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Intelligent fusion processing of data perceived through IR sensors of multiple robots

机译:通过多机器人的红外传感器感知的数据的智能融合处理

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This paper addresses the fusion processing techniques of multi-sensor data perceived through the IR sensors of military surveillance robots, which are positioned within a limited range with a lose distance between each of the robots. To combine the multi-sensor data from the distributed battlefield robots, we propose a set of fusion rules to formulate a combined prediction from the multi-source data. Through the use of these fusion rules, we make informed predictions of the type of target, which are represented by the degrees of reliability denoted in mathematical probabilities. We have implemented three fusion operators to compare the capabilities of their fusion processing, and have experimented them in simulated, uncertain battlefield environments. We have also applied fusion techniques to a battlefield simulator with multiple surveillance robots and various types of targets. The experimental results show that the fusion of multi-sensor data from military robots can be successfully tested in randomly generated military scenarios.
机译:本文讨论了通过军事监视机器人的红外传感器感知到的多传感器数据的融合处理技术,这些传感器位于有限的范围内,每个机器人之间的丢失距离很大。为了组合来自分布式战场机器人的多传感器数据,我们提出了一组融合规则,以根据多源数据制定组合的预测。通过使用这些融合规则,我们可以对目标类型进行明智的预测,并以数学概率表示的可靠性程度来表示。我们已经实现了三个融合算子,以比较它们的融合处理能力,并在模拟,不确定的战场环境中对其进行了实验。我们还将融合技术应用于具有多个监视机器人和各种目标的战场模拟器。实验结果表明,可以在随机生成的军事场景中成功测试来自军事机器人的多传感器数据融合。

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