Path planning for robot navigation based on Cooperative Genetic Optimization

Chen Chien Hsu; Yi Chun Liu

doi:10.1109/ICNSC.2014.6819645

Path planning for robot navigation based on Cooperative Genetic Optimization

Chen Chien Hsu, Yi Chun Liu

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Citations (Scopus)

Abstract

Path planning investigates issues including the shortest path, obstacle avoidance, and computation efficiency, which can be regarded as an optimal problem. Taking advantage of the genetic algorithms to solve various optimal problems, this paper first proposes a Cooperative Genetic Optimization (CGO) Algorithm, including the establishment of an elite policy and larger selection region to minimize the occurrence of local optima so as to increase the speed of convergence. Based on the proposed CGO, a global path planning approach for robots is then presented. As a result, the proposed method of this paper leads to a better performance in comparison with the traditional Genetic algorithm to achieve the goal of obtaining a safer and shorter path.

Original language	English
Title of host publication	Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014
Publisher	IEEE Computer Society
Pages	316-321
Number of pages	6
ISBN (Print)	9781479931064
DOIs	https://doi.org/10.1109/ICNSC.2014.6819645
Publication status	Published - 2014
Event	11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014 - Miami, FL, United States Duration: 2014 Apr 7 → 2014 Apr 9

Publication series

Name	Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014

Other

Other	11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014
Country/Territory	United States
City	Miami, FL
Period	2014/04/07 → 2014/04/09

Keywords

genetic algorithm
path planning
robots

ASJC Scopus subject areas

Computer Networks and Communications
Control and Systems Engineering

Access to Document

10.1109/ICNSC.2014.6819645

Cite this

Hsu, C. C., & Liu, Y. C. (2014). Path planning for robot navigation based on Cooperative Genetic Optimization. In Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014 (pp. 316-321). Article 6819645 (Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014). IEEE Computer Society. https://doi.org/10.1109/ICNSC.2014.6819645

Path planning for robot navigation based on Cooperative Genetic Optimization. / Hsu, Chen Chien; Liu, Yi Chun.
Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014. IEEE Computer Society, 2014. p. 316-321 6819645 (Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hsu, CC & Liu, YC 2014, Path planning for robot navigation based on Cooperative Genetic Optimization. in Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014., 6819645, Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014, IEEE Computer Society, pp. 316-321, 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014, Miami, FL, United States, 2014/04/07. https://doi.org/10.1109/ICNSC.2014.6819645

Hsu CC, Liu YC. Path planning for robot navigation based on Cooperative Genetic Optimization. In Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014. IEEE Computer Society. 2014. p. 316-321. 6819645. (Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014). doi: 10.1109/ICNSC.2014.6819645

@inproceedings{68c8551a268f43748d47cba119974e8a,

title = "Path planning for robot navigation based on Cooperative Genetic Optimization",

abstract = "Path planning investigates issues including the shortest path, obstacle avoidance, and computation efficiency, which can be regarded as an optimal problem. Taking advantage of the genetic algorithms to solve various optimal problems, this paper first proposes a Cooperative Genetic Optimization (CGO) Algorithm, including the establishment of an elite policy and larger selection region to minimize the occurrence of local optima so as to increase the speed of convergence. Based on the proposed CGO, a global path planning approach for robots is then presented. As a result, the proposed method of this paper leads to a better performance in comparison with the traditional Genetic algorithm to achieve the goal of obtaining a safer and shorter path.",

keywords = "genetic algorithm, path planning, robots",

author = "Hsu, {Chen Chien} and Liu, {Yi Chun}",

year = "2014",

doi = "10.1109/ICNSC.2014.6819645",

language = "English",

isbn = "9781479931064",

series = "Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014",

publisher = "IEEE Computer Society",

pages = "316--321",

booktitle = "Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014",

note = "11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014 ; Conference date: 07-04-2014 Through 09-04-2014",

}

TY - GEN

T1 - Path planning for robot navigation based on Cooperative Genetic Optimization

AU - Hsu, Chen Chien

AU - Liu, Yi Chun

PY - 2014

Y1 - 2014

N2 - Path planning investigates issues including the shortest path, obstacle avoidance, and computation efficiency, which can be regarded as an optimal problem. Taking advantage of the genetic algorithms to solve various optimal problems, this paper first proposes a Cooperative Genetic Optimization (CGO) Algorithm, including the establishment of an elite policy and larger selection region to minimize the occurrence of local optima so as to increase the speed of convergence. Based on the proposed CGO, a global path planning approach for robots is then presented. As a result, the proposed method of this paper leads to a better performance in comparison with the traditional Genetic algorithm to achieve the goal of obtaining a safer and shorter path.

AB - Path planning investigates issues including the shortest path, obstacle avoidance, and computation efficiency, which can be regarded as an optimal problem. Taking advantage of the genetic algorithms to solve various optimal problems, this paper first proposes a Cooperative Genetic Optimization (CGO) Algorithm, including the establishment of an elite policy and larger selection region to minimize the occurrence of local optima so as to increase the speed of convergence. Based on the proposed CGO, a global path planning approach for robots is then presented. As a result, the proposed method of this paper leads to a better performance in comparison with the traditional Genetic algorithm to achieve the goal of obtaining a safer and shorter path.

KW - genetic algorithm

KW - path planning

KW - robots

UR - http://www.scopus.com/inward/record.url?scp=84902478992&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84902478992&partnerID=8YFLogxK

U2 - 10.1109/ICNSC.2014.6819645

DO - 10.1109/ICNSC.2014.6819645

M3 - Conference contribution

AN - SCOPUS:84902478992

SN - 9781479931064

T3 - Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014

SP - 316

EP - 321

BT - Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014

PB - IEEE Computer Society

T2 - 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014

Y2 - 7 April 2014 through 9 April 2014

ER -

Path planning for robot navigation based on Cooperative Genetic Optimization

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this