Patents by Inventor Christoph Gladisch

Christoph Gladisch has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20220262103
    Abstract: A computer-implemented method for testing conformance between images generated by a synthetic image generator and images obtained from authentic visual data. A conformance test result results from comparing results of global sensitivity analyses used to rank the effect of visual parameters on the computer vision model both for synthetic and authentic visual data.
    Type: Application
    Filed: January 27, 2022
    Publication date: August 18, 2022
    Inventors: Christoph Gladisch, Christian Heinzemann, Matthias Woehrle
  • Patent number: 11416371
    Abstract: A method for evaluating a simulation model. In the method, for selected test cases, a first performance index is calculated in the simulation model. For the same test case, a second performance index is ascertained in a real test environment. For each of the test cases, a difference is calculated between the first performance index and the second performance index, and a signal metric is determined. For each of the signal metrics, an interrelation between the difference and the respective signal metric is investigated. The signal metric that exhibits the closest interrelation with the difference is selected.
    Type: Grant
    Filed: May 20, 2020
    Date of Patent: August 16, 2022
    Assignee: Robert Bosch GmbH
    Inventors: Joachim Sohns, Christoph Gladisch, Thomas Heinz
  • Publication number: 20220237897
    Abstract: A computer-implemented method for analysing the relevance of visual parameters for training a computer vision model. Upon adjusting the set of visual parameters to increase their relevance a new set of visual data and corresponding groundtruth results that can be used in (re)training and/or testing the computer vision model.
    Type: Application
    Filed: January 6, 2022
    Publication date: July 28, 2022
    Inventors: Christian Heinzemann, Christoph Gladisch, Matthias Woehrle, Ulrich Seger
  • Patent number: 11397660
    Abstract: A method or testing a system. Input parameters of the system are divided into a first group and a second group. Using a first method, a first selection is made from among the input parameter assignments of the first group. Using a second method, a second selection is made from among the input parameter assignments of the second group. A characteristic value is calculated from the second selection. The first selection is adapted depending on the characteristic value.
    Type: Grant
    Filed: May 20, 2020
    Date of Patent: July 26, 2022
    Assignee: Robert Bosch GmbH
    Inventors: Christoph Gladisch, Thomas Heinz, Christian Heinzemann, Matthias Woehrle
  • Publication number: 20220230072
    Abstract: Facilitating the description or configuration of a computer vision model by generating a data structure comprising a plurality of language entities defining a semantic mapping of visual parameters to a visual parameter space based on a sensitivity analysis of the computer vision model.
    Type: Application
    Filed: January 4, 2022
    Publication date: July 21, 2022
    Inventors: Christoph Gladisch, Christian Heinzemann, Martin Herrmann, Matthias Woehrle, Nadja Schalm
  • Publication number: 20220230419
    Abstract: Reducing the number of parameters in a visual parameter set based on a sensitivity analysis of how a given visual parameter affects the performance of a computer vision model to provide a verification parameter set having a reduced size.
    Type: Application
    Filed: January 4, 2022
    Publication date: July 21, 2022
    Inventors: Christoph Gladisch, Christian Heinzemann, Matthias Woehrle
  • Publication number: 20220230418
    Abstract: A computer-implemented method for training a computer vision model to characterise elements of observed scenes parameterized using visual parameters. During the iterative training of the computer vision model, the latent variables of the computer vision model are altered based upon a (global) sensitivity analysis used to rank the effect of visual parameters on the computer vision model.
    Type: Application
    Filed: January 4, 2022
    Publication date: July 21, 2022
    Inventors: Christoph Gladisch, Christian Heinzemann, Matthias Woehrle
  • Publication number: 20220222926
    Abstract: Modifying a visual parameter specification characterising the operational design domain of the computer vision model by improving the visual parameter specification according to a sensitivity analysis of the computer vision model.
    Type: Application
    Filed: January 4, 2022
    Publication date: July 14, 2022
    Inventors: Christoph Gladisch, Christian Heinzemann, Martin Herrmann, Matthias Woehrle, Nadja Schalm
  • Publication number: 20220176949
    Abstract: A method for controlling a vehicle. In the method, data of a digital road map are read in, zones are determined for the digital road map, and possible sequences of trips along a road of the digital road map are ascertained as a function of the determined zones. Furthermore, it is ascertained, as a function of sensor data and/or current driving data of the vehicle, whether a current or predicted traffic situation is outside the possible sequences or corresponds to a possible sequence that is determined as being outside an intended operating range. If the current or predicted traffic situation is outside the possible sequences or corresponds to the possible sequence outside the intended operating range, a measure is determined and the vehicle is controlled as a function of the measure that is taken.
    Type: Application
    Filed: October 18, 2021
    Publication date: June 9, 2022
    Inventors: Christian Heinzemann, Andreas Heyl, Christoph Gladisch, Jens Oehlerking, Martin Butz, Martin Herrmann, Michael Rittel, Nadja Schalm, Tino Brade
  • Patent number: 11243858
    Abstract: A method for testing a technical system. The method includes: tests are carried out with the aid of a simulation of the system, the tests are evaluated with respect to a fulfillment measure of a quantitative requirement on the system and an error measure of the simulation, on the basis of the fulfillment measure and error measure, a classification of the tests as either reliable or unreliable is carried out.
