Using Structured UKR Manifolds for Motion Classification and Segmentation

Steffen JF, Pardowitz M, Ritter H (2009)
In: Intelligent Robots and Systems (IROS). 4785-4790.

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Conference Paper | Published | English
Abstract
Task learning from observations of non-expert human users will be a core feature of future cognitive robots. However, the problem of task segmentation has only received minor attention. In this paper, we present a new approach to classifying and segmenting series of observations into a set of candidate motions. As basis for these candidates, we use structured UKR manifolds, a modified version of unsupervised kernel regression which has been introduced in order to easily reproduce and synthesise represented dextrous manipulation tasks. Together with the presented mechanism, it then realises a system that is able both to reproduce and recognise the represented motions.
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IROS
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St. Louis, USA
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Steffen JF, Pardowitz M, Ritter H. Using Structured UKR Manifolds for Motion Classification and Segmentation. In: Intelligent Robots and Systems (IROS). 2009: 4785-4790.
Steffen, J. F., Pardowitz, M., & Ritter, H. (2009). Using Structured UKR Manifolds for Motion Classification and Segmentation. Intelligent Robots and Systems (IROS), 4785-4790.
Steffen, J. F., Pardowitz, M., and Ritter, H. (2009). “Using Structured UKR Manifolds for Motion Classification and Segmentation” in Intelligent Robots and Systems (IROS) 4785-4790.
Steffen, J.F., Pardowitz, M., & Ritter, H., 2009. Using Structured UKR Manifolds for Motion Classification and Segmentation. In Intelligent Robots and Systems (IROS). pp. 4785-4790.
J.F. Steffen, M. Pardowitz, and H. Ritter, “Using Structured UKR Manifolds for Motion Classification and Segmentation”, Intelligent Robots and Systems (IROS), 2009, pp.4785-4790.
Steffen, J.F., Pardowitz, M., Ritter, H.: Using Structured UKR Manifolds for Motion Classification and Segmentation. Intelligent Robots and Systems (IROS). p. 4785-4790. (2009).
Steffen, Jan Frederik, Pardowitz, Michael, and Ritter, Helge. “Using Structured UKR Manifolds for Motion Classification and Segmentation”. Intelligent Robots and Systems (IROS). 2009. 4785-4790.
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