Empirical study of Q-learning based elemental hose transport control

Authors:
Jose Manuel Lopez-Guede;Borja Fernandez-Gauna;Manuel Graña;Ekaitz Zulueta
Affiliations:
Grupo de Inteligencia Computacional, Universidad del Pais Vasco;Grupo de Inteligencia Computacional, Universidad del Pais Vasco;Grupo de Inteligencia Computacional, Universidad del Pais Vasco;-
Venue:
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
Year:
2011

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Abstract

Non-rigid physical elements attached to robotic systems introduce non-linear dynamics that requires innovative control approaches. This paper describes some of our results applying Q-Learning to learn the control commands to solve a hose transportation problem. The learning process is developed in a simulated environment. Computationally expensive but dynamically accurate Geometrically Exact Dynamic Splines (GEDS) have been used to model the hose to be transported by a single robot, showing the difficulties of controlling flexible elastic passive linking elements.