A genetic algorithm with local map for path planning in dynamic environments

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A genetic algorithm with local map for path planning in dynamic environments

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Genetic And Evolutionary Computation Conference archive
Proceedings of the 11th Annual conference on Genetic and evolutionary computation table of contents

Montreal, Québec, Canada

POSTER SESSION: Track 9: genetic algorithms table of contents

Pages 1859-1860

Year of Publication: 2009

ISBN:978-1-60558-325-9

Authors

Ivan Koryakovskiy	Seoul National University, Seoul, South Korea
Nguyen Xuan Hoai	Seoul National University, Seoul, South Korea
Kyoung Mu Lee	Seoul National University, Seoul, South Korea

Sponsors

SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery

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ACM New York, NY, USA

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ABSTRACT

In this paper, a new genetic algorithm (GA) for solving the path planning in dynamic environments is proposed. The new genetic algorithm uses local maps, therefore, does not require the knowledge of exact or estimated position of the destination point as other approaches in the literature. Consequently, the new GA could be used to solve the problem of dynamic path planning under an assumption that makes the problem more restrictive but more close to reality (in searching tasks).

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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