Abstract: A method for determining objects in an environment with the aid of SLAM and a mobile device in the environment, which has at least one sensor for acquiring object and/or environment information. The method includes: providing sensor data, carrying out an object detection in order to obtain first object datasets for detected objects; carrying out object tracking for a new SLAM dataset, including allocating objects detected with the aid of the object detection to real objects in order to obtain second object datasets or real objects to be considered in the SLAM graph.

Abstract: The disclosure relates to a method for determining the orientation of a robot and comprises at least one method step in which expected orientation data (I) pertaining to an expected orientation of the robot are provided and a method step in which actual orientation data (II) pertaining to an actual orientation of the robot are provided. According to the disclosure, one method step involves the expected orientation data (I) and the actual orientation data (II) being used to ascertain outlier-free orientation data that are used for determining the orientation of the robot. The disclosure further relates to a robot and to an orientation determination apparatus.

Abstract: A method for the simultaneous localization and mapping in 2D using a 3D scanner. An environment is scanned with the aid of the 3D scanner in order to generate a three-dimensional representation of the environment in the form of a 3D pixel cloud made up of a multitude of scanned pixels. A two-dimensional representation of the environment in the form of a 2D pixel cloud is subsequently generated from the 3D pixel cloud. The 2D pixel cloud is conveyed to a 2D SLAM algorithm for the generation of a map of the environment and for the simultaneous ascertainment of the current position of the 3D scanner within the map.

Abstract: A computer-implemented method for operating a mobile agent in an environment on the basis of a pose of the mobile agent. The location of the mobile agent is determined by way of the following steps in order to operate the mobile agent: capturing sensor data regarding walls and/or objects located in an environment, wherein the sensor data indicate the orientation and distance of the walls and/or objects in an agent-based agent coordinate system; establishing the pose of the mobile agent in the environment using a SLAM algorithm while taking account of a Manhattan orientation.

Abstract: A method for position determination. The method includes: recording measured data from the surroundings of a vehicle, robot, or mobile device, using at least one sensor situated on the vehicle, robot, and/or mobile device; compressing the measured data to form a compressed data item; searching for the compressed data item in a map, the map associating compressed data items at least with a position or pose in two- or three-dimensional space; in response to the compressed data item being found in the map, using the position or pose associated with the compressed data item by the map to ascertain the position or pose of the vehicle, robot, or mobile device. A method for creating a map for the position determination is also described.

Abstract: A method for creating digital maps with the aid of a control unit. Measured data of surroundings are received during a measuring run. A SLAM method is carried out for ascertaining a trajectory of the measuring run based on the received measured data. The received measured data are transformed into a coordinate system of the trajectory. The transformed measured data are used for the purpose of creating an intensity map. Features are extracted from the intensity map and are stored in a feature map. A method for carrying out a localization, a control unit, a computer program as well as a machine-readable memory medium are also described.

Abstract: The disclosure relates to a method for determining the orientation of a robot and comprises at least one method step in which expected orientation data (I) pertaining to an expected orientation of the robot are provided and a method step in which actual orientation data (II) pertaining to an actual orientation of the robot are provided. According to the disclosure, one method step involves the expected orientation data (I) and the actual orientation data (II) being used to ascertain outlier-free orientation data that are used for determining the orientation of the robot. The disclosure further relates to a robot and to an orientation determination apparatus.

Abstract: A method for the simultaneous localization and mapping in 2D using a 3D scanner. An environment is scanned with the aid of the 3D scanner in order to generate a three-dimensional representation of the environment in the form of a 3D pixel cloud made up of a multitude of scanned pixels. A two-dimensional representation of the environment in the form of a 2D pixel cloud is subsequently generated from the 3D pixel cloud. The 2D pixel cloud is conveyed to a 2D SLAM algorithm for the generation of a map of the environment and for the simultaneous ascertainment of the current position of the 3D scanner within the map.

Abstract: The disclosure relates to a method for mapping a processing area, in particular for determining a processing area, as part of a navigation method for autonomous robot vehicles. According to the disclosure, said method is characterized in that boundary lines between adjoining mapped and unmapped subareas of the processing area that is to be mapped are identified by comparing distances traveled by the robot vehicle during an initial mapping trip within the processing area, mapping of an unmapped subarea adjoining a boundary line is initiated from a point on one of those identified boundary lines during another mapping trip of the robot vehicle into the unmapped subarea, and a map of the processing area is created on the basis of the subareas mapped by the robot vehicle.

