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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | de Rengerve, A. Boucenna, S. Andry, P. Gaussier, P. |
| Copyright Year | 2010 |
| Description | Author affiliation: ETIS UMR CNRS 8051, ENSEA, University Cergy Pontoise, F-95000, France (de Rengerve, A.; Boucenna, S.; Andry, P.; Gaussier, P.) |
| Abstract | Mimicry and deferred imitation have often been considered as separate kinds of imitation. In this paper, we present a simple architecture for robotic arm control which can be used for both. The model is based on some dynamical equations [1], which provide a motor control with exploring and converging capacities. A visuo-motor map [2] is used to associate positions of the end effector in the visual space with proprioceptive position of the robotic arm. It enables a fast learning of the visuo-motor associations without needing to embed a priori information. The controller can be used both for accurate control and interaction. It has been implemented on a minimal robotic setup showing some interesting emergent properties. The robot can reproduce simple gestures in mimicry situation and finalized actions in deferred imitation situation. Moreover, it can even show some “intention” recognition abilities. Finally, the experiment of deferred imitation which inherits from learning by demonstration, also provides a good basis for cooperative and interactive experiments. |
| Starting Page | 1754 |
| Ending Page | 1759 |
| File Size | 2291151 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424466740 |
| ISSN | 21530866 |
| e-ISBN | 9781424466764 |
| DOI | 10.1109/IROS.2010.5651090 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-10-18 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Visualization Neurons Robot sensing systems Aerospace electronics Pixel Noise level |
| Content Type | Text |
| Resource Type | Article |
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