Abstract: A method for selecting the target object for an automatic distance control of a single-track motor vehicle. The presence of a second single-track motor vehicle preceding directly in the same lane and a third single-track motor vehicle preceding directly the second single-track motor vehicle are detected with the aid of a surroundings sensor system. The lateral offset of the second single-track motor vehicle and of the third single-track motor vehicle are ascertained with regard to the single-track motor vehicle. The target object being selected for the method for distance control as a function of at least one of the lateral offsets.

Abstract: A method for carrying out a distance-regulating or speed-regulating function for a single-track motor vehicle. An activated distance-regulating or speed-regulating function can be deactivated by the driver through actuation of a brake operating element, if the actuation intensity of the brake operating element exceeds a first threshold value. The presence of a collision risk is ascertained by an environmental sensor system. When there is a risk of collision, an emergency braking assistance function is activated through the actuation of the brake operating element by the driver with an actuation intensity exceeding a second threshold value. The second threshold value is lower than the first threshold value. The activated distance-regulating or speed-regulating function is continued independently of the driver after the termination of the emergency braking assistance function, with the settings that were present before the activation of the emergency braking assistance function.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing online robotic motion planning from pre-generated motion plans. A library of pre-generated motion plans for performing a particular task is maintained. Each pre-generated motion plan comprises a plurality of waypoints and one or more actions. One or more present observations of a robot in a workcell are obtained. The one or more observations are classified. A pre-generated candidate motion plan that matches the labels assigned to the present observations of the robot in the workcell is selected from the library of pre-generated motion plans. The pre-generated candidate motion plan is adapted according to the present observations of the robot in the workcell to generate a final motion plan to be executed by the robot.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using skill templates for robotic demonstration learning. One of the methods includes receiving a skill template for a task to be performed by a robot, wherein the skill template defines a state machine having a plurality of subtasks and one or more respective transition conditions between one or more of the subtasks. Local demonstration data for a demonstration subtask of the skill template is received, where the local demonstration data is generated from a user demonstrating how to perform the demonstration subtask with the robot. A machine learning model is refined for the demonstration subtask and the skill template is executed on the robot, causing the robot to transition through the state machine defined by the skill template to perform the task.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using simulated local demonstration data for robotic demonstration learning. One of the methods includes receiving perceptual data of a workcell of a robot to be configured to execute a task according to a skill template, wherein the skill template specifies one or more subtasks required to perform the skill, wherein at least one of the subtasks is a demonstration subtask that relies on learning visual characteristics of the workcell. A virtual model is generated of a portion of the workcell. A training system generates simulated local demonstration data from the virtual model of the portion of the workcell and tunes a base control policy for the demonstration subtask using the simulated local demonstration data generated from the virtual model of the portion of the workcell.

Abstract: A method for operating a vehicle with a driver assistance system. A distance function of the driver assistance system regulates a distance from a preceding target object using system interventions in a brake system and/or a drive system of the vehicle to a speed-dependent safety distance, wherein the distance function is degraded during cornering of the vehicle.

Abstract: A method for setting a cruise control function with automatic distance setting in a single-track vehicle. In the method, a side distance between two preceding single-track vehicles is ascertained, a threshold value is determined as a function of the side distance, the side distance between one's own single-track vehicle and a preceding single-track vehicle is ascertained, and the preceding single-track vehicle is used as the target vehicle to be followed in the event that the side distance between one's own single-track vehicle and the preceding single-track vehicle is less than or equal to the threshold value.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using simulated local demonstration data for robotic demonstration learning. One of the methods includes receiving perceptual data of a workcell of a robot to be configured to execute a task according to a skill template, wherein the skill template specifies one or more subtasks required to perform the skill, wherein at least one of the subtasks is a demonstration subtask that relies on learning visual characteristics of the workcell. A virtual model is generated of a portion of the workcell. A training system generates simulated local demonstration data from the virtual model of the portion of the workcell and tunes a base control policy for the demonstration subtask using the simulated local demonstration data generated from the virtual model of the portion of the workcell.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for distributing skill templates for robotic demonstration learning. One of the methods includes receiving from the user device by a skill template distribution system, a selection of an available skill template. The skill template distribution system provides a skill template, wherein the skill template comprises information representing a state machine of one or more tasks, and wherein the skill template specifies which of the one or more tasks are demonstration subtasks requiring local demonstration data. The skill template distribution system trains a machine learning model for the demonstration subtask using a local demonstration data to generate learned parameter values.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using a demonstration device for robotic demonstration learning. One of the methods includes generating, by a demonstration device for a robot, a representation of a sequence of states input by a user of the demonstration device. The representation is provided by the demonstration device to a robot execution system. The representation of the sequence of actions is translated into a plurality of robot commands corresponding to the representation of the sequence of states input by the user on the demonstration device. The plurality of robot commands corresponding to the sequence of actions input by the user on the demonstration device are executed. Demonstration data is generated from one or more sensor streams of the robot while executing the plurality of robot commands corresponding to the sequence of actions input by the user on the demonstration device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for distributing skill templates for robotic demonstration learning. One of the methods includes receiving, from the user device by a skill template distribution system, a selection of an available skill template. The skill template distribution system provides a skill template, wherein the skill template comprises information representing a state machine of one or more tasks, and wherein the skill template specifies which of the one or more tasks are demonstration subtasks requiring local demonstration data. The skill template distribution system trains a machine learning model for the demonstration subtask using a local demonstration data to generate learned parameter values.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for distributed robotic demonstration learning. One of the methods includes receiving a skill template to be trained to cause a robot to perform a particular skill having a plurality of subtasks. One or more demonstration subtasks defined by the skill template are identified, wherein each demonstration subtask is an action to be refined using local demonstration data. On online execution system uploads sets of local demonstration data to a cloud-based training system. The cloud-based training system generates respective trained model parameters for each set of local demonstration data. The skill template is executed on the robot using the trained model parameters generated by the cloud-based training system.

