A novel cellular neural network and its applications in motion planning

Yan Cao, Feng Zhang, Xuewu Wu, Sheng Lu, Yi Li, Lei Sun, Shuai Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

A Novel Cellular Neural Network (CNN) entitled the shortest path CNN (SP-CNN) is proposed in this paper. Compared with general CNN, it is distinguished in the network structure and neural dynamics. As a result of these distinctions, SP-CNN has a good performance in motion planning for mobile robots. By mapping environment information to parameters in this neural network, motion planning can be transformed to the state evolvement of SP-CNN and the generated state represents information of the optimal path. The proposed method generates the best solution in static environments in real time. Extensive simulations about the above mentioned aspects demonstrate the effectiveness of the proposed approach.
Original languageEnglish
Title of host publicationAdvances in Neural Network Research and Applications
Pages265-273
Number of pages9
DOIs
Publication statusPublished - 1 Dec 2010
Externally publishedYes
Event7th International Symposium on Neural Networks, ISNN 2010 - Shanghai, China
Duration: 6 Jun 20109 Jun 2010

Publication series

NameLecture Notes in Electrical Engineering
Volume67 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference7th International Symposium on Neural Networks, ISNN 2010
CountryChina
CityShanghai
Period6/06/109/06/10

Keywords

  • CNN
  • Mobile robot
  • Motion planning
  • SP-CNN

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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