Embodiments provide systems and methods for three-dimensional building generation from machine learning and topological models. The method uses topology models that are converted into vertices and edges. A BGAN (Building generative adversarial network) is used to create fake vertices/edges. The BGAN is then used to generate random samples from seen sample of different structures of building based on relationship of vertices and edges. The embeddings are then fed into a machine trained network to create a digital structure from the image.

Systems, devices, methods, and computer-readable media for horizon-based navigation. A method can include receiving image data corresponding to a geographical region in a field of view of an imaging unit and in which the device is situated, based on the received image data, generating, by the processing unit, an image horizon corresponding to a horizon of the geographical region and from a perspective of the imaging unit, projecting three-dimensional (3D) points of a 3D point set of the geographical region to an image space of the received image data resulting in a synthetic image, generating, by the processing unit, a synthetic image horizon of the synthetic image, and responsive to determining the image horizon sufficiently correlates with the synthetic image horizon, providing a location corresponding to a perspective of the synthetic image as a location of the processing unit.

A client device receives a first map tile, a second map tile, and map terrain data from a mapping system, the first and second map tiles together including map feature having a geometric base with a height value, the geometric base represented by a set of vertices split across the first and second map tiles. The client device identifies edges of the geometric base that intersect a tile border between the first and second map tiles. The client device determines a set of sample points based on the identified edges and determines a particular sample elevation value corresponding to a sample point in the set. The client device renders the map feature based on the particular sample elevation value and displays the rendering of the map feature.

A system for mining material in a seam under an overburden layer using a geological model map of a geological formation, including a desired drilling end point at a predefined position relative to a geological boundary between the overburden layer and seam. A drill controller controls operation of a drill drilling a blast hole. A sensor pack senses, while drilling the blast hole, blast hole drilling operation parameters; and feeds the sensed parameters in real time to the drill controller. A data storage module stores a geological model of the geological formation and sensed parameters data. A processor module generates a geological model map including the desired drilling end point and locates the drill bit position relative to the geological boundary and such end point. The drill controller drills to the desired drilling end point and causes the drill to stop drilling upon reaching such end point.

A system for mining material in a seam under an overburden layer using a geological model map of a geological formation, including a desired drilling end point at a predefined position relative to a geological boundary between the overburden layer and seam. A drill controller controls operation of a drill drilling a blast hole. A sensor pack senses, while drilling the blast hole, blast hole drilling operation parameters; and feeds the sensed parameters in real time to the drill controller. A data storage module stores a geological model of the geological formation and sensed parameters data. A processor module generates a geological model map including the desired drilling end point and locates the drill bit position relative to the geological boundary and such end point. The drill controller drills to the desired drilling end point and causes the drill to stop drilling upon reaching such end point.

Methods, devices, and systems may be utilized for detecting one or more properties of a plant area and generating a map of the plant area indicating at least one property of the plant area. The system comprises an inspection system associated with a transport device, the inspection system including one or more sensors configured to generate data for a plant area including to: capture at least 3D image data and 2D image data; and generate geolocational data. The datacenter is configured to: receive the 3D image data, 2D image data, and geolocational data from the inspection system; correlate the 3D image data, 2D image data, and geolocational data; and analyze the data for the plant area. A dashboard is configured to display a map with icons corresponding to the proper geolocation and image data with the analysis.

Methods, devices, and systems may be utilized for detecting one or more properties of a plant area and generating a map of the plant area indicating at least one property of the plant area. The system comprises an inspection system associated with a transport device, the inspection system including one or more sensors configured to generate data for a plant area including to: capture at least 3D image data and 2D image data; and generate geolocational data. The datacenter is configured to: receive the 3D image data, 2D image data, and geolocational data from the inspection system; correlate the 3D image data, 2D image data, and geolocational data; and analyze the data for the plant area. A dashboard is configured to display a map with icons corresponding to the proper geolocation and image data with the analysis.

A system includes at least one imaging sensor and a processor. The processor is configured to acquire, using the imaging sensor, detected data describing an environment of an autonomous vehicle. The processor is further configured to derive reference data, which describe the environment, from a predefined map, to compute difference data representing a difference between the detected data and the reference data, and to transfer the difference data. Other embodiments are also described.

A system includes at least one imaging sensor and a processor. The processor is configured to acquire, using the imaging sensor, detected data describing an environment of an autonomous vehicle. The processor is further configured to derive reference data, which describe the environment, from a predefined map, to compute difference data representing a difference between the detected data and the reference data, and to transfer the difference data. Other embodiments are also described.

An augmented reality (AR) device can be configured to generate a virtual representation of a user's physical environment. The AR device can capture images of the user's physical environment to generate a mesh map. The AR device can project graphics at designated locations on a virtual bounding box to guide the user to capture images of the user's physical environment. The AR device can provide visual, audible, or haptic guidance to direct the user of the AR device to look toward waypoints to generate the mesh map of the user's environment.