Abstract: Disclosed are systems and methods for predicting the destination location of a vehicle by processing a local preference graph of a user of the vehicle having nodes corresponding to locations visited by the user. In some embodiments, information about locations which have been visited one after another by users and the time between visits of the locations are also used in the prediction.

Abstract: A travel amount estimation apparatus includes a vehicle travel amount calculation unit, a sensor travel amount calculation unit, an error cause determination unit, and a vehicle travel amount correction unit. The vehicle travel amount calculation unit acquires vehicle information and calculates a vehicle travel amount based on the vehicle information. The sensor travel amount calculation unit acquires sensor information from an external sensor and calculates a sensor travel amount based on the sensor information. The error cause determination unit determines an error cause of the vehicle travel amount. The vehicle travel amount correction unit corrects the vehicle travel amount by using the sensor travel amount in accordance with the error cause and estimates a travel amount of the vehicle on which it is mounted.

Abstract: Trailer coupling assembly arranged to a support structure of a vehicle or support structure of a trailer, wherein the trailer coupling assembly comprises a tow bar or a connection head/trailer hitch, wherein it comprises an intermediate connection device enabling movement of the tow bar or connection head/trailer hitch in a vertical direction and/or longitudinal direction of the vehicle or trailer, respectively. A vehicle with trailer coupling assembly movable in at least a vertical direction and/or longitudinal direction of the vehicle.

Abstract: An object-tracking method includes using the velocity of a track for tracking an object, generated from a point cloud related to the object, in a current recognition period to obtain a current velocity-based heading angle of the track. The method includes accumulating scores associated with information about the current velocity-based heading angle and incorporating the accumulated scores into a heading history having regions sectioned for respective heading angles of the track. The method includes obtaining a history-based heading angle of the track using the heading history, correcting the history-based heading angle using information about the shape of the track, and determining the result of correction to be a final heading angle in the current recognition period.

Abstract: The present disclosure relates to a method for calibrating a position of a matrix headlamp of a motor vehicle by means of a camera of the motor vehicle, wherein the matrix headlamp has a plurality of segments controllable independently of one another for light emission. At least one first image of a sign is recorded by means of the camera, a location area in which the sign is arranged is determined, illuminance of a first segment is changed, at least one second image is recorded and checked, whether a change in a glare effect detected on the basis of the at least one recorded second image has occurred, and if so, the position of the matrix headlamp is calibrated depending on the first segment and position information derived from the location area.

Abstract: Disclosed are techniques for navigating a mobile machine, such as an autonomous robot, in an environment that includes objects that may block, reflect, or distort satellite signals to be used for positioning. Satellite data may be captured from one or more satellites. An image may be captured using an imaging device that is at least partially oriented toward the one or more satellites. A set of sky scores may be calculated for a set of ground positions surrounding the mobile machine based on the satellite data and the image. Each of the set of sky scores may be indicative of an accuracy of a satellite-based position at one of the set of ground positions. The mobile machine's navigation may be modified using the set of sky scores.

Abstract: A vehicle position identification device or a vehicle position identification method for a vehicle acquires first landmark position information including a landmark distance with respect to a subject vehicle, acquires second landmark position information including a landmark elevation angle, estimates a landmark position, acquires map data including a landmark position on a map, and identify a vehicle position on the map.

Abstract: An information processing device includes: a processor configured to: collect monitoring information indicating circumstances of a monitoring area from a plurality of monitoring information acquiring units, detect an object which is located in the monitoring area on the basis of the monitoring information, update map information of the monitoring area using position information indicating a position of the object, and provide the map information to a working machine that performs predetermined work in the monitoring area.

Abstract: An autonomous mobile device (AMD) may move around a physical space while performing tasks. Sensor data is used to determine an occupancy map of the physical space. Some objects within the physical space may be difficult to detect because of characteristics that result in lower confidence in sensor data, such as transparent or reflective objects. To include difficult-to-detect objects in the occupancy map, image data is processed to identify portions of the image that includes features associated with difficult-to-detect objects. Given the portion that possibly includes difficult-to-detect objects, the AMD attempts to determine where in the physical space that portion corresponds to. For example, the AMD may use stereovision to determine the physical area associated with the features depicted in the portion. Objects in that area are included in an occupancy map annotated as objects that should persist unless confirmed to not be within the physical space.

Abstract: Techniques associated with predicting behaviors and states of objects in a physical environment using thermal data.. In some cases, the system may be configured to determine heat signatures of individual features of an object and based on a combination of heat signatures determine a predicted behavior and/or a state of the object. The system may also utilize the thermal data to determine a confidence associated with predicted behavior and/or states of the object.

