Abstract: A measurement device (10) includes a light source (110), a control unit (120), a light receiving unit (130), and a data generation unit (140). The control unit (120) repeatedly performs scanning with light from the light source (110) in a predetermined range. The light receiving unit (130) detects reflected light of the light of scanning by the control unit (120). The data generation unit (140) computes a distance to a reflection point of reflected light by using the reflected light. An abnormality detection unit (210) acquires measurement data generated by the data generation unit (140). Further, the abnormality detection unit (210) determines presence or absence of an abnormality of the control unit (120) by using at least one of a distance to the reflection point and intensity of the reflected light included in each of a plurality of pieces of the measurement data.

Abstract: A self-position estimation device is mounted on a mobile body and acquires a predicted position of the mobile body. Additionally, the self-position estimation device calculates a difference value between a predicted position of an end point of a lane division line that is obtained based on information on the end point of the lane division line acquired from map information and a measured position of the end point of the lane division line measured in such a manner that a measurement unit mounted on the mobile body performs scanning with a light in a predetermined direction. The self-position estimation device estimates a self-position of the mobile body by correcting the predicted position with a value obtained by multiplying the difference value by a coefficient. Further, the self-position estimation device corrects the coefficient based on an interval of scanning positions of the measurement unit at a position where the end point of the lane division line is detected.

Abstract: A measurement device includes a processor coupled to a memory storing instructions. The processor is configured to acquire positional information of a measurement object stored in a storage unit, acquire point group information of points indicating a surrounding feature acquired by an external sensor, output reliability of the positional information of the measurement object indicating a center position of the measurement object existing in a predetermined range based on the point group information of points existing in the predetermined range, the predetermined range being determined based on a position of a movable body, and estimate a movable body position based on the positional information of the measurement object and the center position of the measurement object, wherein the processor determines the center position by calculating an average value of the point group information existing in the predetermined range.

Abstract: A self-position estimation device is mounted on a mobile body and acquires a predicted position of the mobile body. Additionally, the self-position estimation device calculates a difference value between a predicted position of an end point of a lane division line that is obtained based on information on the end point of the lane division line acquired from map information and a measured position of the end point of the lane division line measured in such a manner that a measurement unit mounted on the mobile body performs scanning with a light in a predetermined direction. The self-position estimation device estimates a self-position of the mobile body by correcting the predicted position with a value obtained by multiplying the difference value by a coefficient. Further, the self-position estimation device corrects the coefficient based on an interval of scanning positions of the measurement unit at a position where the end point of the lane division line is detected.

Abstract: An information processing device for assisting adjustment (calibration) of mounting positions and mounting orientations of lidars mounted on a vehicle, and includes: a position and orientation acquisition unit that acquires the mounting positions and mounting orientations of the lidars with respect to the vehicle; a field-of-view information acquisition unit that acquires field-of-view information of the lidars; a measurement information acquisition unit that acquires measurement information (distance information from the lidars to a reference target for each emission angle) from the lidars; and an image generation unit that creates display data in which guides indicating the fields of view of the lidars are superimposed on 3-D point cloud information of the reference target based on the acquired measurement information.

Abstract: The above measurement device acquires output data from a sensor unit for detecting surrounding feature, and extracts, from the output data, data corresponding to detection result in a predetermined range in a predetermined positional relation with an own position. The predetermined range is determined in accordance with accuracy of the own position. Then, the measurement device executes predetermined processing based on the extracted data.

Abstract: A measurement device includes a first acquisition unit configured to acquire positional information of a measurement object stored in a storage unit, a second acquisition unit configured to acquire point group information of points indicating a surrounding feature acquired by an external sensor, and an output unit configured to output reliability of the positional information indicating a predetermined position of the measurement object existing in a predetermined range based on the point group information existing in the predetermined range.

Abstract: The above measurement device acquires output data from a sensor unit for detecting surrounding feature, and extracts, from the output data, data corresponding to detection result in a predetermined range in a predetermined positional relation with an own position. The predetermined range is determined in accordance with accuracy of the own position. Then, the measurement device executes predetermined processing based on the extracted data.

Abstract: The measurement device acquires positional information of a measurement object stored in a storage unit, and acquires point group information of points indicating a surrounding feature acquired by an external sensor. Then, the measurement device calculates the positional information indicating a predetermined position of the measurement object existing in a predetermined range based on the point group information existing in the predetermined range, and outputs its reliability.

