Abstract
Motional stability and robustness play a very important role mainly in bipedal robots, especially if it is connected with a dynamic environment, where many motion changes are necessary to be done. Here, this problem is shown on kicking a ball in robotic soccer. The movement control leads to constructing movement trajectories which should secure stable behaviour. Some control approaches are oriented in creating smooth trajectories instead of complicated stability analyses. For such purposes the so-called Bézier curves are used. In this paper we use Fuzzy Cognitive Maps (FCMs) for determining parameters of Bézier curves as well as a Particle Swarm Optimization (PSO) algorithm for learning FCMs. The main advantages of PSO consist in their speed and necessity of a relatively small training set. Two types of a kicking system for generating smooth movement trajectories are proposed and compared in the paper, which is documented by performed experiments.
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Vaščák, J., Michna, R. (2015). Learning of Fuzzy Cognitive Maps by a PSO Algorithm for Movement Adjustment of Robots. In: Sinčák, P., Hartono, P., Virčíková, M., Vaščák, J., Jakša, R. (eds) Emergent Trends in Robotics and Intelligent Systems. Advances in Intelligent Systems and Computing, vol 316. Springer, Cham. https://doi.org/10.1007/978-3-319-10783-7_17
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DOI: https://doi.org/10.1007/978-3-319-10783-7_17
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10782-0
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