Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive data from a sensor specifying a plurality of points, the points including a plurality of first points that describe an object; define a boundary surrounding the first points while minimizing a volume of space that is both (i) contained by the boundary and (ii) identified as unoccupied; and actuate a component with respect to a vehicle based on the boundary.

Abstract: A reference pose graph can be generated from first point cloud data collected at each of a plurality of mobile nodes. A location of a stationary node can be specified based on the reference pose graph and second point cloud data collected by the stationary node.

Abstract: A system includes a computer including a processor and a memory storing instructions executable by the processor to identify a location and an orientation of a vehicle on a map. The instructions include instructions to determine a location of an infrastructure sensor on the map based on the location and the orientation of the vehicle, data from a vehicle sensor, and data from the infrastructure sensor.

Abstract: A reference pose of an object in a coordinate system of a map of an area is determined. The reference pose is based on a three-dimensional (3D) reference model representing the object. A first pose of the object is determined as the object moves with respect to the coordinate system. The first pose is determined based on the reference pose and sensor data collected by the sensor at a first time. A second pose of the object is determined as the object continues to move with respect to the coordinate system. The second pose is determined based on the reference pose, the first pose, and sensor data collected by the sensor at a second time consecutive to the first time.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive data from a sensor specifying a plurality of points, the points including a plurality of first points that describe an object; define a boundary surrounding the first points while minimizing a volume of space that is both (i) contained by the boundary and (ii) identified as unoccupied; and actuate a component with respect to a vehicle based on the boundary.

Abstract: A system includes a processor and a memory. The memory stores instructions executable by the processor to select a technique, from a plurality of techniques, to identify a vehicle location by sensor and map data based on features detected in sensor data of an area in which the vehicle is located, to determine a location of the vehicle based on the selected technique; and to navigate the vehicle based at least in part on the identified location.

Abstract: A computer includes a processor and a memory. The memory stores instructions executable by the processor to receive in a host vehicle, from a target vehicle via wireless vehicle-to-vehicle communications, a target vehicle first location in a global coordinate system, determine a target vehicle second location in a local coordinate system that has an origin at the host vehicle, and identify a host vehicle location in the global coordinate system based solely on (i) local coordinate system data determined in the host vehicle, including the target vehicle second location and (ii) data in the vehicle-to-vehicle communications, including the target vehicle first location.

Abstract: A system includes a processor and a memory. The memory stores instructions executable by the processor to define a plurality of volumes represented in an original set of point cloud data. The memory stores instructions executable by the processor to define a respective set of sub-volumes in each of the volumes, and to generate a reduced set of point cloud data including a number of points counted in selected sub-volumes.

Abstract: A system includes a processor and a memory. The memory stores instructions executable by the processor to determine a plurality of waypoints for mapping an area by analyzing a received aerial image of the area, to select an optimal number of the waypoints for mapping, and to actuate the vehicle to traverse a route determined to cover the selected waypoints.

Abstract: A reference pose graph can be generated from first point cloud data collected at each of a plurality of mobile nodes. A location of a stationary node can be specified based on the reference pose graph and second point cloud data collected by the stationary node.

Abstract: A system includes a processor and a memory. The memory stores instructions executable by the processor to receive sensor data including floating-point numbers. The memory stores instructions to convert the floating-point numbers to integer numbers based on a parameter set. The memory stores instructions to actuate a vehicle component based on the integer numbers.

Abstract: A system includes a processor and a memory. The memory stores instructions executable by the processor to generate, from LIDAR data, a first intensity map of an area around a vehicle, and to estimate a vehicle location based on comparing the first intensity map to a grayscale top view image.

Abstract: A system includes a processor and a memory. The memory stores instructions executable by the processor to select a technique, from a plurality of techniques, to identify a vehicle location by sensor and map data based on features detected in sensor data of an area in which the vehicle is located, to determine a location of the vehicle based on the selected technique; and to navigate the vehicle based at least in part on the identified location.

Abstract: A system includes a processor and a memory. The memory stores instructions executable by the processor to define a plurality of volumes represented in an original set of point cloud data. The memory stores instructions executable by the processor to define a respective set of sub-volumes in each of the volumes, and to generate a reduced set of point cloud data including a number of points counted in selected sub-volumes.

Abstract: A system includes a processor and a memory. The memory stores instructions executable by the processor to determine a plurality of waypoints for mapping an area by analyzing a received aerial image of the area, to select an optimal number of the waypoints for mapping, and to actuate the vehicle to traverse a route determined to cover the selected waypoints.

Abstract: A system includes a processor and a memory. The memory stores instructions executable by the processor to receive sensor data including floating-point numbers. The memory stores instructions to convert the floating-point numbers to integer numbers based on a parameter set. The memory stores instructions to actuate a vehicle component based on the integer numbers.

Abstract: This disclosure relates to systems and methods that include receiving media content from a content submitter, classifying the media content by initiating one of synchronous classification and asynchronous classification based on a type of the media content, generating a media content certificate based on the media type, the certificate including results of the classification, storing the media content certificate with the media content, and filtering the media content based on at least one of an identity of the content submitter, the results of the classification, and the media content including malicious content.

Abstract: In various example embodiments, a system and method for generating a filtering spam content using machine learning are presented. One or more electronic content is received. The one or more electronic content is labeled as spam or not spam by a current spam filtering system. An associated accuracy score for each of the one or more labeled content is calculated. Potential errors in the one or more labeled content is identified based on the label of the one or more labeled content being inconsistent with information associated with the source of the one or more labeled content. The one or more labeled content with identified potential errors is sent for assessment. The one or more electronic content labeled as spam with an associated accuracy score within a predetermined range is filtered, excluding labeled content with identified potential errors.

Abstract: This disclosure relates to systems and methods that include receiving media content from a content submitter, classifying the media content by initiating one of synchronous classification and asynchronous classification based on a type of the media content, generating a media content certificate based on the media type, the certificate including results of the classification, storing the media content certificate with the media content, and filtering the media content based on at least one of an identity of the content submitter, the results of the classification, and the media content including malicious content.