A Self-Learning Algorithm for Primitive Actions’ Affordances of Nuclear Power Plant Maintenance Robot-Reference-Cited by-同舟云学术

A Self-Learning Algorithm for Primitive Actions’ Affordances of Nuclear Power Plant Maintenance Robot

Published:2014-12 Issue: Volume:701-702 Page:219-222
ISSN:1662-7482
Container-title:Applied Mechanics and Materials
language:
Short-container-title:AMM

Author:

Liu Chun Yang¹,Zhang Jing Wei²,Zheng Xue Feng¹,Tu Xu Yan¹

Affiliation:

1. University of Science and Technology Beijing

2. North China Electric Power University

Abstract

In this paper, an algorithm concerning the primitive action affordances of learning nuclear power plant maintenance robot is presented. The algorithm generates a random matching data set through a new matching method, which is utilized for the selection of object operation, with the matching rate improved by trial and error, and then the attempt number for a successful operation is reduced. In the end, simulation is conducted to verify the feasibility and correctness of the proposed algorithm.

Publisher

Trans Tech Publications, Ltd.

Link

https://www.scientific.net/AMM.701-702.219.pdf

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