Plastic Representation of the Reachable Space for a Humanoid Robot
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Altres documents de l'autoria: Antonelli, Marco; Grzyb, Beata J.; Castelló, Vicente; del Pobil, Angel P.
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Mostra el registre complet de l'elementcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/61544
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Títol
Plastic Representation of the Reachable Space for a Humanoid RobotData de publicació
2012Editor
Springer Berlin HeidelbergISBN
978-3-642-33092-6ISSN
0302-9743; 1611-3349Cita bibliogràfica
Antonelli, Marco; Grzyb, Beata J.; Castelló, Vicente; Pobil, Angel P. " Plastic Representation of the Reachable Space for a Humanoid Robot". En: From Animals to Animats 12 – 12th International Conference on Simulation of Adaptive Behavior, SAB 2012, Odense, Denmark, August 27-30, 2012. Proceedings / Ziemke, Tom [et al.] (Eds.). Berlin : Springer, 2012. (Lecture Notes in Computer Science; 7426) . ISBN: 978-3-642-33092-6. pp. 167-176Tipus de document
info:eu-repo/semantics/bookPartVersió de l'editorial
http://link.springer.com/chapter/10.1007%2F978-3-642-33093-3_17Paraules clau / Matèries
Resum
Reaching a target object requires accurate estimation of the object spatial position and its further transformation into a suitable arm-motor command. In this paper, we propose a framework that provides a robot with ... [+]
Reaching a target object requires accurate estimation of the object spatial position and its further transformation into a suitable arm-motor command. In this paper, we propose a framework that provides a robot with a capacity to represent its reachable space in an adaptive way. The location of the target is represented implicitly by both the gaze direction and the angles of arm joints. Two paired neural networks are used to compute the direct and inverse transformations between the arm position and the head position. These networks allow reaching the target either through a ballistic movement or through visually-guided actions. Thanks to the latter skill, the robot can adapt its sensorimotor transformations so as to reflect changes in its body configuration. The proposed framework was implemented on the NAO humanoid robot, and our experimental results provide evidences for its adaptative capabilities. [-]
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