Abstract: The object recognition device acquires external field information from by an external detection device arranged on a movable body, and acquires object position information indicating a position of an object existing around the movable body. Then, the object recognition device extracts prediction information, predicted to include information indicating the object, from the external field information based on the object position information, and recognizes the object based on the prediction information.

Abstract: The object recognition device acquires external field information from by an external detection device arranged on a movable body, and acquires object position information indicating a position of an object existing around the movable body. Then, the object recognition device extracts prediction information, predicted to include information indicating the object, from the external field information based on the object position information, and recognizes the object based on the prediction information.

Abstract: An object of the present invention is to provide a degraded feature identification apparatus and the like that can identify a degraded feature from a large number of features. The present invention receives light emitted from a moving object and reflected by a feature, acquires reflection intensity data measured at the moving object, and identifies a degraded feature based on acquired reflection intensity data.

Abstract: A self-position estimation device is mounted on a mobile body and acquires a predicted position of the mobile body. Additionally, the self-position estimation device calculates a difference value between a predicted position of an end point of a lane division line that is obtained based on information on the end point of the lane division line acquired from map information and a measured position of the end point of the lane division line measured in such a manner that a measurement unit mounted on the mobile body performs scanning with a light in a predetermined direction. The self-position estimation device estimates a self-position of the mobile body by correcting the predicted position with a value obtained by multiplying the difference value by a coefficient. Further, the self-position estimation device corrects the coefficient based on an interval of scanning positions of the measurement unit at a position where the end point of the lane division line is detected.

Abstract: The above measurement device acquires output data from a sensor unit for detecting surrounding feature, and extracts, from the output data, data corresponding to detection result in a predetermined range in a predetermined positional relation with an own position. The predetermined range is determined in accordance with accuracy of the own position. Then, the measurement device executes predetermined processing based on the extracted data.

Abstract: The measurement device acquires output data from a sensor unit for detecting road surface lines around, and determines a predetermined range based on an own position and positional information of broken-line type road surface lines. Then, the measurement device extract, from the output data, data corresponding to detection result of the predetermined range, and executes predetermined processing based on the extracted data.

Abstract: A sever device 4 stores a three-dimensional point cloud DB 43. When receiving, from a vehicle mounted device 1, a point cloud information request signal Sr including LIDAR specification information IL on specifications of a LIDAR 2 and a predicted own vehicle position Ppr, the server device 4 specifies a scan target space by the LIDAR 2. Then, the sever device 4 extracts, from the three-dimensional point cloud DB 43, map point cloud information Da corresponding to a point cloud situated within the specified scan target space, and transmits the map point cloud information Da to the vehicle mounted device 1.

Abstract: The measurement device acquires positional information of a measurement object stored in a storage unit, and acquires point group information of points indicating a surrounding feature acquired by an external sensor. Then, the measurement device calculates the positional information indicating a predetermined position of the measurement object existing in a predetermined range based on the point group information existing in the predetermined range, and outputs its reliability.

Abstract: An object of the present invention is to provide a degraded feature identification apparatus and the like that can identify a degraded feature from a large number of features. The present invention receives light emitted from a moving object and reflected by a feature, acquires reflection intensity data measured at the moving object, and identifies a degraded feature based on acquired reflection intensity data.

Abstract: An enhanced map information processing unit 14 of a driving assistance device 1 acquires from a determination unit 13 information on surroundings of a vehicle which is needed to perform autonomous driving, and acquires from a server device 2 environment information on surroundings of a route on which autonomous driving is performed. On the basis of the acquired environment information, the enhanced map information processing unit 14 extracts, as an autonomous driving unsuitable location Pn, a location at which the accuracy of the acquirement of the sensor unit 12 is predicted not to satisfy a standard for acquiring the information on the surroundings of the vehicle needed to perform autonomous driving. An informing unit 18 alerts the extracted autonomous driving unsuitable location Pn to a user.

Abstract: The object recognition device acquires external field information from by an external detection device arranged on a movable body, and acquires object position information indicating a position of an object existing around the movable body. Then, the object recognition device extracts prediction information, predicted to include information indicating the object, from the external field information based on the object position information, and recognizes the object based on the prediction information.