Abstract: An autonomous implement includes at least one orientation device configured to provide an orientation within a processing zone. The at least one orientation device is different from a perimeter-wire orientation device. The autonomous implement further includes at least one control and/or regulating unit configured to ascertain a travel strategy. The at least one control and/or regulating unit is configured at least to ascertain an alignment relative to a base station for a targeted docking onto an interface of the base station based on at least one orientation parameter captured using the at least one orientation device.

Abstract: The disclosure relates to a method for mapping a processing area, in particular for determining a processing area, as part of a navigation method for autonomous robot vehicles. According to the disclosure, said method is characterized in that boundary lines between adjoining mapped and unmapped subareas of the processing area that is to be mapped are identified by comparing distances traveled by the robot vehicle during an initial mapping trip within the processing area, mapping of an unmapped subarea adjoining a boundary line is initiated from a point on one of those identified boundary lines during another mapping trip of the robot vehicle into the unmapped subarea, and a map of the processing area is created on the basis of the subareas mapped by the robot vehicle.

Abstract: An autonomous implement includes at least one orientation device configured to provide an orientation within a processing zone. The at least one orientation device is different from a perimeter-wire orientation device. The autonomous implement further includes at least one control and/or regulating unit configured to ascertain a travel strategy. The at least one control and/or regulating unit is configured at least to ascertain an alignment relative to a base station for a targeted docking onto an interface of the base station based on at least one orientation parameter captured using the at least one orientation device.

Abstract: An autonomous working device, in particular an autonomous lawn mower, is configured to travel across a surface that is to be worked. The working device includes a processing unit configured to divide the surface that is to be worked into at least two dynamic partial surfaces to be traveled across separately by the working device.

Abstract: An autonomous implement, in particular an autonomous lawnmower, includes at least one computing unit configured to travel over an area to be worked. The computing unit is configured at least partly to automatically initialize relocalization in at least one operating state.

Abstract: An autonomous working device, in particular an autonomous lawn mower, comprising a computing unit. The autonomous working device is configured to cover a surface to be treated in strips. The computing unit is configured to adjust an overlap of the strips according to at least one parameter.

Abstract: An autonomous implement comprising at least one drive unit including at least one drive wheel, at least one sensor unit configured to detect at least one characteristic value, at least one location-determining unit configured to detect at least one characteristic value, and at least one evaluating unit. The at least one evaluating unit is configured to determine a slip of the at least one drive wheel from the at least one characteristic value detected by the at least one sensor unit and the at least one characteristic value detected by the at least one location-determining unit.

Abstract: The disclosure relates to a method for processing a surface by means of a robotic vehicle, wherein the robotic vehicle has a control system in which data concerning the outline of the surface to be processed are stored, wherein locating means are present, which determine the position of the robotic vehicle, in particular in relation to the surface to be processed, and wherein the method comprises the following steps: dividing the surface to be processed into individual segments; classifying each individual segment into a property class; and moving to and processing each individual segment in succession, each individual segment being processed with a processing strategy corresponding to its property class.

Abstract: A self-controlling vehicle, designed for the autonomous movement in an area, is disclosed. The self-controlling vehicle includes driving means for movement and navigation means, wherein the navigation means are designed for the position determination along a closed path surrounding an operating space of the area. The navigation means are designed for creating successive path sectional data, the path sectional data for route sections of the path has assigned orientation information, in particular angle information, and the navigation means are assigned with autocorrelation means, which are designed such that they determine from a sequence of path sectional data corresponding to a movement along the path by determining auto correlation data whether and/or that the vehicle has driven completely along the surrounding path and/or a sequence of route sections already driven is driven again.

Abstract: An autonomous implement comprising at least one drive unit including at least one drive wheel, at least one sensor unit configured to detect at least one characteristic value, at least one location-determining unit configured to detect at least one characteristic value, and at least one evaluating unit. The at least one evaluating unit is configured to determine a slip of the at least one drive wheel from the at least one characteristic value detected by the at least one sensor unit and the at least one characteristic value detected by the at least one location-determining unit.

Abstract: An autonomous working device, in particular an autonomous lawn mower, is configured to travel across a surface that is to be worked. The working device includes a processing unit configured to divide the surface that is to be worked into at least two dynamic partial surfaces to be traveled across separately by the working device.