    Type: Grant
    Filed: March 10, 2021
    Date of Patent: February 8, 2022
    Assignee: Robert Bosch GmbH
    Inventors: Christoph Gladisch, Daniel Seiler-Thull, Joachim Sohns, Philipp Glaser, Thomas Heinz, Ji Su Yoon
  • Patent number: 11237931
    Abstract: A method for testing a technical system. The method includes: tests are carried out with the aid of a simulation of the system, the tests are evaluated with respect to a fulfillment measure of a quantitative requirement on the system and an error measure of the simulation, on the basis of the fulfillment measure and error measure, a classification of the tests as either reliable or unreliable is carried out, and a test database is improved on the basis of the classification.
    Type: Grant
    Filed: March 9, 2021
    Date of Patent: February 1, 2022
    Assignee: Robert Bosch GmbH
    Inventors: Christoph Gladisch, Daniel Seiler-Thull, Ji Su Yoon, Philipp Glaser, Thomas Heinz, Joachim Sohns
  • Publication number: 20210364393
    Abstract: A method for testing a technical system. Tests are carried out with the aid of a simulation of the system. The tests are evaluated with respect to a fulfillment measure of a quantitative requirement on the system and different error measures of the simulation. On the basis of the fulfillment measure and each of the error measures, a classification of the tests is carried out as either reliable or unreliable case by case. A selection among the error measures is made on the basis of a number of the tests classified as reliable.
    Type: Application
    Filed: March 8, 2021
    Publication date: November 25, 2021
    Inventors: Christoph Gladisch, Ji Su Yoon, Joachim Sohns, Philipp Glaser, Thomas Heinz, Daniel Seiler-Thull
  • Publication number: 20210342239
    Abstract: A method for testing a technical system. The method includes: tests are carried out with the aid of a simulation of the system, the tests are evaluated with respect to a fulfillment measure of a quantitative requirement on the system and an error measure of the simulation, on the basis of the fulfillment measure and error measure, a classification of the tests as either reliable or unreliable is carried out.
    Type: Application
    Filed: March 10, 2021
    Publication date: November 4, 2021
    Inventors: Christoph Gladisch, Daniel Seiler-Thull, Joachim Sohns, Philipp Glaser, Thomas Heinz, Ji Su Yoon
  • Publication number: 20210342238
    Abstract: A method for testing a technical system. The method includes: tests are carried out with the aid of a simulation of the system, the tests are evaluated with respect to a fulfillment measure of a quantitative requirement on the system and an error measure of the simulation, on the basis of the fulfillment measure and error measure, a classification of the tests as either reliable or unreliable is carried out, and a test database is improved on the basis of the classification.
    Type: Application
    Filed: March 9, 2021
    Publication date: November 4, 2021
    Inventors: Christoph Gladisch, Daniel Seiler-Thull, Ji Su Yoon, Philipp Glaser, Thomas Heinz, Joachim Sohns
  • Publication number: 20210248464
    Abstract: A device and a computer-implemented method for machine learning. First input data are provided which encompass information concerning dimensions and options for the machine learning. At least one of the options is associated with at least one of the dimensions as a function of information concerning the dimensions and options for at least one test case for the machine learning. A combination of options for a subset of the dimensions that is lacking in the set of test cases is determined, and a test case is determined for this combination.
    Type: Application
    Filed: February 3, 2021
    Publication date: August 12, 2021
    Inventors: Christian Heinzemann, Christoph Gladisch, Martin Herrmann, Matthias Woehrle
  • Publication number: 20200409823
    Abstract: A method for optimizing test cases. The method includes the following features. On the basis of simulation data obtained by way of the simulation, a simulation metamodel is created. On the basis of measurements performed in the test environment, a reality metamodel is created. Uncertainties inherent in the simulation data and measurements are combined by the fact that either the sum is calculated or the worst case of the two calculations is used or the worst case is respectively considered for each uncertainty being considered. On the basis of the combination of the uncertainties, a metamodel encompassing the simulation and the test environment is created. A search-based optimization of the test cases is performed by way of the metamodel.
    Type: Application
    Filed: May 8, 2020
    Publication date: December 31, 2020
    Inventors: Joachim Sohns, Christoph Gladisch, Thomas Heinz
  • Publication number: 20200409817
    Abstract: A method for evaluating a simulation model. In the method, for selected test cases, a first performance index is calculated in the simulation model. For the same test case, a second performance index is ascertained in a real test environment. For each of the test cases, a difference is calculated between the first performance index and the second performance index, and a signal metric is determined. For each of the signal metrics, an interrelation between the difference and the respective signal metric is investigated. The signal metric that exhibits the closest interrelation with the difference is selected.
    Type: Application
    Filed: May 20, 2020
    Publication date: December 31, 2020
    Inventors: Joachim Sohns, Christoph Gladisch, Thomas Heinz
  • Publication number: 20200409816
    Abstract: A method or testing a system. Input parameters of the system are divided into a first group and a second group. Using a first method, a first selection is made from among the input parameter assignments of the first group. Using a second method, a second selection is made from among the input parameter assignments of the second group. A characteristic value is calculated from the second selection. The first selection is adapted depending on the characteristic value.
    Type: Application
    Filed: May 20, 2020
    Publication date: December 31, 2020
    Inventors: Christoph Gladisch, Thomas Heinz, Christian Heinzemann, Matthias Woehrle