TY - GEN
T1 - Generalization of the tacit learning controller based on periodic tuning functions
AU - Berenz, Vincent
AU - Hayashibe, Mitsuhiro
AU - Alnajjar, Fady
AU - Shimoda, Shingo
N1 - Funding Information:
The authors are grateful to A. S. Abou-Sayed, M. A. Addis, B. J. Carter, N. G. W. Cook, A. Chudnovsky, E. Detournay, W. Deeg, C. Fairhurst, A. N. Galybin, A. N. Mokhel, Giin-Fa Fuh, B. C. Haimson, A. R. Ingraffea, F. Mody, J. Neda, P. C. Papanastasiou, E. Papamichos, P. Peška, D. D. Pollard, L. M. Ring, D. W. Rhett, J.-C. Roegiers, H. M. R. Santos, R. L. Salganik, J. Shlyapobersky, D. P. Yale, L. Vernik, Z. Zheng and M. D. Zoback for useful discussions. The authors are especially grateful to D. W. Stearns, V. Dunayevsky, L. R. Myer and K. B. Ustinov for many comments that helped to considerably improve this paper. They would also like to acknowledge the courtesy of J. M. Cook and C. D. Martin who kindly sent the photographs shown in Fig. 1(a) and (b) , respectively. They appreciate very much E. Sahouryeh's generous suggestion to use the photograph shown in Fig. 5(c) prior to its publication in his paper written jointly with the authors [84] . The first author is thankful to the US National Science Foundation for supporting his work on this paper (Grants CMS-9896136 and OCE-9896021). The second author acknowledges the support of the Australian Research Council Small Grant (1996–1997) and the Large Grant A89801617 (1998–2000).
PY - 2014/9/30
Y1 - 2014/9/30
N2 - Living organisms are characterized by their smooth adaptability to environmental changes and their robustness against morphological modifications. To investigate the computational mechanisms behind such learning scheme, we proposed tacit learning as a novel learning method. In tacit learning, there are no clear distinctions between learning and motor control: learning is a simple accumulation process embedded in the controller. In previous work, tacit learning was applied with success to bipedal locomotion of a 36 DoF humanoid robot. In this paper, we generalize the structure of the controller such as applying adaptive integration to a wider range of systems and behaviors. This is achieved by applying the principle of tacit learning in a hierarchical fashion, in which the value of a virtual periodic dynamic variable is tuned for continuous adaptation. This resulting PD-PI (proportional-derivative periodic-integration) controller preserves the advantages of tacit learning that the controllers do not include any prior knowledge of the system in which they are embedded. It also shares with biological systems the property that control and adaptation progress without explicit distinction between them.
AB - Living organisms are characterized by their smooth adaptability to environmental changes and their robustness against morphological modifications. To investigate the computational mechanisms behind such learning scheme, we proposed tacit learning as a novel learning method. In tacit learning, there are no clear distinctions between learning and motor control: learning is a simple accumulation process embedded in the controller. In previous work, tacit learning was applied with success to bipedal locomotion of a 36 DoF humanoid robot. In this paper, we generalize the structure of the controller such as applying adaptive integration to a wider range of systems and behaviors. This is achieved by applying the principle of tacit learning in a hierarchical fashion, in which the value of a virtual periodic dynamic variable is tuned for continuous adaptation. This resulting PD-PI (proportional-derivative periodic-integration) controller preserves the advantages of tacit learning that the controllers do not include any prior knowledge of the system in which they are embedded. It also shares with biological systems the property that control and adaptation progress without explicit distinction between them.
UR - http://www.scopus.com/inward/record.url?scp=84918578474&partnerID=8YFLogxK
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U2 - 10.1109/biorob.2014.6913894
DO - 10.1109/biorob.2014.6913894
M3 - Conference contribution
AN - SCOPUS:84918578474
T3 - Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
SP - 893
EP - 898
BT - "2014 5th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2014
A2 - Carloni, Raffaella
A2 - Masia, Lorenzo
A2 - Sabater-Navarro, Jose Maria
A2 - Ackermann, Marko
A2 - Agrawal, Sunil
A2 - Ajoudani, Arash
A2 - Artemiadis, Panagiotis
A2 - Bianchi, Matteo
A2 - Lanari Bo, Antonio Padilha
A2 - Casadio, Maura
A2 - Cleary, Kevin
A2 - Deshpande, Ashish
A2 - Formica, Domenico
A2 - Fumagalli, Matteo
A2 - Garcia-Aracil, Nicolas
A2 - Godfrey, Sasha Blue
A2 - Khalil, Islam S.M.
A2 - Lambercy, Olivier
A2 - Loureiro, Rui C. V.
A2 - Mattos, Leonardo
A2 - Munoz, Victor
A2 - Park, Hyung-Soon
A2 - Rodriguez Cheu, Luis Eduardo
A2 - Saltaren, Roque
A2 - Siqueira, Adriano A. G.
A2 - Squeri, Valentina
A2 - Stienen, Arno H.A.
A2 - Tsagarakis, Nikolaos
A2 - Van der Kooij, Herman
A2 - Vanderborght, Bram
A2 - Vitiello, Nicola
A2 - Zariffa, Jose
A2 - Zollo, Loredana
PB - IEEE Computer Society
T2 - 5th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2014
Y2 - 12 August 2014 through 15 August 2014
ER -