Abstract
In this work we show how a simple anti-pheromone ant foraging based algorithm can be effective in urban navigation by reducing exploration times. We use a distributed multi agent architecture to test this algorithm. Swarm collaboration is analysed for different scenarios with varying number of units and map complexity. We show how an increase in the number of robots results in smaller exploration times. Also, we measure how the complexity of the map topology affects the navigability. We validate our approach through numerical tests with both synthetic random generated maps and real bicycle routes in four cities. Also, by monitoring the dynamics of three real prototypes built at the laboratory, we check both the feasibility of our approach and the robustness of the algorithm.
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This work has been partially supported by the Junta of Castile and Leon (Spain) through the Moviurban project SA070U 16.
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García, R.M., Prieto-Castrillo, F., González, G.V., Bajo, J. (2017). Electric Vehicle Urban Exploration by Anti-pheromone Swarm Based Algorithms. In: De Paz, J., Julián, V., Villarrubia, G., Marreiros, G., Novais, P. (eds) Ambient Intelligence– Software and Applications – 8th International Symposium on Ambient Intelligence (ISAmI 2017). ISAmI 2017. Advances in Intelligent Systems and Computing, vol 615. Springer, Cham. https://doi.org/10.1007/978-3-319-61118-1_17
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DOI: https://doi.org/10.1007/978-3-319-61118-1_17
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