Abstract
This paper deals with multi-objective optimization problems in ascending and descending gait planning of biped robot, which has been solved using particle swarm optimization algorithm and genetic algorithm separately. In order to model this problem, two modules of adaptive neuro-fuzzy inference systems have been adopted. Two contrasting objectives, such as power consumption and dynamic balance margin have been considered, and Pareto optimal front of solutions has been obtained.
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Rajendra, R., Pratihar, D.K. (2012). Particle Swarm Optimization Algorithm vs. Genetic Algorithm to Solve Multi-Objective Optimization Problem in Gait Planning of Biped Robot. In: Satapathy, S.C., Avadhani, P.S., Abraham, A. (eds) Proceedings of the International Conference on Information Systems Design and Intelligent Applications 2012 (INDIA 2012) held in Visakhapatnam, India, January 2012. Advances in Intelligent and Soft Computing, vol 132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27443-5_65
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DOI: https://doi.org/10.1007/978-3-642-27443-5_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27442-8
Online ISBN: 978-3-642-27443-5
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