Abstract: A method of simultaneous localization and mapping (SLAM) is provided to position a target object. Each of detected tracked objects in a surrounding environment of the target object is classified into a moving object or a static object based on data detected at different time points. The target object is then positioned without considering any of the tracked objects that are classified into a moving object.

Abstract: An apparatus for identifying the state of an object inputs time series images into a first classifier to detect an object region including a predetermined object from each image, determines whether the region of each image is in a mixed state in which the region includes another object other than the object, chronologically inputs characteristics obtained from pixel values of the region of each image into a second classifier having a recursive structure, and applies a recursively used internal state of the second classifier stored in a memory to the second classifier, identifying the state of the object involving time-varying changes in outward appearance. The apparatus rejects the latest internal state when the region of each image is in the mixed state. The apparatus updates the internal state stored in the memory with this latest internal state when the region is not in the mixed state.

Abstract: An artificial intelligence (AI) device installed in a first vehicle includes a sensing unit configured to sense an area in which the first vehicle is moveable at a current position, and a processor configured to receive a request for assignment of control authorization for allowing a first external vehicle to control the first vehicle from the first external vehicle, based on information sensed by the sensing unit, or to make a request to the second external vehicle for assignment of control authorization for allowing the AI device to control a second external vehicle.

Abstract: A method of controlling a mobile work machine on a worksite includes receiving an indication of an object detected on the worksite, determining a location of the object relative to the mobile work machine, receiving an image of the worksite, correlating the determined location of the object to a portion of the image, evaluating the object by performing image processing of the portion of the image, and generating a control signal that controls the mobile work machine based on the evaluation.

Abstract: A system comprising a computer including a processor and a memory, the memory including instructions such that the processor is programmed to: process vehicle sensor data with a deep neural network to generate a prediction indicative of one or more objects based on the data and determine an object uncertainty corresponding to the prediction and when the object uncertainty is greater than an uncertainty threshold, segment the vehicle sensor data into a foreground portion and a background portion. Classify the foreground portion as including an unseen object class when a foreground uncertainty is greater than a foreground uncertainty threshold; classify the background portion as including unseen background when a background uncertainty is greater than a background uncertainty threshold; and transmit the data and a data classification to a server.

Abstract: A method in accordance with the invention controls movements of an actor, such as an autonomous vehicle. The method includes collecting one or more data sets of location information from sources that include a first actor, a second actor, and a fixed agent. Each data set indicates a current location of an object from one or more objects. The method also includes merging the data sets to generate a second set of current location information of the one or more objects, filtering the second set of current location information to remove location information of static objects to generate a subset of the current locations corresponding to a subset of the objects, using the subset of current locations to predict future locations of the subset of objects, and coordinating the movement of the first actor based on the predicted future locations to optimize one or more pre-determined criteria.

Abstract: An apparatus for detecting an inclination angle includes a processor configured to input an image generated by a camera into a first classifier that has been trained to detect a two-wheeler, thereby detecting an object region including the two-wheeler in the image; rotate the object region by predetermined different angles to define characteristic regions as respective rotated regions; cut out the characteristic regions from the image; and detect a width of the two-wheeler in each of the characteristic regions and detects a rotation angle relative to the image as the inclination angle of the two-wheeler to the normal of the ground, based on rotation angles of the respective characteristic regions relative to the image and widths of the two-wheeler in the respective characteristic regions, the rotation angle minimizing the width of the two-wheeler.

Abstract: Various embodiments include methods for improving navigation by a processor of a robotic device. Such embodiments may include initiating a start of a predetermined time period associated with semantic information extraction, and determining whether an adverse event related to one or more sensors of the robotic device is detected. Such embodiments may also include identifying a current time slot of the predetermined time period, identifying a current estimated position and orientation of the robotic device, and recording updates to semantic information stored for the one or more sensor based on the identified current time slot and the current estimated position and orientation of the robotic device in response to determining that an adverse event related to one or more sensors of the robotic device is detected.

Abstract: A method for controlling rights of an autonomous vehicle includes acquiring, via a network, identification information for identifying a user or a terminal of the user, and dispatching request information that indicates a dispatch request for the autonomous vehicle issued by the user. The method further includes selecting the autonomous vehicle to be dispatched to the user from among multiple autonomous vehicles based on the dispatch request information, and assigning a control right for the selected autonomous vehicle, to the user or the terminal, based on the identification information.

Abstract: A modular electronic damping control system is described and includes a damping component located at a vehicle suspension location. The modular electronic damping control system also includes a control system configured to control the damping component, and determine the type of damping component present. Also, the control system is configured to automatically tune a vehicle's suspension based on the type of damping component present, and automatically monitor the damping component and determine when a change has been made to the damping component so that the control system can then automatically re-tune the vehicle's suspension based on the change to the damping component.