Systems and methods are disclosed that provide contextual tracking information to tracking sensor systems to provide accurate and efficient object tracking. Contextual data of a first tracking sensor system is used to identify a tracked object of a second tracking sensor system.

A method for calibrating a Lidar and a positioning device, a device, and a storage medium. The method includes: acquiring a point-cloud data sequence of the Lidar and a pose data sequence of the positioning device, in which, the Lidar and the positioning device are on a same traveling device; determining first trajectory information of the Lidar and second trajectory information of the positioning device according to the point-cloud data sequence and the pose data sequence; and determining a calibration offset between the Lidar and the positioning device according to the first trajectory information and the second trajectory information, in which, a matching degree between the first trajectory information and the second trajectory information satisfies a preset matching degree condition under a trajectory information correspondence determined based on the calibration offset.

An object detecting system comprising: a first distance measuring device, configured to measure a first distance between a first part of an object and the first distance measuring device; a second distance measuring device, configured to measure a second distance between a second part of the object and the second distance measuring device; a uniform light source, configured to emit uniform light to the object; an optical sensor, configured to sense optical data of the object generated based on the uniform light; and a control circuit, configured to calculate a location of the object according to the first distance, the second distance and the optical data.

With the advent of augmented reality devices becoming increasingly prevalent, accessible, and cross-compatible, there is an opportunity to leverage the capabilities of such devices in order to streamline workflow and information access in number of contexts. The present invention provides an integrated, dynamic system for leveraging the capabilities of augmented reality systems in order to provide users with personalized information in a dependable, seamless, and secure manner.

A system uses range and Doppler velocity measurements from a lidar system and images from a video system to estimate a six degree-of-freedom trajectory (6DOF) of a target. The 6DOF transformation parameters are used to transform multiple images to the frame time of a selected image, thus obtaining multiple images at the same frame time. These multiple images may be used to increase a resolution of the image at each frame time, obtaining the collection of the superresolution images.

The invention is a method of determining wind speed components using a ground-based LiDAR sensor (1) comprising determining the wind direction (Dir) and the average wind speed (v) in a measurement plane (PM), then constructing a projection line perpendicular to wind direction (Dir) in measurement plane (PM), and subsequently determining a time shift (δt) between the measurement points (b1, b2, b3, b4) and the projection line, to determine corrected measurement signals.

An object-tracking method using a LiDAR sensor includes generating current shape information about a current tracking box at a current time from an associated segment box, using history shape information accumulated prior to the current time with respect to a target object that is being tracked, and updating information on a previous tracking box at a time prior to the current time, contained in the history shape information, using the current shape information and the history shape information and determining a previous tracking box having the updated information to be a final output box containing information on the shape of the target object.

A LIDAR-to-vehicle alignment system includes a memory and alignment and autonomous driving modules. The memory stores points of data provided based on an output of one or more LIDAR sensors and localization data. The alignment module performs an alignment process including: based on the localization data; determining whether a host vehicle is turning; in response to the host vehicle turning; selecting a portion of the points of data; aggregating the selected portion to provide aggregated data; selecting targets based on the aggregated data; and based on the selected targets, iteratively reducing a loss value of a loss function to provide a resultant LIDAR-to-vehicle transformation matrix. The autonomous driving module: based on the resultant LIDAR-to-vehicle transformation matrix, converts at least the selected portion to at least one of vehicle coordinates or world coordinates to provide resultant data; and performs one or more autonomous driving operations based on the resultant data.

A motion monitor includes a lidar device, a controller, and a circuit. The lidar device is configured to perform scans of an environment proximate the ego vehicle to generate lidar point clouds related to one or more objects in the environment. The controller is configured to transform the lidar point clouds with location transform matrices to generate location point sets, aggregate the location point sets in a duration of interest to generate aggregated point sets, register the location point sets to the aggregated point sets to generate correction transform matrices, update the location transform matrices with the correction transform matrices to generate updated location transform matrices, and generate motion sets based on the updated location transform matrices. The circuit is configured to receive the motion sets.

Provided is a target instrument including a pole, a prism provided on the pole, and a terminal device provided on the pole, wherein the terminal device comprises an image pickup module, a tilt sensor which detects tilts in two axial directions, and an arithmetic control module, wherein the image pickup module acquires an image which includes a reference object, the tilt sensor detects a tilt angle of a target instrument, and the arithmetic control module calculates a tilt direction of the target instrument from a position of the reference object in the image, calculates a tilt direction of the target instrument based on tilt angles in the two axial directions of the tilt sensor, acquires a deviation between the two tilt directions, and corrects the tilt angles in the two axial directions of the tilt sensor to tilt angles in directions parallel to an optical axis of the image pickup module and orthogonal to the optical axis based on the deviation.