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.

A structural analysis computing device may generate a proposed insurance claim and/or generate a proposed insurance quote for an object pictured in a three-dimensional (3D) image. The structural analysis computing device may be coupled to a drone configured to capture exterior images of the object. The structural analysis computing device may include a memory, a user interface, an object sensor configured to capture the 3D image, and a processor in communication with the memory and the object sensor. The processor may access the 3D image including the object, and analyze the 3D images to identify features of the object—such as by inputting the 3D image into a trained machine learning or pattern recognition program. The processor may generate a proposed claim form for a damaged object and/or a proposed quote for an uninsured object, and display the form to a user for their review and/or approval.

Method for inspecting a geometry (10) having a surface (11), which method uses an inspection device (100) having a digital image capturing means (120) and a shape scanning means (130), comprising the steps of

a) orienting the inspection device (100) in a first orientation;
b) depicting the surface (11) to produce a first image;
c) measuring a shape of a first geometry part to produce a first shape;
d) moving the inspection device (100) to a second orientation;
e) depicting the surface (11) to produce a second image;
f) measuring a second part of said geometry (10) to produce a second shape;
g) using digital image processing based on said first and second images, determining a geometric orientation difference between said first and second orientations;
h) determining a geometric relation between the first and second shapes; and
i) producing a data representation of said geometry based on said first shape, said second shape and said geometric relation.

The invention also relates to a device.

A system for implementing a trial in one or more fields is provided. In an embodiment, a agricultural intelligence computing system receives field data for a plurality of agricultural fields. Based, at least in part, on the field data for the plurality of agricultural fields, the agricultural intelligence computing system identifies one or more target agricultural fields. The agricultural intelligence computing system sends, to a field manager computing device associated with the one or more target agricultural fields, a trial participation request. The server receives data indicating acceptance of the trial participation request from the field manager computing device. The server determines one or more locations on the one or more target agricultural fields for implementing a trial and sends data identifying the one or more locations to the field manager computing device.

A method for analyzing of a road transport route for transport of a heavy load from an origin to a destination includes i) obtaining images of the transport route, the images being images taken by a drone or satellite camera system, where each of the images includes a different road section of the complete transport route and an peripheral area adjacent to the respective road section; ii) determining objects and their location in the peripheral area of the road section by processing each of the images by a first trained data driven model, where the images are as a digital input to the first trained data driven model and where the first trained data driven model provides the objects, if any, and their location as a digital output; and iii) determining critical objects from the number of determined objects along the road transport route

Provided are embodiments for a system and method for performing real-time detection for mapping. The embodiments include one or more processors, a scanner, and a mobile computing device removably coupled to the 2D scanner where the mobile computing device having a display. Embodiments include collecting scan data of an environment to generate a first map and identifying lines from the collected scan data corresponding to a surface of a structure. Embodiments also include grouping the identified lines into buckets based at least in part on a characteristic of the identified lines and combining the identified lines in each bucket. Embodiments also include optimizing the first map to generate a second map and displaying the second map on the display.

A method (50) of acquiring images of a terrestrial region Z using a spacecraft (10) in non-geostationary orbit around the Earth (30), the spacecraft includes an observation instrument associated with a ground footprint of length L along the direction of travel, the method includes: a step (51) of observing a portion P1 of the terrestrial region Z, including a step of controlling the attitude of the spacecraft (10) during which the ground footprint is kept stationary during the entirety of the step of observing portion P1, and a step of acquiring an image of portion P1, a step (52) of modifying the pitch attitude of the spacecraft (10) so as to place the ground footprint over a portion P2 of the terrestrial region Z, and a step (53) of observing portion P2 of the terrestrial region.

There is disclosed a method and corresponding systems for generating one or more video-based models of a target. The method understood providing video streams from at least two moving or movable vehicles equipped with cameras for simultaneously imaging the target from different viewpoints. Position synchronization of the moving or movable vehicles is provided to create a stable image base, which represents the distance between the moving or movable vehicles. Pointing synchronization of the cameras is provided to cover the same object and/or dynamic event. Time synchronization of the video frames of the video streams is provided to obtain, for at least one point in time, a set of simultaneously registered video frames. The method further included generating, for the at least one point in time, at least one three-dimensional, 3D.

A technique is directed to methods and systems for creating ground control points (GCPs). In some implementations, a GCP system can analyze satellite data for a location, at which multiple photons were measured, and extract terrain and canopy information from the satellite data. The GCP system can create GCPs with the extracted ICESat-2 data and calculate a quality indicator, which indicates a metric of reliability, for each GCP using photon information. In some implementations, the GCP system classifies and filters the GCPs based building footprint data, water data, forest index data, and/or landform classification mask data.

A structural analysis computing device for determining structural characteristics of an object pictured in a three-dimensional (3D) image may be provided. The structural analysis computing device may include a memory, a user interface, an object sensor configured to capture the 3D image of the object, and at least one processor in communication with the memory and the object sensor. The processor may be configured to access the 3D image including the object, automatically determine a first plurality of measurements of the object from the 3D image, and display the 3D image on the user interface. The processor may be further configured to generate a data file including the 3D image and the first plurality of measurements, and store the data file within the memory. The processor may also be configured to transmit the data file to an insurance server computing device for generation of an associated insurance claim form.