• Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
搜索

Author:

Dai, Li-Zhen (Dai, Li-Zhen.) | Yang, Gang (Yang, Gang.) | Ruan, Xiao-Gang (Ruan, Xiao-Gang.)

Indexed by:

EI Scopus PKU CSCD

Abstract:

Since the gradual learning process like humans or animals of two-wheeled robot cannot be realized by the traditional control methods, an autonomous operant conditioning automaton (AOCA) is established based on Skinner's theory of operant conditioning for self-balance learning control of robots. A bionic learning algorithm based on AOCA is proposed to balance the two-wheeled robot. The corresponding simulation experiments for self-balance learning control of the two wheeled robot are given, in which the robot effectively realizes autonomous balance. Theoretical analysis and simulation show that the autonomous operant conditioning automata bionic learning model applied to the two-wheeled robot for autonomous balance learning control makes the robot progressive formation of self-organization, development and improvement of its balance. Copyright © 2014 Acta Automatica Sinica. All rights reserved.

Keyword:

Automata theory Robots Learning algorithms Bionics Learning systems

Author Community:

  • [ 1 ] [Dai, Li-Zhen]School of Electrical and Electronic Engineering, East China Jiaotong University, Nanchang ; 330013, China
  • [ 2 ] [Yang, Gang]School of Electrical and Electronic Engineering, East China Jiaotong University, Nanchang ; 330013, China
  • [ 3 ] [Ruan, Xiao-Gang]Institute of Artificial Intelligence and Robots, College of Electronic and Control Engineering, Beijing University of Technology, Beijing ; 100124, China

Reprint Author's Address:

  • [yang, gang]school of electrical and electronic engineering, east china jiaotong university, nanchang ; 330013, china

Email:

Show more details

Related Keywords:

Source :

Acta Automatica Sinica

ISSN: 0254-4156

Year: 2014

Issue: 9

Volume: 40

Page: 1951-1957

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

Online/Total:521/10583357
Address:BJUT Library(100 Pingleyuan,Chaoyang District,Beijing 100124, China Post Code:100124) Contact Us:010-67392185
Copyright:BJUT Library Technical Support:Beijing Aegean Software Co., Ltd.