络对组合导航多传感器信息进行融合的方法，在此基础上提出了一种神经网络组合导航容错算法。
In this paper, a method of multi-sensor data fusion using neural network in integrated navigation system is given, and then a fault-tolerant algorithm is proposed.
而分层融合结构作为多传感器信息融合的另一种重要的模式，在组合导航系统中应用尚未见报道。
However, the multi level fusion architecture, another important multisensor information fusion mode, has not been applied to the integrated navigation system as far as know.
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