Abstract
This paper analyzes and discusses the problem of optimizing the size of a team of robots for multi-robot exploration. We are concerned with the number of robots for a given exploration task that minimizes both exploration time and cost. Minimizing time means that the exploration should be done as fast as possible. Minimizing cost means that the number of robots and their energy consumption should be as low as possible. To solve this problem, we report in this paper, on a series of exploration simulations based on ROS and MORSE using a cluster of computers. The simulated code is exactly the same as that which would run on the actual robots. Such a simulation infrastructure is crucial to “quickly” execute experiments with different parameters such as the number of robots or their initial positions.
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Yan, Z., Fabresse, L., Laval, J., Bouraqadi, N. (2014). Team Size Optimization for Multi-robot Exploration. In: Brugali, D., Broenink, J.F., Kroeger, T., MacDonald, B.A. (eds) Simulation, Modeling, and Programming for Autonomous Robots. SIMPAR 2014. Lecture Notes in Computer Science(), vol 8810. Springer, Cham. https://doi.org/10.1007/978-3-319-11900-7_37
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DOI: https://doi.org/10.1007/978-3-319-11900-7_37
Publisher Name: Springer, Cham
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