Here Global B.v.

Digitalglobe, Incorporated

Microsoft Technology Licensing, LLC

Intermap Technologies Inc.

Carolyn Johnston

Jan Van Sickle

Robert Ledner

Timm Kayser

Dietmar Rabel

Eric Dieckman

James Thomas Smith, Ii

Brett W Bader

Laurence C Bleiler

Ozy Sjahputera

Stephen Charles Griffiths

Natalie Findlay

Systems and methods of automating the generation of a correction of an estimate of an elevation of a digital elevation model (DEM) of the bare earth under forest canopy. The disclosed embodiments facilitate generation of a more accurate DEM in areas of canopy coverage (where the input X-band DSM cannot see the ground) to estimate both the canopy height and the associated DEM. In some embodiments, the result of computationally correcting an estimate of an original DEM is a modified DEM. The method of correcting an estimate of an original DEM utilizes a pair of P-band radar images, an original DEM overlapping the same scene as the P-band radar images, at least one common, uniquely-identifiable point in the P-band radar images, and a definition of a geographical area surrounding the common, uniquely identifiable point over which the elevation correction is applicable.

System and methods for correcting terrain elevations under forest canopy

An apparatus onboard a vehicle and in communication with sensors onboard the vehicle is configured to receive a maplet request identifying a request region; determine that the apparatus has entered the request region; process and fuse sensor data captured by two or more sensors of the sensors to generate a multi-sensor data stream comprising a plurality of observations corresponding to a portion of a road network; generate a maplet based on the multi-sensor data stream and the maplet request, wherein generating the maplet comprises using a predetermined data model to encode road data, from the multi-sensor data stream, corresponding to at least one environment element of the road network; and provide the maplet such that a network apparatus receives the maplet. The network apparatus is configured to (a) validate or (b) update map data of a digital map representing the road network based at least in part on the maplet.

Maplets for maintaining and updating a self-healing high definition map

An apparatus is onboard a vehicle and in communication with sensors onboard the vehicle. The apparatus receives a maplet request identifying a request region; and, responsive to determining that the vehicle is within the request region, processes sensor data captured by sensors to generate a multi-sensor data stream corresponding to a road network segment. The apparatus identifies an observation corresponding to a pole-like object within the multi-sensor data stream; and generates a maplet based on the observation and the maplet request. Generating the maplet comprises using a predetermined data model and a predetermined data format corresponding to a pole-like object observation class to encode road data corresponding to the observation corresponding to the pole-like object. The apparatus provides the maplet such that a network apparatus receives the maplet. The network apparatus is configured to validate/update map data of a digital map representing the road network based on the maplet.

An apparatus is onboard a vehicle and in communication with sensors onboard the vehicle. The apparatus receives a maplet request identifying a request region; and, responsive to determining that the vehicle is within the request region, processes sensor data captured by sensors to generate a multi-sensor data stream corresponding to a road network segment. The apparatus identifies an observation corresponding to a construction marker within the multi-sensor data stream; and generates a maplet based on the observation and the maplet request. Generating the maplet comprises using a predetermined data model and a predetermined data format corresponding to a construction marker observation class to encode road data corresponding to the observation corresponding to the construction marker. The apparatus provides the maplet such that a network apparatus receives the maplet. The network apparatus is configured to validate/update map data of a digital map representing the road network based on the maplet.

An apparatus is onboard a vehicle and in communication with sensors onboard the vehicle. The apparatus receives a maplet request identifying a request region; and, responsive to determining that the vehicle is within the request region, processes sensor data captured by sensors to generate a multi-sensor data stream corresponding to a road network segment. The apparatus identifies an observation corresponding to a traffic signal within the multi-sensor data stream; and generates a maplet based on the observation and the maplet request. Generating the maplet comprises using a predetermined data model and a predetermined data format corresponding to a traffic signal observation class to encode road data corresponding to the observation corresponding to the traffic signal. The apparatus provides the maplet such that a network apparatus receives the maplet. The network apparatus is configured to validate/update map data of a digital map representing the road network based on the maplet.

An apparatus is onboard a vehicle and in communication with sensors onboard the vehicle. The apparatus receives a maplet request identifying a request region; and, responsive to determining that the vehicle is within the request region, processes sensor data captured by sensors to generate a multi-sensor data stream corresponding to a road network segment. The apparatus identifies an observation corresponding to a road marking within the multi-sensor data stream; and generates a maplet based on the observation and the maplet request. Generating the maplet comprises using a predetermined data model and a predetermined data format corresponding to a road marking observation class to encode road data corresponding to the observation corresponding to the road marking. The apparatus provides the maplet such that a network apparatus receives the maplet. The network apparatus is configured to validate/update map data of a digital map representing the road network based on the maplet.

A new drive includes a plurality of instances of location data that are received. The location data was captured by a probe apparatus onboard a vehicle as the vehicle traversed a lane network. The plurality of instances of location data are map matched using a lane level map matcher. The matched nodes (e.g., nodes of the LNG model representing the lane network to which an instance of location data was map matched) are identified and updated based on the new drive. Unmatched instances of location data (e.g., instances of location data that cannot be satisfactorily matched to a node of the LNG model) may be used to generate new nodes of the LNG model. A portion of the LNG model may be updated based on an update to a linked localization layer.

Generation and update of a lane network graph model

A Metric Information Network (MIN) with a plurality of Ground Control Points (GCPs) that are selected in an automated fashion. The GCP selection includes clustering algorithms as compared to prior art pair-wise matching algorithms. Further, the image processing that takes place in identifying interest points, clustering, and selecting tie points to be GCPs is all performed before the MIN is updated. By arranging for the processing to happen in this manner, the processing that is embarrassingly parallel (identifying interest points, clustering, and selecting tie points) can be performed in a distributed fashion across many computers and then the MIN can be updated.

Automated metric information network

One or more techniques and/or systems are disclosed for matching entity names. A matching analysis is performed between a first entity name (e.g., business entity name) and a second entity name. The matching analysis comprises comparing a first entity category descriptor that has been amended into the first entity name with a second entity category descriptor that has been amended into the second entity name. If a match is identified in the category descriptors, the first and second entity names may comprise the same entity.

Growing community of inventors

Eindhoven, Netherlands

Carolyn Johnston