ニューロ・遺伝的アルゴリズムを用いた移動物体軌跡計測システムの開発

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  • Development of Locus Measuring System for Cruising Object using Neural Network and Genetic Algorithm
  • ニューロ イデンテキ アルゴリズム オ モチイタ イドウブッタイ キセキ ケイ

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In recent years, an automated mobile vehicle without direct control by a human has been researched and developed at the companies and universities. We have proposed the tracking control system of the autonomous mobile robot with multiple sensors in which supersonic distance sensors and infrared direction sensors are configured. In discussion on the controllability of the vehicle, it must be indispensable for us to track the trajectory of moving vehicle precisely without human manipulation. In the paper, we have proposed a new locus measuring system for cruising object using the neural network and genetic algorithm. Especially in the present neural network algorithm, the learning process with noises is introduced to enhance the percentage of the recognition of the objects in case of damaged or un-focal images with noises and being out of focus. The paradigm based on the genetic algorithm (GA) is introduced to enhance the speed of the rough detection of the target object because the scanning target could not be conducted randomly in the neural network approach.

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