Haptic Intelligence

6 results (View BibTeX file of all listed publications)

2021

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An electric machine with two-phase planar Lorentz coils and a ring-shaped Halbach array for high torque density and high-precision applications

Nguyen, V., Javot, B., Kuchenbecker, K. J.

(EP21170679.1), April 2021 (patent)

Abstract
An electric machine, in particular a motor or a generator, comprising a rotor and a stator, wherein the rotor comprises a planar, ring-shaped rotor base element and the stator comprises a planar ring-shaped stator base element, wherein the rotor base element and the stator base element are aligned along an axial axis (Z) of the electric machine, wherein a plurality of magnet elements are arranged around the circumference of the ring-shaped rotor base element forming a Halbach magnet-ring assembly, wherein the Halbach magnet-ring assembly generates a magnetic field (BR) with axial and azimuthal components, wherein a plurality of coils are arranged around the circumference (C) of the ring-shaped stator base element.

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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]

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.

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2020

System and Method for Simultaneously Sensing Contact Force and Lateral Strain
System and Method for Simultaneously Sensing Contact Force and Lateral Strain

Lee, H., Kuchenbecker, K. J.

(EP20000480.2), December 2020 (patent)

Abstract
A tactile sensing system having a sensor component which comprises a plurality of layers stacked along a normal axis Z and a detection unit electrically connected to the sensor component, wherein the sensor component comprises a first layer, designed as a piezoresistive layer, a third layer, designed as a conductive layer which is electrically connected to the detection unit, and a second layer, designed as a spacing layer between the first layer and the third layer, wherein the first layer comprises a plurality of electrodes In electrically connected to the detection unit, wherein at least one contact force along the normal axis Z on the sensor component is detectable by the detection unit due to a change of a current distribution between the first layer and the third layer, wherein at least one lateral strain on the sensor component is detectable by the detection unit due to a change of the resistance distribution change in the piezoresistive first layer.

Project Page [BibTex]

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]