While a vehicle is in an area, a stored map uncertainty value of map data for the area is retrieved. The stored map uncertainty value gives a range of uncertainty for at least one indicator of a travel path specified by the map data. Upon estimating the travel path and a vehicle pose, a dynamic map uncertainty value is determined based on a pose uncertainty value and a travel path uncertainty value. The pose uncertainty value gives a range of uncertainty for the vehicle pose in three degrees-of-freedom based on vehicle sensor data, and the travel path uncertainty value gives a range of uncertainty for the at least one indicator of the estimated travel path based on vehicle sensor data. Upon determining that the dynamic map uncertainty value is less than the stored map uncertainty value, the map data is updated based on the vehicle sensor data. Upon updating the map data, the vehicle is operated based on the updated map data.

A method of complementing a map of a scene with 3D reference points including four steps. In a first step, data is collected and recorded based on samples of at least one of an optical sensor, a GNSS, and an IMU. A second step includes initial pose generation by processing of the collected sensor data to provide a track of vehicle poses. A pose is based on a specific data set, on at least one data set re-coded before that dataset and on at least one data set recorded after that data set. A third step includes SLAM processing of the initial poses and collected optical sensor data to generate keyframes with feature points. In a fourth step 3D reference points are generated by fusion and optimization of the feature points by using future and past feature points together with a feature point at a point of processing. This second and fourth steps provides significantly better results than SLAM or VIO methods known from prior art, as the second and the fourth steps are based on recorded data. Wherein a normal SLAM or VIO algorithm only can access data of the past, in these steps, processing may also be done by looking at positions ahead, by using the recorded data.

Systems and methods for mapping the distribution of residue material in an environment in which one or more agricultural machines are operable. A sensing arrangement having one or more sensors mounted or otherwise coupled to an agricultural machine operating within the environment is used to obtain sensor data indicative of residue material spread by a spreader tool of the agricultural machine. From this a local distribution of residue material associated with the spreader tool is determined which is used to update a map of a global distribution of the residue material across the environment. The map comprises a grid-based map having a plurality of cells corresponding to sub-regions within the environment, wherein a value associated with each cell is representative of a measure of the residue material present within the corresponding sub-region.

Systems and methods are provided for obtaining characterizations of paths to be traversed, such as foot paths. A scanning tool may be configured to capture information or data characterizing aspects of such a path. The scanning tool may comprise multiple sensors for capturing image/visual data from multiple perspectives, as well as for capturing data reflecting physical features or conditions of the path. Such information can be combined and quantified or otherwise characterized to provide insight into micromobility zones.

An embodiment user equipment includes an image sensor configured to photograph a surrounding image, a display module, a communicator configured to communicate with a server, a database configured to store visual positioning system (VPS) map information based on augmented reality (AR) and two dimensional (2D) map information, and a controller configured to generate 2D route information based on the 2D map information and delivery information received from the server, generate three dimensional (3D) route information based on the delivery information and the VPS map information, and control the display module to display the 2D route information or the 3D route information based on a distance between the user equipment and a point of interest (POI) included in the delivery information, the 3D route information being based on augmented reality.

A system for acquiring data from vehicle in real time for mapping infrastructure using blockchain technology.

A rideshare management system includes: a communicator configured to communicate with a plurality of terminal devices used by a plurality of users; an acquirer configured to acquire use requests from the plurality of users in which a use condition including at least a desired access place is defined; a user arrival situation monitor configured to monitor an arrival situation of the users at a predetermined place derived according to the desired access place; and a service manager configured to search for an available vehicle according to the use condition included in the use requests and determine a vehicle service schedule and configured to determine a user accessing the vehicle at the predetermined place according to the arrival situation of the users monitored by the user arrival situation monitor.

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.

A map updating method and apparatus (800), and a device (900) are disclosed, which can be used in automated driving (Automated driving), intelligent driving (Intelligent Driving), and other fields. The map updating method includes: when an abnormal scenario occurs, obtaining various types of sensing data of the abnormal scenario, calculating a minimum safety boundary based on the sensing data of the abnormal scenario; and updating a map based on the minimum safety boundary obtained through calculation. According to the map updating method, a map updating program can be triggered when the abnormal scenario occurs, without the need to wait for a collection vehicle/crowd-sourcing vehicle. This improves real-time performance of map refreshing, and ensures safety of an automated driving environment.

A method of area coverage planning with replenishment planning includes receiving information of a boundary of the work area, location information of one or more refill stations, and information of a current amount of the material left in the autonomous vehicle, laying a plurality of tracks within the boundary of the work area so as to minimize a total distance of the plurality of tracks, generating a coverage trajectory, and based on (i) the coverage trajectory, (ii) the location information of the one or more refill stations, (iii) the current amount of the material left in the autonomous vehicle, and (iv) a nominal full amount and a nominal consumption rate of the material by the autonomous vehicle, determining one or more logistic points along the coverage trajectory at which a remaining amount of the material reaches a threshold, for each logistic point, generating a replenishment trajectory.