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2014


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Pole Balancing with Apollo

Holger Kaden

Eberhard Karls Universität Tübingen, December 2014 (mastersthesis)

[BibTex]

2014

[BibTex]


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Learning Coupling Terms for Obstacle Avoidance

Rai, A.

École polytechnique fédérale de Lausanne, August 2014 (mastersthesis)

Project Page [BibTex]

Project Page [BibTex]


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Object Tracking in Depth Images Using Sigma Point Kalman Filters

Issac, J.

Karlsruhe Institute of Technology, July 2014 (mastersthesis)

Project Page [BibTex]

Project Page [BibTex]


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Learning objective functions for autonomous motion generation

Kalakrishnan, M.

University of Southern California, University of Southern California, Los Angeles, CA, 2014 (phdthesis)

Project Page Project Page [BibTex]

Project Page Project Page [BibTex]


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Muscle Synergy Features in Behavior Adaptation and Recovery

Alnajjar, F. S., Berenz, V., Ken-ichi, O., Ohno, K., Yamada, H., Kondo, I., Shimoda, S.

In Replace, Repair, Restore, Relieve – Bridging Clinical and Engineering Solutions in Neurorehabilitation: Proceedings of the 2nd International Conference on NeuroRehabilitation (ICNR2014), Aalborg, 24-26 June, 2014, pages: 245-253, Springer International Publishing, Cham, 2014 (inbook)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Data-driven autonomous manipulation

Pastor, P.

University of Southern California, University of Southern California, Los Angeles, CA, 2014 (phdthesis)

Project Page Project Page [BibTex]

Project Page Project Page [BibTex]

2010


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Locally weighted regression for control

Ting, J., Vijayakumar, S., Schaal, S.

In Encyclopedia of Machine Learning, pages: 613-624, (Editors: Sammut, C.;Webb, G. I.), Springer, 2010, clmc (inbook)

Abstract
This is article addresses two topics: learning control and locally weighted regression.

link (url) [BibTex]

2010

link (url) [BibTex]

2009


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Synchronized Oriented Mutations Algorithm for Training Neural Controllers

Berenz, V., Suzuki, K.

In Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II, pages: 244-251, Springer Berlin Heidelberg, Berlin, Heidelberg, 2009 (inbook)

link (url) DOI [BibTex]

2009

link (url) DOI [BibTex]


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Integration of Visual Cues for Robotic Grasping

Bergström, N., Bohg, J., Kragic, D.

In Computer Vision Systems, 5815, pages: 245-254, Lecture Notes in Computer Science, Springer Berlin Heidelberg, 2009 (incollection)

Abstract
In this paper, we propose a method that generates grasping actions for novel objects based on visual input from a stereo camera. We are integrating two methods that are advantageous either in predicting how to grasp an object or where to apply a grasp. The first one reconstructs a wire frame object model through curve matching. Elementary grasping actions can be associated to parts of this model. The second method predicts grasping points in a 2D contour image of an object. By integrating the information from the two approaches, we can generate a sparse set of full grasp configurations that are of a good quality. We demonstrate our approach integrated in a vision system for complex shaped objects as well as in cluttered scenes.

pdf link (url) DOI [BibTex]

pdf link (url) DOI [BibTex]


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Bayesian Methods for Autonomous Learning Systems (Phd Thesis)

Ting, J.

Department of Computer Science, University of Southern California, Los Angeles, CA, 2009, clmc (phdthesis)

PDF [BibTex]

PDF [BibTex]

1991


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Ways to smarter CAD-systems

Ehrlenspiel, K., Schaal, S.

In Proceedings of ICED’91Heurista, pages: 10-16, (Editors: Hubka), Edition, Schriftenreihe WDK 21. Zürich, 1991, clmc (inbook)

[BibTex]

1991

[BibTex]