One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

A method of collecting visual data using a mobile image capture device is provided. The method comprises the steps of: capturing image data with the mobile image capture device and associating time and location data with each image; and storing the image data and associated time and location data. The method further comprises monitoring the position and orientation of the image capture device. The method further comprises: defining an area surrounding or next to the location of the mobile image capture device; and identifying a characteristic of the defined area based on one or more of: the density of the image data in the area; the age of the image data in the area; and/or data demand values associated with locations within the defined area. The timing of capture of image data is based on the characteristic of the defined area.

The disclosure describes systems (2) of navigating a hazardous environment (8). The system includes personal protective equipment (PPE) (13) and computing device(s) (32) configured to process sensor data from the PPE (13), generate pose data of an agent (10) based on the processed sensor data, and track the pose data as the agent (10) moves through the hazardous environment (8). The PPE (13) may include an inertial measurement device to generate inertial data and a radar device to generate radar data for detecting a presence or arrangement of objects in a visually obscured environment (8). The PPE (13) may include a thermal image capture device to generate thermal image data for detecting and classifying thermal features of the hazardous environment (8). The PPE (13) may include one or more sensors to detect a fiducial marker (21) in a visually obscured environment (8) for identifying features in the visually obscured environment (8). In these ways, the systems (2) may more safely navigate the agent (10) through the hazardous environment (8).

A method for reconstructing a motion track applied to a terminal is provided. The method includes: obtaining a data set, the data set including positioning data obtained by positioning a target object; performing data fitting on target data in the data set to obtain a plurality of segments of first curves, the target data being positioning data obtained by performing noise filtering on the data set; and determining a motion track of the target object based on the plurality of segments of first curves. Counterpart apparatus and non-transitory computer-readable storage medium embodiments are also contemplated.

A position estimation unit 25 estimates, for each movement in a predetermined section, a plurality of position candidates of a position estimation target on the basis of position information and sensor information. A position determination unit 26 evaluates, for each movement in the predetermined section, on the basis of the plurality of position candidates of the position estimation target obtained by the movement in the predetermined section, whether the position information used to estimate the position candidates has an error caused by any of a position of a GPS satellite, a position of a mobile body in a real space, or the mobile body or does not have any error caused thereby. The position determination unit 26 determines a final output value of the position of the position estimation target on the basis of a result obtained by removing, from the plurality of estimated position candidates of the position estimation target in the plurality of times of the movement in the predetermined section, a position candidate of the position estimation target estimated in the movement in the predetermined section that has been evaluated to have the error.

A system for collecting and distributing navigation information relative to a road segment is disclosed. In one embodiment, the system includes at least one processor programmed to receive drive information collected from each of a plurality of vehicles that traversed the road segment, wherein the drive information received from each of the plurality of vehicles includes indicators of speed traveled by one of the plurality of vehicles during a drive traversing the road segment; determine, based on the indicators of speed included in the drive information received from each of the plurality of vehicles, at least one aggregated common speed profile for the road segment; store the at least one aggregated common speed profile in an autonomous vehicle road navigation model associated with the road segment; and distribute the autonomous vehicle road navigation model to one or more autonomous vehicles for use in navigating along the road segment.

Provided herein is a system and method of a vehicle. The system comprises one or more sensors, processors, maps, and a memory storing instructions that, when executed by the one or more processors, causes the system to perform: monitoring a location of the vehicle while driving; detecting a sign while the vehicle is driving; capturing, frame-by-frame, data of the sign until the sign disappears from a field of view of the sensor; synchronizing each frame of the data with the location of the vehicle; determining a location of the sign based on the frame-by-frame data; in response to determining, at a frame immediately before the sign disappears from the field of view of the sensor, that the vehicle is driving towards the sign, uploading the detected sign and the location of the sign onto the one or more maps; and implementing a driving action based on the sign.

A method for determining a geographical location of a vehicle (10) includes using a camera/sensor device (20) of the vehicle for recording (S10) first image and sensor data (30) from surroundings of the vehicle (10) while the vehicle (10) is traveling a route. The first image and sensor data (30) are assigned geographical coordinates and are sent to a data evaluation unit (50) for creating a digital map. The method continues by using a second camera and sensor device (20) for recording (S40) second image and sensor data (30) from surroundings while the vehicle (10) is traveling the same route and sending (S50) the recorded second image and sensor data (30) to the data evaluation unit (50). The data evaluation unit (50) compares (S60) the recorded second image and sensor data (30) with the digital map of the surroundings (70) and determines (S70) a position of the vehicle (10).

A system for collecting traffic information includes a vehicle having at least one sensor for collecting dead reckoning (DR) information, and a global positioning system (GPS) receiver configured to receive GPS information, and a server that maps the DR information and the GPS information to a server map to generate first map matching information, and collects the first map matching information as the traffic information when it is determined that a version of a software platform of the vehicle is a latest version and all the DR information and the GPS information are received.