Abstract
This work uses the metaheuristic Bat Algorithm, and the main reason for its use is its speed of convergence, giving us the advantage of solving problems of optimization in a short time in comparison with other metaheuristic. We apply the Bat Algorithm in optimizing the trajectory of a unicycle mobile robot, which is the model considered in this work based on two wheels mounted on the same axis and a front wheel and the algorithm is responsible for building the best Type-1 fuzzy system once selected the best applied to the mobile robot model with the objective of following an established path with the least margin of error.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Amador-Angulo, L., Castillo, O.: Comparative analysis of designing different types of membership functions using bee colony optimization in the stabilization of fuzzy controllers. In: Nature-Inspired Design of Hybrid Intelligent Systems, pp. 551–571 (2017)
Amador-Angulo, L., Castillo, O.: A fuzzy bee colony optimization algorithm using an interval type-2 fuzzy logic system for trajectory control of a mobile robot. In: MICAI, pp. 460–471 (2015)
Amador-Angulo, L., Castillo, O., Castro, J.R., Garcia-Valdez, M.: A comparative study of type-1 fuzzy logic systems, interval type-2 fuzzy logic systems and generalized type-2 fuzzy logic systems in control problems. Inf. Sci. 354, 257–274 (2016)
Amador-Angulo, L., Castillo, O.: Statistical analysis of type-1 and interval type-2 fuzzy logic in dynamic parameter adaptation of the BCO. In: IFSA-EUSFLAT (2015)
Behrouz, S., Bahareh, B., Parisa, G.: Fault detection in nonlinear systems based on type-2 fuzzy sets and bat optimization algorithm. J. Intell. Fuzzy Syst. 28(1), 179–187 (2015)
MartÃnez-Soto, R., Castillo, O., Aguilar, L.T.: Optimization of interval type-2 fuzzy logic controllers for a perturbed autonomous wheeled mobile robot using genetic algorithms. Inf. Sci. 179(13), 2158–2174 (2009)
MartÃnez-Soto, R., Castillo, O., Soria, J.: Particle swarm optimization applied to the design of type-1 and type-2 fuzzy controllers for an autonomous mobile robot. In: Bio-inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition, pp. 247–262 (2009)
Olivas, F., Valdez, F., Castillo, O., González, C.I., Martinez, G.E., Melin, P.: Ant colony optimization with dynamic parameter adaptation based on interval type-2 fuzzy logic systems. Appl. Soft Comput. 53, 74–87 (2017)
Perez, J., Valdez, F., Castillo, O.: A new bat algorithm augmentation using fuzzy logic for dynamical parameter adaptation. In: Mexican International Conference on Artificial Intelligence, MICAI-2015, pp. 433–442 (2015)
Pérez, J., Valdez, F., Castillo, O.: Bat algorithm comparison with genetic algorithm using benchmark functions. In: Recent Advances on Hybrid Approaches for Designing Intelligent Systems, pp. 225–237. Springer, Heidelberg (2014)
Perez, J., Valdez, F., Castillo, O.: Modification of the bat algorithm using fuzzy logic for dynamic parameter adaptation. In: IEEE Congress on Evolutionary computation, CEC2015, Sendai, Japan, May 2015
Perez, J., Valdez, F., Castillo, O.: Modification of the bat algorithm using fuzzy logic for dynamical parameter adaptation. In: IEEE Congress on Evolutionary Computation (CEC 2015), pp. 464–471 (2015)
Perez, J., Valdez, F., Castillo, O.: Modification of the bat algorithm using type-2 fuzzy logic for dynamical parameter adaptation. In: Nature-Inspired Design of Hybrid Intelligent Systems, vol. 667, pp. 385–400, December 2016
Perez, J., Valdez, F., Castillo, O., Roeva, O.: Bat algorithm with parameter adaptation using interval type-2 fuzzy logic for benchmark mathematical functions. In: Proceedings of 8th International IEEE Conference on Intelligent Systems, pp. 120–127, November 2016
Roeva, O., Perez, J., Valdez, F., Castillo, O.: InterCriteria analysis of bat algorithm with parameter adaptation using type-1 and interval type-2 fuzzy systems. In: 20th International Conference on Intuitionistic Fuzzy Sets, vol. 22, no. 3, pp. 91–105, September 2016
Yang, X.-S.: A new metaheuristic bat-inspired algorithm. In: Nature Inspired Cooperative Strategies for Optimization (NISCO 2010), pp. 67–74 (2010)
Yang, X.-S.: Bat Algorithm for multi-objective optimization. Int. J. Bio-Inspired Comput. 3(5), 267–274 (2010)
Yang X.-S.: BAT algorithm. In: Nature-Inspired Metaheuristic Algorithms, pp. 97–104. Luniver Press, United Kingdom (2010)
Yang, X.-S.: Bat algorithm: literature review and applications. J. Bio-Inspired Comput. 5, 141–149 (2013)
Yang, X.-S., Jamil, M.: A literature survey of benchmark functions for global optimization problems. Int. J. Math. Modell. Numer. Optim. 4(2), 150–194 (2013)
Yang, X.-S.: Nature-Inspired Optimization Algorithm. Middlesex University London, Elsevier, London (2014)
Yılmaz, S., Kücüksille, E.U.: A new modification approach on bat algorithm for solving optimization problems. Appl. Soft Comput. 28, 259–275 (2015)
Acknowledgment
We would like to express our gratitude to the CONACYT and Tijuana Institute of Technology for the facilities and resources granted for the development of this research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Perez, J., Melin, P., Castillo, O., Valdez, F., Gonzalez, C., Martinez, G. (2018). Trajectory Optimization for an Autonomous Mobile Robot Using the Bat Algorithm. In: Melin, P., Castillo, O., Kacprzyk, J., Reformat, M., Melek, W. (eds) Fuzzy Logic in Intelligent System Design. NAFIPS 2017. Advances in Intelligent Systems and Computing, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-319-67137-6_25
Download citation
DOI: https://doi.org/10.1007/978-3-319-67137-6_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-67136-9
Online ISBN: 978-3-319-67137-6
eBook Packages: EngineeringEngineering (R0)