Parallel Elite Genetic Algorithm and Its Application to Global Path Planning for Autonomous Robot Navigation

This paper presents a parallel elite genetic algorithm (PEGA) and its application to global path planning for autonomous mobile robots navigating in structured environments. This PEGA, consisting of two parallel EGAs along with a migration operator, takes advantages of maintaining better population...

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Published in:	IEEE transactions on industrial electronics (1982) Vol. 58; no. 10; pp. 4813 - 4821
Main Authors:	Tsai, Ching-Chih, Huang, Hsu-Chih, Chan, Cheng-Kai
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.10.2011 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Autonomous Elite genetic algorithm Genetic algorithms global path planning Hardware Migration mobile robot Mobile robots Natural gas Navigation Parallel processing Path planning Robots Studies
ISSN:	0278-0046, 1557-9948
Online Access:	Get full text
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Abstract	This paper presents a parallel elite genetic algorithm (PEGA) and its application to global path planning for autonomous mobile robots navigating in structured environments. This PEGA, consisting of two parallel EGAs along with a migration operator, takes advantages of maintaining better population diversity, inhibiting premature convergence, and keeping parallelism in comparison with conventional GAs. This initial feasible path generated from the PEGA planner is then smoothed using the cubic B-spline technique, in order to construct a near-optimal collision-free continuous path. Both global path planner and smoother are implemented in one field-programmable gate array chip utilizing the system-on-a-programmable-chip technology and the pipelined hardware implementation scheme, thus significantly expediting computation speed. Simulations and experimental results are conducted to show the merit of the proposed PEGA path planner and smoother for global path planning of autonomous mobile robots.
AbstractList	This paper presents a parallel elite genetic algorithm (PEGA) and its application to global path planning for autonomous mobile robots navigating in structured environments. This PEGA, consisting of two parallel EGAs along with a migration operator, takes advantages of maintaining better population diversity, inhibiting premature convergence, and keeping parallelism in comparison with conventional GAs. This initial feasible path generated from the PEGA planner is then smoothed using the cubic B-spline technique, in order to construct a near-optimal collision-free continuous path. Both global path planner and smoother are implemented in one field-programmable gate array chip utilizing the system-on-a-programmable-chip technology and the pipelined hardware implementation scheme, thus significantly expediting computation speed. Simulations and experimental results are conducted to show the merit of the proposed PEGA path planner and smoother for global path planning of autonomous mobile robots.
Author	Ching-Chih Tsai Hsu-Chih Huang Cheng-Kai Chan
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SubjectTerms	Autonomous Elite genetic algorithm Genetic algorithms global path planning Hardware Migration mobile robot Mobile robots Natural gas Navigation Parallel processing Path planning Robots Studies
Title	Parallel Elite Genetic Algorithm and Its Application to Global Path Planning for Autonomous Robot Navigation
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