DocumentCode :
1653798
Title :
Multi-objective Immune Evolutionary Algorithms for SLAM
Author :
Meiyi, Li
Author_Institution :
Xiangtan Univ., Xiangtan
fYear :
2007
Firstpage :
216
Lastpage :
220
Abstract :
The simultaneous localization and mapping problem with evolutionary algorithms is translated to a multi-objective immune optimization problem since it inherently possesses of multi-objective characters, and in order to efficiently solve the simultaneous localization and mapping problem, a local searcher with immunity is constructed. The local searcher employs domain knowledge of the problem, which is named as a key point grid pulling that is developed in the paper. The experiment results of a real mobile robot indicate that the computational expensiveness of designed algorithms is less than other evolutionary algorithms of single-objection and multi-objective optimization problem without immunity for simultaneous localization and mapping and accuracy of obtained maps are higher.
Keywords :
SLAM (robots); artificial immune systems; evolutionary computation; SLAM; key point grid pulling; mobile robot; multi-objective optimization; multiobjective immune evolutionary algorithm; multiobjective immune optimization problem; simultaneous localization and mapping problem; single-objection optimization; Algorithm design and analysis; Buildings; Design optimization; Educational institutions; Electronic mail; Evolutionary computation; Mobile robots; Simultaneous localization and mapping; LAM; key point grid pulling; multi-objective immune evolutionary algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
Type :
conf
DOI :
10.1109/CHICC.2006.4347449
Filename :
4347449
Link To Document :
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