Environment-adaptive interaction primitives through visual context for human–robot motor skill learning
Author:
Funder
New Energy and Industrial Technology Development Organization
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
http://link.springer.com/content/pdf/10.1007/s10514-018-9798-2.pdf
Reference38 articles.
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3. Ben Amor, H., Neumann, G., Kamthe, S., Kroemer, O., & Peters, J. (2014). Interaction primitives for human-robot cooperation tasks. In IEEE international conference on robotics and automation (ICRA) (pp. 2831–2837). IEEE.
4. Cao, Z., Simon, T., Wei, S., & Sheikh, Y. (2017). Realtime multi-person 2D pose estimation using part affinity fields. In IEEE conference on computer vision and pattern recognition (CVPR) (pp. 1302–1310).
5. Cui, Y., Poon, J., Matsubara, T., Valls Miro, J., Sugimoto, K., & Yamazaki, K. (2016). Environment-adaptive interaction primitives for human–robot motor skill learning. In IEEE-RAS international conference on humanoid robots (Humanoids) (pp. 711–717).
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