Abstract
In this chapter we describe the methodology to design an optimized fuzzy logic controller for an autonomous mobile robot, using Ant Colony Optimization (ACO). This is achieved by applying a systematic and hierarchical optimization modifying the conventional ACO algorithm using ants partition. The simulations results proved that the proposed algorithm performs even better that the classic ACO algorithm when optimizing membership functions of FLC, parameters and fuzzy rules.
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Lizarraga, E., Castillo, O., Soria, J., Valdez, F. (2014). A Fuzzy Control Design for an Autonomous Mobile Robot Using Ant Colony Optimization. In: Castillo, O., Melin, P., Pedrycz, W., Kacprzyk, J. (eds) Recent Advances on Hybrid Approaches for Designing Intelligent Systems. Studies in Computational Intelligence, vol 547. Springer, Cham. https://doi.org/10.1007/978-3-319-05170-3_20
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