Robert Boschgmbh

Jens Oehlerking

Christian Heinzemann

Michael Rittel

Andreas Heyl

Christoph Gladisch

Martin Herrmann

Nadja Schalm

Martin Butz

Michael Fey

Alexandre Wagner

Konrad Groh

Matthias Woehrle

Oliver Willers

Martin Knopp

Joerg Frauhammer

Sebastian Sudholt

Matthias Eckart

Tino Brade

A computer-implemented method for evaluating an image classifier, in which a classifier output of the image classifier is provided for the actuation of an at least semi-autonomous robot. The evaluation method includes: ascertaining a first dataset including image data and annotations being assigned to the image data, the annotations including information about the scene imaged in the respective image and/or about image regions to be classified and/or about movement information of the robot; ascertaining regions of the scenes that are reachable by the robot based on the annotations; ascertaining relevance values for image regions to be classified by the image classifier; classifying the image data of the first image dataset with the aid of the image classifier; evaluating the image classifier based on image regions correctly classified by the image classifier and incorrectly classified image regions, as well as the calculated relevance values of the corresponding image regions.

Method and device for evaluating an image classifier

A computer-implemented method for detecting an obstacle on a route ahead of a first vehicle. In the method, information on a second vehicle driving ahead on the route is recorded in the first vehicle by at least one sensor of the first vehicle. In the first vehicle, depending on the recorded information, a computer detects an avoidance maneuver of the second vehicle due to an obstacle or detects that the second vehicle has driven over an obstacle. An obstacle is detected on the route depending on the detected avoidance maneuver or the detection that the vehicle has driven over an obstacle. A measure for protecting the vehicle and/or the obstacle is initiated depending on the detected obstacle.

Method for detecting an obstacle on a route

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.

Method for controlling a vehicle

A method for controlling a filling level of an exhaust gas component accumulator of a catalytic converter in the exhaust gas of an internal combustion engine where an actual filling level of the accumulator is determined with a first catalytic converter model. The method includes forming a lambda setpoint is formed, wherein a predetermined target fill level is converted into a base lambda setpoint via a second system model reverse of the first catalytic converter model, a deviation of the actual fill level from the predetermined target fill level is determined and processed to a lambda setpoint correction value via a fill level control unit, a sum of the base lambda setpoint value and the lambda setpoint value correction value is formed, and said sum is used to form a correction value, with which fuel metering to at least one combustion chamber of the internal combustion engine is influenced.

Method for controlling an exhaust gas component filling level in an accumulator of a catalytic converter

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Stuttgart, Germany

Jens Oehlerking