An example robot performs a scan to obtain image data of a given region. The robot performs image analysis on the image data to detect a set of undesirable objects, and generates a reference map that excludes the set of undesirable objects, where the reference map is associated with the location of the robot at the time of the scan.

A surveying instrument for executing a relocation functionality, which determines first coordinates of a stationary target point associated with the start signal, in response to a start signal, a first actuator and a second actuator are controlled such that the stationary target point remains within a detection area of a tracking unit of the surveying instrument, determines second coordinates of the stationary target point, receives an end signal, wherein the second coordinates of the stationary target point are associated with the end signal, and based at least in part on the first and second coordinates of the stationary target point, and determines a relative pose of the surveying instrument with respect to a first setup location and a second setup location, wherein the first setup location is associated with the first coordinates and the second setup location is associated with the second coordinates.

A system and method is provided for determining where a vehicle has parked in a parking lot. The method includes determining a geometry for a parking lot; receiving vehicle event data including periodic vehicle event data for vehicle speed and steering angle; tracking a movement of a vehicle using the vehicle event data; and determining where a vehicle has parked using a steering angle to determine a number of turns in the parking lot geometry.

A vertical deflection estimation device usable for inertial navigation includes: a gravity gradiometer, a known vertical deflection library part, a high frequency extraction part, and an estimation part. The gravity gradiometer measures a change in vertical deflection in accordance with positional movement of a mobile body and outputs it as a measured vertical deflection. The known vertical deflection library part—obtains known information of vertical deflection on map as known vertical deflection. The high frequency extraction part extracts a high spatial frequency component of a change in the measured vertical deflection which is measured in accordance with the positional movement of the mobile body by the gravity gradiometer. The estimation part derives a change in an estimated vertical deflection by combining a change in the known vertical deflection on map in accordance with the positional movement of the mobile body using information of the known vertical deflection of the known vertical deflection library part and a change in the measured vertical deflection of the high spatial frequency component extracted by the high frequency extraction part.

A system and method for inspection maintenance and/or diagnosis of a variety of workpieces is provided. The system serves workers working on a workpiece, inspectors who are distal from the workers and/or can be used for remote training or for advanced diagnosis and/or repair. The system preferably includes a template of a set of one or more predefined required images of a workpiece required by an inspector to perform their inspection or diagnosis. The set of predefined required images is provided to the worker. The worker captures the images with an appropriate workpiece data capture device and provides them to the inspector for review. The inspector examines the provided images and either approves the workpiece based on their content, requests additional images for further examination and/or provides annotations and other information to the worker to address identified issues. The system maintains a database of all images and information.

Methods and systems for relative inertial measurement may include a user device comprising an inertial measurement device and/or a camera. A second inertial measurement device may be configured to move with a reference frame. One or more processors may receive inertial measurements from the first and second inertial measurement devices and determine movement of the user device relative to the reference frame by comparing the received inertial measurements. Additionally reference objects in a view of a camera may be used to calibrate the determined motion of the user device within the reference frame.

The present disclosure provides a method for obtaining confidence of a measurement value based on multi-sensor fusion and an autonomous vehicle, which includes that: a first measurement value position of a positioning component on a target vehicle is determined at a first moment, and a second measurement value position of the positioning component is determined at a second moment, where the first moment is earlier than the second moment; first distance information is acquired according to the first measurement value position and the second measurement value position; inertial measurement information and wheel speedometer information of the target vehicle from the first moment to the second moment are determined; second distance information is acquired based on the inertial measurement information and the wheel speedometer information; and confidence of a target measurement value corresponding to the second moment is acquired according to the first distance information and the second distance information.

An underwater celestial navigation beacon configured to provide position information is disclosed. The underwater celestial navigation beacon can include a data store configured to store an astronomical model of the moon. The underwater celestial navigation beacon can include an inertial measurement unit (IMU) operable to capture IMU data that includes three-axis acceleration data and three-axis rate gyroscopic data. The underwater celestial navigation beacon can include a controller. The controller can determine a latitude of the underwater celestial navigation beacon using the three-axis rate gyroscopic data. The controller can determine a longitude of the underwater celestial navigation beacon based on a gravitational pull of the moon, using the three-axis acceleration data and the astronomical model of the moon. The controller can determine the position information for the underwater celestial navigation beacon based on the latitude and longitude.

A rear axle center (RAC) locating system may include a tractor and a RAC location acquisition unit. The tractor may include a rear axle having a center, a global positioning system (GPS) antenna offset from the rear axle, and inertial measurement units. The RAC location acquisition unit may include a processing unit and a non-transitory computer-readable medium containing instructions to direct the processing unit to determine a geographic location of the GPS antenna based upon signals received by the GPS antenna and determine a geographic location of the center of the rear axle based upon the geographic location of the GPS antenna and combined data from the inertial measurement units.

A device is configured for performing localization using a set of sensors that are transportable with the device. The device includes at least one processor operationally connected to the set of sensors, and at least one memory that stores program code. The program code configures the at least one processor to determine a first set of device poses where a first sensor satisfies a localization performance rule, and to determine a second set of device poses where a second sensor satisfies the localization performance rule. The at least one processor is further configured to activate the second sensor while the first sensor is active based on a pose of the device transitioning from not being within to being within the second set of device poses.