Multi-sensor integration system based on fuzzy inference and neural network for industrial application

Toshio Fukuda, Koji Shimojima, F. Arai, H. Matsuura
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引用次数: 26

Abstract

The authors deal with a multi-sensor system applied to an unknown curved metal surface cutting robot system. The measurements were performed by sensors set on an array of the tip of a five axis manipulator. The sensor array is carried to the target surface by moving the manipulator. The manipulator approaches the surface by using sensor outputs. To approach the work fast, the system should use long measurement range sensors. For precise cutting and a fast approach, the system should use both high accuracy sensors and long measurement range sensors. To use these sensors effectively, the multi-sensor integration system was based on neural network and fuzzy inference techniques. As a result, the system can consider the angle between the sensors and the object. The proposed system was shown to be effective through extensive experiments.<>
基于模糊推理和神经网络的工业多传感器集成系统
研究了一种应用于未知曲面金属切割机器人系统的多传感器系统。测量是通过设置在五轴机械手尖端阵列上的传感器进行的。通过移动机械手将传感器阵列搬运到目标表面。机械手通过传感器输出接近表面。为了快速接近工作,系统应采用远量程传感器。为了实现精确切割和快速切割,系统应同时使用高精度传感器和长测量范围传感器。为了有效地利用这些传感器,多传感器集成系统基于神经网络和模糊推理技术。因此,系统可以考虑传感器与物体之间的角度。通过大量的实验表明,所提出的系统是有效的。
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