Abstract: A method for operating a single-track or multi-track vehicle including a driver-assistance system. In the method, a speed of the vehicle and a distance of the vehicle from a vehicle in front are controlled. The speed is controlled within a system-related speed range of the driver-assistance system using a position of an operating element of the vehicle and is controlled up to an optional target speed that is selectable within the speed range. Before an upper limit of the speed range is exceeded, a warning signal is provided to a driver of the vehicle. The distance is controlled within the speed range in a speed-dependent distance buffer region depending on the position.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using a demonstration device for robotic demonstration learning. One of the methods includes generating, by a demonstration device for a robot, a representation of a sequence of states input by a user of the demonstration device. The representation is provided by the demonstration device to a robot execution system. The representation of the sequence of actions is translated into a plurality of robot commands corresponding to the representation of the sequence of states input by the user on the demonstration device. The plurality of robot commands corresponding to the sequence of actions input by the user on the demonstration device are executed. Demonstration data is generated from one or more sensor streams of the robot while executing the plurality of robot commands corresponding to the sequence of actions input by the user on the demonstration device.

Abstract: A loudspeaker containing a sound-generating element and a grill mounted as a cover in front of the sound-generating element. The grill has optically transparent areas. At least one lighting element is mounted between the sound-generating element and the grill, the lighting element being visible from the outside through the optically transparent areas of the grill when illuminated.

Abstract: Process for making a granule containing (A) at least one chelating agent selected from alkali metal salts of methyl glycine diacetic acid (MGDA) and of iminodisuccinic acid (IDS), and, optionally, (B) at least one homo- or copolymer of (meth)acrylic acid, partially or fully neutralized with alkali, said process comprising the steps of (a) providing an aqueous solution or slurry containing chelating agent (A) and, if applicable, (co)polymer (B), (b) removing most of said water by spray granulation in a fluidized bed, (c) treating the resultant granule in a vessel of which at least one part rotates around a horizontal axis and wherein said vessel is selected from paddle mixers, free-fall mixers and plough share mixers.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for integrating sensor streams for robotic demonstration learning. One of the methods includes selecting, by a learning system for a robot, a base update rate for combining multiple sensor streams into a task state representation. The learning system repeatedly generates the task state representation at the base update rate, including combining, during each time period defined by the update rate, the task state representation from most recently updated sensor data processed by the plurality of neural networks. The learning system repeatedly uses the task state representations to generate commands for the robot at the base update rate.

Abstract: The present invention is related to a process for coating anoxide material, said process comprising the following steps: (a) providing a particulate material selected from lithiated nickel-cobalt aluminum oxides, lithiated cobalt-manganese oxides and lithiated layered nickel-cobalt-manganese oxides, (b) treating said cathode active material with a metal alkoxide or metal amide or alkyl metal compound, (c) treating the material obtained in step (b) with moisture, and, optionally, repeating the sequence of steps (b) and (c), wherein steps (b) and (c) are carried out in a mixer that mechanically introduces mixing energy into the particulate material, or by way of a moving bed or fixed bed, and wherein steps (b) and (c) are carried out at a pressure that is in the range of from 5 mbar to 1 bar above normal pressure.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using a demonstration device for robotic demonstration learning. One of the methods includes generating, by a demonstration device for a robot, a representation of a sequence of states input by a user of the demonstration device. The representation is provided by the demonstration device to a robot execution system. The representation of the sequence of actions is translated into a plurality of robot commands corresponding to the representation of the sequence of states input by the user on the demonstration device. The plurality of robot commands corresponding to the sequence of actions input by the user on the demonstration device are executed. Demonstration data is generated from one or more sensor streams of the robot while executing the plurality of robot commands corresponding to the sequence of actions input by the user on the demonstration device.

Abstract: A method for operating a motor vehicle, in particular a motorcycle, in which a driving maneuver, which includes a lane change and/or a passing maneuver, is carried out in an at least partially automated manner. The acceleration dynamics of the motor vehicle are adjusted as a function of the relative speed of at least one other motor vehicle, for example of a motor vehicle preceding and/or approaching from behind, as the driving maneuver is carried out.