Robert Boschgmbh

Gerhard Neumann

Anh Vien Ngo

Hanna Ziesche

Hans-Jurgen Conrad

Helmut Martini

Michael Volpp

Hanns Kurz

Alireza Ranjbar

Rodrigo Chau

Ning Gao

A computer-implemented method for ascertaining, using a machine learning system, a first output signal characterizing a classification and/or a regression of a first input signal, and the output signal includes a first representation which characterizes an expected value of the classification or the regression, and a second representation, which characterizes a variance of the classification or regression. The method includes: ascertaining, using an encoder, latent representations each ascertained based on a second input signal and a second output signal that corresponds to the second input signal, and the second input signal and the second output signal characterize a context, the latent representation includes a first representation characterizing an expected value and a second representation characterizing a variance; ascertaining a third representation characterizing an accumulation of the first representations; ascertaining a fourth representation characterizing an accumulation of the second representations; ascertaining the first output signal using a decoder.

Method for ascertaining an output signal with the aid of a machine learning system

A method for controlling a robot device. The method includes: acquiring an image of an environment of the robot device; processing the image using a neural network, which outputs from the image a respective value image with pixel values for multiple pixels for at least one action parameter value, the pixel value for each pixel indicating an evaluation of an action specified by the action parameter value and the position of the pixel in the value image; selecting, from multiple actions, the particular action from among the multiple actions for which the pixel value of the pixel in the value image is at a maximum for the action parameter value at the position that specifies the action together with the action parameter value; and controlling the robot device to carry out the selected action.

Method for controlling a robot device

A method for training a control arrangement for a controlled system. The control arrangement includes a regulation device and an actuator that operates according to a control strategy. The method includes the generation of control actions by the regulation device, each control action being generated by detecting measured variables that indicate a state of the controlled system, ascertaining a correction term for the detected measured variables by the actuator according to the control strategy, adapting the detected measured variables using the correction term for the detected measured variables, and generating the control action by supplying the adapted measured variables to the regulation device as the actual value. The method further includes training the control strategy by reinforcement learning for maximizing the gain that is achieved by the generated control actions.

Method for training a control arrangement for a controlled system

A device and computer implemented method of controlling a machine. The method includes determining a state of the machine, determining a policy comprising parameters in particular a gain, for mapping the state of the machine to an input for the machine, mapping the state to the input according to the policy, an controlling the machine according to the input. A cone program is defined by a plurality of parameters of a linear quadratic regulator for the machine. A cost function is defined depending on the plurality of parameters and the policy. A constraint is defined for the parameters and for a solution of the cone program. The determining of the policy comprises determining the solution to the cone program so that the cost function meets a criterion subject to the constraint.

Method and device for controlling a machine

Thermal deburring system

To avoid venting of a deburring chamber and associated equipment after charge of the chamber with an explosive mixture if a spark plug (3a) has failed to ignite the mixture, a glow ignition block (4) is located in the path of gas communication between a mixing block (3) in which the spark plug is retained, and a glow plug (8) is located to have its glow portion exposed to the combustible gas mixture, preferably in a bypass (9) to a main gas path. A thermal element (12) monitors whether, upon application of an ignition pulse to the spark plug (3a), ignition has occurred by sensing a sharp temperature pulse; upon failure to sense such a temperature pulse, the glow plug is energized for ignition of the combustible mixture thereby. The spark plug may be of the vehicular internal combustion engine type; and the glow plug may, for example, be similar to 'pre-glow' plugs used in vehicular-type Diesel engines.

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Stuttgart, Germany

Gerhard Neumann