Abstract : To be able to generate desired movements a robot needs to learn which motor commands move the limb from one position to another. We argue that learning by imitation might be an efficient way to acquire such a function, and investigate favorable properties of the movement used during training in order to maximize the control system's generalization capabilities. Our control system was trained to imitate one particular movement and then tested to see if it can imitate other movements without further training.
Type de document :
Communication dans un congrès
Max Bramer. Third IFIP TC12 International Conference on Artificial Intelligence (AI) / Held as Part of World Computer Congress (WCC), Sep 2010, Brisbane, Australia. Springer, IFIP Advances in Information and Communication Technology, AICT-331, pp.79-88, 2010, Artificial Intelligence in Theory and Practice III. 〈10.1007/978-3-642-15286-3_8〉
https://hal.inria.fr/hal-01054581
Contributeur : Hal Ifip
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Soumis le : jeudi 7 août 2014 - 15:33:49
Dernière modification le : vendredi 11 août 2017 - 11:17:19
Document(s) archivé(s) le : mercredi 26 novembre 2014 - 01:45:46
Rikke Amilde Lävlid. Learning Motor Control by Dancing YMCA. Max Bramer. Third IFIP TC12 International Conference on Artificial Intelligence (AI) / Held as Part of World Computer Congress (WCC), Sep 2010, Brisbane, Australia. Springer, IFIP Advances in Information and Communication Technology, AICT-331, pp.79-88, 2010, Artificial Intelligence in Theory and Practice III. 〈10.1007/978-3-642-15286-3_8〉. 〈hal-01054581〉
