A Method of the Generalized Skill Acquisition of Virtual Mobile Robot for Adapting Environmental Changes using Genetic Algorithms

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  • 遺伝的アルゴリズムによる仮想的な移動ロボットの環境変化に対応する一般化知識の獲得手法
  • イデンテキ アルゴリズム ニヨル カソウテキ ナ イドウ ロボット ノ カンキ

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Abstract

We propose a method for acquisition of generalized action-decision rules for mobile robot which is based on the assumption that selection of adequate focal point is important for the skill acquisition. The method makes it effective to acquire the generalized knowledge which are robust against environmental changes, especially unknown environment. The skill acquisition starts from discovery of rules to drive a robot to a goal point under a certain environment using genetic algorithm. Then, for the generalization of acquired rules, we select an adequate sensing range of the robot for detecting obstacles, which is described in the if-part of rules. Results of computer simulation show that the extracted skills work well to accelerate the learning of robot under new environment.

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