Task Allocation of Multi-Robot Systems Based on a Novel Explosive Immune Evolutionary Algorithm

Ming Xin Yuan; Ya Feng Jiang; Yi Shen; Zhao Li Ye; Qi Wang

doi:10.4028/www.scientific.net/AMM.246-247.331

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 246-247Task Allocation of Multi-Robot Systems Based on a...

Task Allocation of Multi-Robot Systems Based on a Novel Explosive Immune Evolutionary Algorithm

Abstract:

To solve the task allocation of multi-robot systems, a novel explosive evolution - based immune genetic algorithm (EIGA) is presented. On the basis of the immune genetic algorithm (IGA), the population number of EIGA is increased quickly through explosive evolutionary mode, and then the better individuals are selected through the comparison of allelic genes, which can improve the population quality with the premise of ensuring the population diversity, and enhance the search speed and search precision of EIGA. Compared with the IGA and genetic algorithm (GA), the simulation results indicate that the proposed EIGA is characterized by quick convergence speed, high optimization precision and good stability, and the tasks are allocated rationally and scientifi-cally which realizes the task cooperation of multi-robot systems well.

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Periodical:

Applied Mechanics and Materials (Volumes 246-247)

Pages:

331-335

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.246-247.331

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Online since:

December 2012

Authors:

Ming Xin Yuan, Ya Feng Jiang, Yi Shen, Zhao Li Ye, Qi Wang

Keywords:

Explosive Evolution, Immune Genetic Algorithm, Multi-Robot Systems, Task Allocation

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