Comparison of Task-Allocation Algorithms in Frontier-Based Multi-robot Exploration

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.