A device for searching a parking space includes at least one space detection sensor mounted on a vehicle, and a controller that analyzes sensed information obtained through the space detection sensor to recognize space and object information within a parking lot, predicts a distribution of available parking spaces in the parking lot based on the recognized space and object information, and determines an optimal available parking space based on the distribution of the available parking spaces and characteristics of a driver.

A method and an assistance device assist automated driving operation of a motor vehicle. Surroundings raw data recorded by way of a surroundings sensor system of the motor vehicle are processed by the assistance device in order to generate semantic surroundings data. This is accomplished by carrying out semantic object recognition. Further, a comparison of predefined semantically annotated map data against the semantic surroundings data is performed. This involves static objects indicated in the map data being identified in the semantic surroundings data as far as possible. Discrepancies detected during the process are used to recognize perception errors of the assistance device. A recognized perception error prompts a predefined safety measure to be carried out.

Provided is an image processing method. The image processing method includes receiving images acquired from a plurality of vehicles positioned on a road; storing the received images according to acquisition information of the received images; determining a reference image and a target image based on images having the same acquisition information among the stored images; performing an image registration using a plurality of feature points extracted from each of the determined reference image and target image; performing a transparency process for each of the reference image and the target image which are image-registered; extracting static objects from the transparency-processed image; and comparing the extracted static objects with objects on map data which is previously stored and updating the map data when the objects on the map data which is previously stored and the extracted static objects are different from each other.

In one embodiment, a system includes a controller. The controller is configured to perform operations including obtaining data about an area related to a user, determining vacancy information about the area based on the data, determining at least one of an accessibility and a usability of the area, determining that the area is available for occupancy by one or more mobile units based on the vacancy information and at least one of the accessibility and the usability of the area, and updating a map including the area with an indication that the area is available for occupancy by one or more mobile units.

Embodiments of the present invention disclose a map construction method, apparatus, and storage medium. The method includes the following steps: acquiring sensor data collected by a preset sensor; establishing a pose constraint relationship of a movable object and a semantic constraint relationship of a semantic object according to the sensor data; performing a joint optimization solution according to the pose constraint relationship and the semantic constraint relationship to determine a semantic result of the semantic object and a pose result of the movable object; and constructing a semantic map and a point cloud map according to the semantic result and the pose result. By adopting the above technical solution, the semantic map and the point cloud map can be obtained quickly and accurately, thereby obtaining a more accurate high-definition map.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for lighting adaptive navigation. In some implementations, map data associated with a property is received. Sensor data is obtained. Based on the map data and the sensor data, a lighting scenario is determined. Based on the lighting scenario, a modification to at least one of the lighting scenario, to a planned navigation path for the robotic device, to settings for a sensor of the robotic device, to a position for a sensor of the robotic device, or to a position of the robotic device is determined. An action is performed by based on the one or more modifications.

The invention relates to a method for generating and/or updating a digital model of at least one sub-region of a digital map, said digital model being assembled from sections originating from different sources. First data are provided relating to a first section and comprising objects and/or feature points characterized at least by their spatial position, said objects and/or feature points being classifiable into a plurality of degrees of detail. Second data are then provided, relating to a second section and comprising objects and/or feature points characterized at least by their spatial position, said objects and/or feature points being classifiable into the plurality of degrees of detail. The first section and the second sections partially overlap. The method, which is preferably implemented in a backend, includes aligning the first section and the second section relative to each other by minimizing a target functional, which has a weighted error term for each degree of detail of the plurality of degrees of detail, in one or more processors, wherein each error term describes a weighted deviation between the objects and/or feature points of the first section and the corresponding objects and/or feature points of the second section.

A method and system for determining a geographical location and orientation of a vehicle travelling through a road network is disclosed. The method comprises obtaining, from one or more cameras associated with the vehicle travelling through the road network, a sequence of images reflecting the environment of the road network on which the vehicle is travelling, wherein each of the images has an associated camera location at which the image was recorded. A local map representation representing an area of the road network on which the vehicle is travelling is then generated using at least some of the obtained images and the associated camera locations. The generated local map representation is compared with a section of a reference map, the reference map section covering the area of the road network on which the vehicle is travelling, and the geographical location and orientation of the vehicle within the road network is determined based on the comparison. Methods and systems for generating and/or updating an electronic map using data obtained by a vehicle travelling through a road network represented by the map are also disclosed.

An approach is provided for automatically coding cartographic feature(s), e.g., human settlement(s). The approach involves receiving data point(s) associated with point location(s) and indicative of a cartographic feature. The approach also involves retrieving or generating a cartographic feature polygon corresponding to the cartographic feature based on the data point(s). The approach further involves generating a plurality of polygon data points that replicate the cartographic feature polygon, and/or a spider web model that represents the point location(s). The approach further involves retrieving imagery data depicting the cartographic feature based on the plurality of polygon data points and/or the spider web model. The approach further involves merging the data point(s), the plurality of polygon data points, and/or the imagery data to generate new or updated polygon structure data point(s) to represent the cartographic feature. The approach further involves storing the new or updated polygon structure data point(s) in a map database.

Techniques for improving the display of markers on a map include pre-computing cells for multiple locations on the map and associating points of interest with the pre-computed cells. In response to a request from a user device to display points of interest for a particular location, stored data specifying the pre-computed cells for the particular location is accessed and, for each of the cells, a point of interest is selected from the points of interests associated with that cell. The user device is caused to display the map with a marker in each of the cells for the selected point of interest.