DocumentCode
265953
Title
Probabilistic roadmaps and hierarchical genetic algorithms for optimal motion planning
Author
Lakhdari, Abdallah ; Achour, Nouara
Author_Institution
LRPE Lab., USTHB Univ., Algiers, Algeria
fYear
2014
fDate
27-29 Aug. 2014
Firstpage
221
Lastpage
225
Abstract
In this paper we present a motion planning algorithm that combines between Probabilistic Roadmaps (PRM) and Hierarchical Genetic Algorithms (HGA) in order to generate optimal motions for a non holonomic mobile robot. PRM are used to generate a set of paths that will be optimized by HGA, the obtained trajectory leads a non holonomic mobile robot from an initial to a final configuration while maintaining feasibility and no-collision with obstacles.
Keywords
genetic algorithms; mobile robots; path planning; probability; HGA; PRM; hierarchical genetic algorithms; motion planning algorithm; nonholonomic mobile robot; obstacle avoidance; optimal motion planning; probabilistic roadmaps; Biological cells; Genetic algorithms; Mobile robots; Optimization; Planning; Trajectory; PRM; Path planning; hierarchical genetic algorithms; robotics;
fLanguage
English
Publisher
ieee
Conference_Titel
Science and Information Conference (SAI), 2014
Conference_Location
London
Print_ISBN
978-0-9893-1933-1
Type
conf
DOI
10.1109/SAI.2014.6918193
Filename
6918193
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