Described are systems and methods to utilize images to determine the position and/or orientation of a vehicle (e.g., an autonomous ground vehicle) operating in an unstructured environment (e.g., environments such as sidewalks which are typically absent lane markings, road markings, etc.). The described systems and methods can determine the vehicle's position and orientation based on an alignment of annotated images captured during operation of the vehicle with a known annotated reference map. The translation and rotation applied to obtain alignment of the annotated images with the known annotated reference map can provide the position and the orientation of the vehicle.

Systems and methods for updating navigational maps based using at least one sensor are provided. In one aspect, a control system for an autonomous vehicle, includes a processor and a computer-readable memory configured to cause the processor to: receive output from at least one sensor located on the autonomous vehicle indicative of a driving environment of the autonomous vehicle, retrieve a navigational map used for driving the autonomous vehicle, and detect one or more inconsistencies between the output of the at least one sensor and the navigational map. The computer-readable memory is further configured to cause the processor to: in response to detecting the one or more inconsistencies, trigger mapping of the driving environment based on the output of the at least one sensor, update the navigational map based on the mapped driving environment, and drive the autonomous vehicle using the updated navigational map.

A map establishment method and a map establishment system are provided. The map establishment method includes: detecting a physical motion performed by a user and generating motion sensing data by at least one motion sensor; obtaining spatial dimension information, in multiple directions, of a target place where the user is located and information of an obstacle in the target place by a deep learning model according to the motion sensing data; and generating map data according to the spatial dimension information and the information of the obstacle, wherein the map data reflects a contour of the target place where the user is located and a distribution status of at least one obstacle in the target place.

In one embodiment, a method is provided. The method comprises determining a first value of a coefficient of an edge-determining algorithm in response to a spatial resolution of a first image acquired with an image capture device onboard a vehicle, a spatial resolution of a second image, and a second value of the coefficient in response to which the edge-determining algorithm generated a second edge map corresponding to the second image. The method further comprises determining, with the edge-determining algorithm in response to the coefficient having the first value, at least one edge of at least one object in the first image. The method further comprises generating, in response to the determined at least one edge, a first edge map corresponding to the first image. The method further comprises determining at least one navigation parameter of the vehicle in response to the first and second edge maps.

There is disclosed a method of updating a database of positioning data, using a mobile user device moved along a path through a plurality of positions, the method comprising the steps of: at each of the plurality of positions: receiving position estimate data and measurement data from a plurality of positioning modules associated with the mobile user device; calculating an estimate of the position in dependence on the data received from the plurality of positioning modules; and storing the estimate of the position and the measurement data; subsequently processing the stored measurement data to calculate at least one revised estimate of a respective position; and processing said at least one revised estimate to update the database of positioning data.

A device implementing a system for estimating device location includes at least one processor configured to receive a first estimated position of the device at a first time. The at least one processor is further configured to capture, using an image sensor of the device, images during a time period defined by the first time and a second time, and determine, based on the images, a second estimated position of the device, the second estimated position being relative to the first estimated position. The at least one processor is further configured to receive a third estimated position of the device at the second time, and estimate a location of the device based on the second estimated position and the third estimated position.

An unmanned aerial vehicle (UAV) logs first UAV information at a first frequency. The UAV triggers a camera associated with the UAV to capture an image. In response to triggering the camera to capture the image, the UAV logs second UAV information at a second frequency that is higher than the first frequency. A device that is separate from the UAV identifies a location of the UAV corresponding to the image based on a capture timestamp of the image received from the camera, the first UAV information, and the second UAV information. The device generates a geo-rectified imagery based on the image and the location of the UAV.

Localization and navigation systems and techniques are described. An electronic device comprises a processor configured to maintain a state vector storing estimates for a position of the electronic device at poses along a trajectory within an environment along with estimates for positions for one or more features within the environment. The processor computes, from the image data, one or more constraints based on features observed from multiple poses of the electronic device along the trajectory, and computes updated state estimates for the position of the electronic device in accordance with the motion data and the one or more computed constraints without computing updated state estimates for the features for which the one or more constraints were computed.

A method comprises accessing a data set comprising a LIDAR acquired point cloud comprising a plurality of points each of which are attributed with at least a geospatial coordinate, sub-sampling at least a portion of the plurality of points to derive a representative sample of the plurality of points and displaying the representative sample of the plurality of points.

A method for image-based point measurement includes moving a surveying system along a path through a surrounding and capturing a series of images of the surrounding. A subset of images are defined as frames and a subset of frames are defined as key-frames. Textures are identified in first and second frames and are tracked in successive frames to generate first and second frame feature lists. A structure from motion algorithm is used to calculate camera poses for the images based on the first and second frame feature lists. Corresponding image points in images of the series of images are identified using feature recognition in at least a plurality of images. Three-dimensional coordinates of the selected image point are determined using forward intersection with the poses of the subset of images in which corresponding image points are identified. The three-dimensional coordinates of the selected image point are presented to the user.