In this paper, we address the problem of efficient allocation of the navigational goals in the multi-robot exploration of unknown environment. Goal candidate locations are repeatedly determined during the exploration. Then, the assignment of the candidates to the robots is solved as the task-allocation problem. A more frequent decision-making may improve performance of the exploration, but in a practical deployment of the exploration strategies, the frequency depends on the computational complexity of the task-allocation algorithm and available computational resources. Therefore, we propose an evaluation framework to study exploration strategies independently on the available computational resources and we report a comparison of the selected task-allocation algorithms deployed in multi-robot exploration.
CITATION STYLE
Faigl, J., Simonin, O., & Charpillet, F. (2015). Comparison of task-allocation algorithms in frontier-based multi-robot exploration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8953, pp. 101–110). Springer Verlag. https://doi.org/10.1007/978-3-319-17130-2_7
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