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Author:

Yu Jianjun (Yu Jianjun.) | Zhou Lu (Zhou Lu.) | Du Hongwei (Du Hongwei.) | Wang Guanwei (Wang Guanwei.)

Indexed by:

CPCI-S

Abstract:

This paper apply operant conditioning automata to bionic behavior which used for hexapod robot at unknown environment exploration and construct an independent phototatic operant conditioning model used for hexapod robot. Aim at the problem of the overflow of probability and the sum of all probability not equal to one, the learning mechanism has been ameliorative and the improved learning mechanism also been proved that the sum of all probability influenced by it equal to 1. Result of the emulation experiment enunciate: According to the improved operant conditioning automata, The hexapod robot learn independent phototatic behavior and have capability of independent learning. This paper also apply learning algorithm to hexapod robot physical object. Result of independent phototatic experiment show that the hexapod robot which base on improved operant conditioning automata have independent phototatic ability.

Keyword:

Hexapod robot Operant conditioning Bionic learning Learning automata Unknown environment exploration

Author Community:

  • [ 1 ] [Yu Jianjun]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100124, Peoples R China
  • [ 2 ] [Zhou Lu]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100124, Peoples R China
  • [ 3 ] [Du Hongwei]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100124, Peoples R China
  • [ 4 ] [Wang Guanwei]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100124, Peoples R China

Reprint Author's Address:

  • [Yu Jianjun]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100124, Peoples R China

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Source :

2013 25TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC)

ISSN: 1948-9439

Year: 2013

Page: 4410-4415

Language: Chinese

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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