NDLI: Realization of path planning for mobile robots based upon s-adaptive genetic algorithm

Content Provider	IEEE Xplore Digital Library
Author	Lin-lin Xia Gui-juan Miao Jiang Jiang Zhuo Wang
Copyright Year	2010
Description	Author affiliation: School of Automation Engineering, Northeast Dianli University, Jilin, 132012, China (Lin-lin Xia; Gui-juan Miao; Jiang Jiang; Zhuo Wang)
Abstract	Genetic algorithm (GA) is widely applied to optimal path planning of mobile robots. In this work, an adaptive genetic algorithm (AGA) is proposed, which is expected to solve some difficulties that conventional GA inevitably faces, including local optimum in the early stage, too lower convergence speed, and large complicated computation process. Sine-AGA denotes that the cross probability and mutation probability could realize the adaptive adjustments by conforming to a set of sine functions, guaranteeing to achieve a preservation scheme for optimal individuals. The whole iterative process consists of path coding, choices of fitness function, design of reproduction, crossover and mutation operations, and the setting of initial parameters of AGA. Simulation under the same condition indicates that the convergence performances of average solution and optimal solution are highly enhanced, better than the ones obtained through the pure AGA scheme, and the convergence speed is proved to be increased as expected.
Starting Page	3518
Ending Page	3522
File Size	248071
Page Count	5
File Format	PDF
ISBN	9781424459582
e-ISBN	9781424459612
DOI	10.1109/ICNC.2010.5584086
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Adaptation model Sine adaptive function Numerical simulation Path planning Encoding GA mutation probability path planning cross probability Mobile robots Convergence
Content Type	Text
Resource Type	Article

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