Intelligent Systems

8 results (View BibTeX file of all listed publications)

2021

Sensor arrangement for sensing forces and methods for fabricating a sensor arrangement and parts thereof
Sensor arrangement for sensing forces and methods for fabricating a sensor arrangement and parts thereof

Sun, H., Martius, G., Kuchenbecker, K. J.

(PCT/EP2021/050230), Max Planck Institute for Intelligent Systems, Max Planck Ring 4, January 2021 (patent)

Abstract
The invention relates to a vision-based haptic sensor arrangement for sensing forces, to a method for fabricating a top portion of a sensor arrangement, and to a method for fabricating a sensor arrangement.

Project Page [BibTex]

2021

Sun, H., Martius, G., Kuchenbecker, K. J. Sensor arrangement for sensing forces and methods for fabricating a sensor arrangement and parts thereof (PCT/EP2021/050230), Max Planck Institute for Intelligent Systems, Max Planck Ring 4, January 2021 (patent)

Project Page [BibTex]

Method for force inference, method for training a feed-forward neural network, force inference module, and sensor arrangement
Method for force inference, method for training a feed-forward neural network, force inference module, and sensor arrangement

Sun, H., Martius, G., Kuchenbecker, K. J.

(PCT/EP2021/050231), Max Planck Institute for Intelligent Systems, Max Planck Ring 4, January 2021 (patent)

Abstract
The invention relates to a method for force inference of a sensor arrangement for sensing forces, to a method for training a feed-forward neural network, to a force inference module, and to a sensor arrangement.

Project Page [BibTex]

2020

Method for Force Inference of a Sensor Arrangement, Methods for Training Networks, Force Inference Module and Sensor Arrangement
Method for Force Inference of a Sensor Arrangement, Methods for Training Networks, Force Inference Module and Sensor Arrangement

Sun, H., Martius, G., Lee, H., Spiers, A., Fiene, J.

(PCT/EP2020/083261), Max Planck Institute for Intelligent Systems, Max Planck Ring 4, November 2020 (patent)

Abstract
The present invention relates to a method for force inference of a sensor arrangement, to related methods for training of networks, to a force inference module for performing such methods, and to a sensor arrangement for sensing forces. When developing applications such as robots, sensing of forces applied on a robot hand or another part of a robot such as a leg or a manipulation device is crucial in giving robots increased capabilities to move around and/or manipulate objects. Known implementations for sensor arrangements that can be used in robotic applications in order to have feedback with regard to applied forces are quite expensive and do not have sufficient resolution. Sensor arrangements may be used to measure forces. However, known sensor arrangements need a high density of sensors to provide for a high special resolution. It is thus an object of the present invention to provide for a method for force inference of a sensor arrangement and related methods that are different or optimized with regard to the prior art. It is a further object to provide for a force inference module to perform such methods. It is a further object to provide for a sensor arrangement for sensing forces with such a force inference module.

Project Page [BibTex]

2014

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Robot Learning by Guided Self-Organization

Martius, G., Der, R., Herrmann, J. M.

In Guided Self-Organization: Inception, 9, pages: 223-260, Emergence, Complexity and Computation, Springer Berlin Heidelberg, 2014 (incollection)

link (url) DOI [BibTex]

2014

Martius, G., Der, R., Herrmann, J. M. Robot Learning by Guided Self-Organization In Guided Self-Organization: Inception, 9, pages: 223-260, Emergence, Complexity and Computation, Springer Berlin Heidelberg, 2014 (incollection)

link (url) DOI [BibTex]

2013

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Behavior as broken symmetry in embodied self-organizing robots

Der, R., Martius, G.

In Advances in Artificial Life, ECAL 2013, pages: 601-608, MIT Press, 2013 (incollection)

[BibTex]

2013

Der, R., Martius, G. Behavior as broken symmetry in embodied self-organizing robots In Advances in Artificial Life, ECAL 2013, pages: 601-608, MIT Press, 2013 (incollection)

[BibTex]

2011

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Tipping the Scales: Guidance and Intrinsically Motivated Behavior

Martius, G., Herrmann, J. M.

In Advances in Artificial Life, ECAL 2011, pages: 506-513, (Editors: Tom Lenaerts and Mario Giacobini and Hugues Bersini and Paul Bourgine and Marco Dorigo and René Doursat), MIT Press, 2011 (incollection)

[BibTex]

2011

Martius, G., Herrmann, J. M. Tipping the Scales: Guidance and Intrinsically Motivated Behavior In Advances in Artificial Life, ECAL 2011, pages: 506-513, (Editors: Tom Lenaerts and Mario Giacobini and Hugues Bersini and Paul Bourgine and Marco Dorigo and René Doursat), MIT Press, 2011 (incollection)

[BibTex]

2010

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Taming the Beast: Guided Self-organization of Behavior in Autonomous Robots

Martius, G., Herrmann, J. M.

In From Animals to Animats 11, 6226, pages: 50-61, LNCS, Springer, 2010 (incollection)

link (url) DOI [BibTex]

2010

Martius, G., Herrmann, J. M. Taming the Beast: Guided Self-organization of Behavior in Autonomous Robots In From Animals to Animats 11, 6226, pages: 50-61, LNCS, Springer, 2010 (incollection)

link (url) DOI [BibTex]