An information processing device (100) includes a map information generation unit (11) and a usage amount calculation unit (12). The map information generation unit (11) generates map information by using measurement information including a plurality of types of information measured by a measurement device (300) which measures information on features and is mounted on a measurement vehicle (310). The usage amount calculation unit (12) calculates a usage amount of the map information generation unit (11) used for generating the map information by using at least one of the plurality of types of information included in measurement information.

In one embodiment, a system and method for point cloud registration of LIDAR poses of an autonomous driving vehicle (ADV) is disclosed. The method selects poses of the point clouds that possess higher confidence level during the data capture phase as fixed anchor poses. The fixed anchor points are used to estimate and optimize the poses of non-anchor poses during point cloud registration. The method may partition the points clouds into blocks to perform the ICP algorithm for each block in parallel by minimizing the cost function of the bundle adjustment equation updated with a regularity term. The regularity term may measure the difference between current estimates of the poses and previous or the initial estimates. The method may also minimize the bundle adjustment equation updated with a regularity term when solving the pose graph problem to merge the optimized poses from the blocks to make connections between the blocks.

A vehicle control system includes a communication circuit, an internal sensor, and a controller connected to the communication circuit and the internal sensor. The controller is configured to detect an impact to a vehicle through the internal sensor, calculate an impulse for the detected impact, estimate a bump shape based on the calculated impulse, match first bump information that represents the estimated bump shape and second bump information acquired from a database by using the communication circuit, and update bump information of the database based on a matching result.

The presently disclosed subject matter includes a system and a method of navigating an unmanned ground vehicle (UGV) vehicle comprising a scanning device and an Inertial Navigation System (INS) being operatively connected to at least one processor. Operating the scanning device for scanning an area surrounding the UGV, and generate scanning output data; Generating, based on the scanning output data, a map representing at least a part of the area, the map being relative to a location of the UGV and comprising cells, each cell is classified to a class selected from at least two classes, comprising traversable and non-traversable, and characterized by dimensions larger than an accumulated drift value of the INS over a predefined distance; receiving INS data indicative of a current location of the UGV and updating a location of the UGV relative to cells in the map based on the INS data.

The present invention provides a technique to accurately recognize a position of a vehicle even in a vicinity of a branch road or a junction road, neither of which is included in map data. The present invention provides a vehicle control device. When a vehicle is traveling on a road that is not described in map data, the vehicle control device is configured to determine whether or not the vehicle is traveling on a junction road or a branch road, based on a positional relationship between a position of the vehicle and a starting point of the junction road or a starting point of the branch road.

A system and method of navigating a vehicle, the vehicle comprising a scanning device and a self-contained navigation system (SCNS) operatively connected to a computer, the method comprising: operating the scanning device for repeatedly executing a scanning operation, each operation includes scanning an area surrounding the vehicle, thereby generating respective scanning output data; operating the computer for generating, based on the scanning output data, a relative map representing at least a part of the area, the map having known dimensions and being relative to a position of the vehicle, wherein the map comprises cells, each cell classified to a class from at least two classes, comprising traversable and non-traversable, and characterized by dimensions equal or larger than an accumulated drift value of the SCNS; wherein non-traversable cells correspond to identified obstacles; receiving SCNS data and updating a position of the vehicle relative to the cells based on the SCNS data.

The data transmission device includes a processor configured to: acquire data based on a sensor signal from a sensor mounted on a vehicle repeatedly at a predetermined time interval, determine a selection cycle based on a movement speed of the vehicle and selects one or more sets of data from the repeatedly acquired data for each determined selection cycle, and transmit the selected one or more sets of data to an external server.

Systems and methods to localize objects for mapping applications may comprise a vehicle having an imaging device, a location sensor, and an edge processor. Using imaging data from the imaging device, location data from the location sensor, and bounding box data associated with objects, three-dimensional models of environments may be reconstructed using structure from motion algorithms and/or direct triangulation algorithms. After aligning the reconstructions to real-world environments based on the location data, objects may be accurately localized relative to real-world environments.

Embodiments relate to methods for efficiently encoding sensor data captured by an autonomous vehicle and building a high definition map using the encoded sensor data. The sensor data can be LiDAR data which is expressed as multiple image representations. Image representations that include important LiDAR data undergo a lossless compression while image representations that include LiDAR data that is more error-tolerant undergo a lossy compression. Therefore, the compressed sensor data can be transmitted to an online system for building a high definition map. When building a high definition map, entities, such as road signs and road lines, are constructed such that when encoded and compressed, the high definition map consumes less storage space. The positions of entities are expressed in relation to a reference centerline in the high definition map. Therefore, each position of an entity can be expressed in fewer numerical digits in comparison to conventional methods.

The present disclosure generally relates to a methods and systems for compensating for changes in the absolute position of locations with respect to the Earth's surface which occur over time due to crustal dynamics. The invention is particularly, although not exclusively, concerned with such compensation in the context of methods using digital map data, for example, methods of localization of a vehicle.