NDLI: Global path planning for autonomous robot navigation using hybrid metaheuristic GA-PSO algorithm

Content Provider	IEEE Xplore Digital Library
Author	Hsu-Chih Huang Ching-Chih Tsai
Copyright Year	2011
Description	Author affiliation: Department of Electrical Engineering, National Chung Hsing University, Taiwan (Ching-Chih Tsai) \|\| Department of Computer Science and Information Enginnering, Hungkuang University, Taiwan (Hsu-Chih Huang)
Abstract	This paper presents a hybrid metaheuristic GA (genetic algorithm)-PSO (particle swarm optimization) algorithm for autonomous robot navigation to find an optimal path between a starting and ending point in a grid environment. GA has been combined with PSO in evolving new solutions by applying crossover and mutation operators on solutions constructed by particles. This hybrid algorithm avoids the premature convergence and time complexity in conventional GA and PSO algorithms. The initial feasible path generated from the hybrid GA-PSO planner is then smoothed using the cubic B-spline technique, in order to construct a near-optimal collision-free continuous path. Simulation results are conducted to show the merit of the proposed hybrid GA-PSO path planner and smoother for global path planning of autonomous robot navigation.
Starting Page	1338
Ending Page	1343
File Size	1101906
Page Count	6
File Format	PDF
ISBN	9781457707148
e-ISBN	9784907764395
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-13
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	SICE (The Society of Instrument and Cont
Subject Keyword	Path planning Spline Robots Navigation Genetic algorithms Biological cells Collision avoidance particle swarm optimization genetic algorithm global path planning autonomous robot navigation
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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