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Cited by 463

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Learning and Reproduction of Gestures by Imitation

Open access
Calinon, Sylvain, D'halluin, Florent, Sauser, Eric, Caldwell, Darwin, Billard, Aude·2010·IEEE Robotics & Automation Magazine

Abstract

We presented and evaluated an approach based on HMM, GMR, and dynamical systems to allow robots to acquire new skills by imitation. Using HMM allowed us to get rid of the explicit time dependency that was considered in our previous work [12], by encapsulating precedence information within the statistical representation. In the context of separated learning and reproduction processes, this novel formulation was systematically evaluated with respect to our previous approach, LWR [20], LWPR [21], and DMPs [13]. We finally presented applications on different kinds of robots to highlight the flexibility of the proposed approach in three different learning by imitation scenarios.

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Metadata

Authors
Calinon, S., D'halluin, F., Sauser, E., Caldwell, D., & Billard, A.
Venue
IEEE Robotics & Automation Magazine
Published
2010-06
Volume
17
Issue
2
Pages
44-54
ISSN
1070-9932 (ISSN-L)
OpenAlex
W2154543878
Cited by
463
References
3
FWCI
45.14
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Learning and Reproduction of Gestures by Imitation. https://app.cochat.ai/papers/10.1109/mra.2010.936947
The paper
Calinon, S., D'halluin, F., Sauser, E., Caldwell, D., & Billard, A. (2010). Learning and Reproduction of Gestures by Imitation. IEEE Robotics & Automation Magazine. https://doi.org/10.1109/mra.2010.936947

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.