Abstract
The paper presents an Evolutionary Algorithm (EA) based framework capable of handling a variety of complex Multi-Robot Task Allocation (MRTA) problems. Equipped with a flexible chromosome structure, customized variation operators, and a penalty function, the EA demonstrates the capability to switch between single-robot and multi-robot cases of MRTA and entertains team heterogeneity. The framework is validated and compared against a Genetic Algorithm based representation and a heuristic-based solution. The experimental results show that the presented EA provides better overall results to the task allocation problem with faster convergence and lesser chances of sub-optimal results.
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CITATION STYLE
Arif, M. U., & Haider, S. (2018). A flexible evolutionary algorithm for task allocation in multi-robot team. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11056 LNAI, pp. 89–99). Springer Verlag. https://doi.org/10.1007/978-3-319-98446-9_9
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