Design of path planning based cellular neural network

Yan Cao; Xiaolan Zhou; Shuai Li; Feng Zhang; Xinwei Wu; Aomei Li; Lei Sun

doi:10.1109/WCICA.2010.5554403

Design of path planning based cellular neural network

Yan Cao, Xiaolan Zhou, Shuai Li, Feng Zhang, Xinwei Wu, Aomei Li, Lei Sun

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

6 Citations (Scopus)

Abstract

In this paper, a Novel Cellular Neural Network (CNN) entitled the shortest path CNN (SP-CNN) is proposed. It has a good performance in path planning for mobile robots because of its network structure and neural dynamics. The proposed method not only can generate the best solution in static environments in real time but also generate the optional solution in dynamic environments or in unknown environments according to its currently acquired navigation map. Extensive simulations about the above mentioned aspects demonstrate the effectiveness of the proposed approach.

Original language	English
Title of host publication	2010 8th World Congress on Intelligent Control and Automation, WCICA 2010
Pages	6539-6544
Number of pages	6
DOIs	https://doi.org/10.1109/WCICA.2010.5554403
Publication status	Published - 27 Oct 2010
Externally published	Yes
Event	2010 8th World Congress on Intelligent Control and Automation, WCICA 2010 - Jinan, China Duration: 7 Jul 2010 → 9 Jul 2010

Conference

Conference	2010 8th World Congress on Intelligent Control and Automation, WCICA 2010
Country/Territory	China
City	Jinan
Period	7/07/10 → 9/07/10

Keywords

Dynamic environment
Mobile robot
Path planning
SP-CNN

ASJC Scopus subject areas

Control and Systems Engineering
Software
Computer Science Applications

More information

10.1109/WCICA.2010.5554403

Cite this

@inproceedings{737a8689190942b381b9315304396b44,

title = "Design of path planning based cellular neural network",

abstract = "In this paper, a Novel Cellular Neural Network (CNN) entitled the shortest path CNN (SP-CNN) is proposed. It has a good performance in path planning for mobile robots because of its network structure and neural dynamics. The proposed method not only can generate the best solution in static environments in real time but also generate the optional solution in dynamic environments or in unknown environments according to its currently acquired navigation map. Extensive simulations about the above mentioned aspects demonstrate the effectiveness of the proposed approach.",

keywords = "Dynamic environment, Mobile robot, Path planning, SP-CNN",

author = "Yan Cao and Xiaolan Zhou and Shuai Li and Feng Zhang and Xinwei Wu and Aomei Li and Lei Sun",

year = "2010",

month = oct,

day = "27",

doi = "10.1109/WCICA.2010.5554403",

language = "English",

isbn = "9781424467129",

pages = "6539--6544",

booktitle = "2010 8th World Congress on Intelligent Control and Automation, WCICA 2010",

note = "2010 8th World Congress on Intelligent Control and Automation, WCICA 2010 ; Conference date: 07-07-2010 Through 09-07-2010",

}

TY - GEN

T1 - Design of path planning based cellular neural network

AU - Cao, Yan

AU - Zhou, Xiaolan

AU - Li, Shuai

AU - Zhang, Feng

AU - Wu, Xinwei

AU - Li, Aomei

AU - Sun, Lei

PY - 2010/10/27

Y1 - 2010/10/27

N2 - In this paper, a Novel Cellular Neural Network (CNN) entitled the shortest path CNN (SP-CNN) is proposed. It has a good performance in path planning for mobile robots because of its network structure and neural dynamics. The proposed method not only can generate the best solution in static environments in real time but also generate the optional solution in dynamic environments or in unknown environments according to its currently acquired navigation map. Extensive simulations about the above mentioned aspects demonstrate the effectiveness of the proposed approach.

AB - In this paper, a Novel Cellular Neural Network (CNN) entitled the shortest path CNN (SP-CNN) is proposed. It has a good performance in path planning for mobile robots because of its network structure and neural dynamics. The proposed method not only can generate the best solution in static environments in real time but also generate the optional solution in dynamic environments or in unknown environments according to its currently acquired navigation map. Extensive simulations about the above mentioned aspects demonstrate the effectiveness of the proposed approach.

KW - Dynamic environment

KW - Mobile robot

KW - Path planning

KW - SP-CNN

UR - http://www.scopus.com/inward/record.url?scp=77958145661&partnerID=8YFLogxK

U2 - 10.1109/WCICA.2010.5554403

DO - 10.1109/WCICA.2010.5554403

M3 - Conference article published in proceeding or book

SN - 9781424467129

SP - 6539

EP - 6544

BT - 2010 8th World Congress on Intelligent Control and Automation, WCICA 2010

T2 - 2010 8th World Congress on Intelligent Control and Automation, WCICA 2010

Y2 - 7 July 2010 through 9 July 2010

ER -

Design of path planning based cellular neural network

Abstract

Conference

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this