IEEE.org| IEEE Xplore Digital Library| IEEE Standards| IEEE Spectrum| More Sites

Cart (Loading....) | Create Account | 

Close category search window
Author Searchbeta |  Advanced Search  |  Preferences |  Search Tips  |  More Search Options  
 
Browse Conference Publications > Intelligent Systems Design an ... Help

An Improved Genetic Algorithm of Optimum Path Planning for Mobile Robots

Full Text Sign-In or Purchase

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing! close button
puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Qing Li ; Sch. of Inf. Eng., Univ. of Sci. & Technol., Beijing ; Wei Zhang ; Yixin Yin ; Zhiliang Wang
more authors

An improved genetic algorithm of optimum path planning for mobile robots is proposed in this paper. An obstacle avoidance algorithm is introduced to generate the initial population in order to improve the path planning efficiency. Domain heuristic knowledge based crossover, mutation, refinement and deletion operators are specifically designed to fit path planning for mobile robots. Furthermore, a fuzzy logic control algorithm is integrated to self-adaptively adjust the probabilities of crossover and mutation in the genetic algorithm. Simulation studies for both static and dynamic environments are carried out, and the simulation results show that the proposed genetic algorithm exhibits improved search speed, high search quality and enhanced self adaptability

Published in:
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on  (Volume:2 )

Date of Conference: 16-18 Oct. 2006

Page(s):
637 - 642
Print ISBN:
0-7695-2528-8
INSPEC Accession Number:
9275201
Conference Location :
Jinan
Digital Object Identifier :
10.1109/ISDA.2006.253911
Product Type:
Conference Publications

IEEE Account

Purchase Details

Profile Information

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.