Abstract: Examples described herein provide a method that includes performing a first scan of an object to generate first scan data. The method further includes detecting a defect on a surface of the object by analyzing the first scan data to identify a region of interest containing the defect by comparing the first scan data to reference scan data. The method further includes performing a second scan of the region of interest containing the defect to generate second scan data, the second scan data being higher resolution scan data than the first scan data. The method further includes combining the first scan data and the second scan data to generate a point cloud of the object.

Abstract: A system includes a first type of measurement device that captures first 2D images, a second type of measurement device that captures 3D scans. A 3D scan includes a point cloud and a second 2D image. The system also includes processors that register the first 2D images. The method includes accessing the 3D scan that records at least a portion of the surrounding environment that is also captured by a first 2D image. Further, 2D features in the second 2D image are detected, and 3D coordinates from the point cloud are associated to the 2D features. 2D features are also detected in the first 2D image, and matching 2D features from the first 2D image and the second 2D image are identified. A position and orientation of the first 2D image is calculated in a coordinate system of the 3D scan using the matching 2D features.

Abstract: An example method for training a neural network includes generating a training data set of point clouds. The training data set includes pairs of closed surfaces point clouds and non-closed surfaces point clouds. The method further includes, for each of the closed surface point clouds and the non-closed surface point clouds, generating a two-dimensional (2D) image by rendering a three-dimensional scene. The 2D image for the non-closed surfaces point clouds includes a gap in a surface, and the 2D image for the closed surfaces point clouds are free of gaps. The method further includes training the neural network to generate a trained neural network. The method further includes filling, using the trained neural network, gaps between scan points of the 2D image, and de-noising, using the trained neural network, scan point cloud data to generate a closed surface image of the scan point cloud data.

Abstract: Motorized cartridges and coordinate measuring machines having motorized cartridges are provided. The motorized cartridges include a cartridge housing having a shaft passing therethrough, a measurement probe coupled to shaft and arranged to detect movement of the shaft, and an integrated motor operably coupled to the shaft and arranged to drive movement of the shaft.

Abstract: A system and a method for removing artifacts from a 3D coordinate data are provided. The system includes one or more processors and a measuring device. The one or more processors are operable to receive training data and train the 3D measuring device to identify artifacts by analyzing the training data. The one or more processors are further operable to identify artifacts in live data based on the training of the processor system. The one or more processors are further operable to generate clear scan data by filtering the artifacts from the live data and output the clear scan data.

Abstract: A method for determining three-dimensional (3D) coordinates of an object surface with a 3D measuring device includes forming from the determined 3D coordinates a mesh having a first face, constructing a voxel array aligned to the first face, obtaining a plurality of images from a first camera having a corresponding plurality of poses, obtaining for each voxel in the voxel array a plurality of voxel values obtained from the corresponding plurality of images, determining for each voxel row a quality value determined based at least in part on an average value of a first quantity and a dispersion of the first quantity, the first quantity based at least in part on first voxel values determined as a function of pose, and determining a distance from a point on the first face to the object surface based at least in part on the determined quality values for the voxel rows.

Abstract: A system and method of inspecting a plurality of objects using a computed tomography (CT) system is provided. The method includes acquiring an image of a fixture used for holding the plurality of objects with the CT system. A first electronic model of the fixture is generated. The objects are placed in the fixture. An image of the fixture and the objects is acquired with the CT system. A second electronic model of the fixture and the objects is generated. A third electronic model of the objects is defined based at least in part on subtracting the first electronic model from the second electronic model. Dimensions of the objects from the third electronic model are compared with a computer aided design (CAD) model. A report is output based at least in part on the comparison of the objects from the third electronic model with the CAD model.

Abstract: Aspects of the present disclosure provide a system for measuring an object, the system including a plurality of frame segments. The frame segments are configured to mechanically couple together to form a frame. The plurality of frame segments includes a plurality of measurement device link segments and each of the plurality of measurement device link segments includes a measurement device which together form a plurality of measurement devices having a field of view within or adjacent to the frame. Each of the plurality of measurement devices is operable to measure three-dimensional (3D) coordinates for a plurality of points on the object. The system further includes a computing device to receive data from the plurality of measurement devices via a network established by the plurality of measurement device link segments.

Abstract: A system of generating a three-dimensional (3D) scan of an environment includes multiple 3D scanners including a first 3D scanner at respective first and second positions. The system further includes a controller coupled to the 3D scanners via a common communications network. The first scanner and second scanner transmit a subset of data to the controller while acquiring a set of 3D coordinates. The controller registers the subsets of data to each other while the sets of 3D coordinates is being acquired.

Abstract: A laser projector steers a pulsed laser beam to form a pattern of stationary dots on an object, the pulsed laser beam having a periodicity determined based at least in part on a maximum allowable spacing of the dots and on a maximum angular velocity at which the beam can be steered, wherein a pulse width of the laser beam and a pulse peak power of the laser beam are based at least in part on the determined periodicity and on laser safety requirements.

Abstract: A virtual reality (VR) system that includes a three-dimensional (3D) point cloud having a plurality of points, a VR viewer having a current position, a graphics processing unit (GPU), and a central processing unit (CPU). The CPU determines a field-of-view (FOV) based at least in part on the current position of the VR viewer, selects, using occlusion culling, a subset of the points based at least in part on the FOV, and provides them to the GPU. The GPU receives the subset of the plurality of points from the CPU and renders an image for display on the VR viewer based at least in part on the received subset of the plurality of points. The selecting a subset of the plurality of points is at a first frame per second (FPS) rate and the rendering is at a second FPS rate that is faster than the first FPS rate.

Abstract: Provided are embodiments for a method for performing colorization of scans. The method includes analyzing a scanner, a scan of an environment to identify one or more patterns within the scan, and obtaining a subset of colorization data of the environment. The method also includes predicting colors for the one or more patterns in the scan based on the subset of colorization data, and assigning the predicted colors to the one or more patterns in the scan to generate a colorized scan. The method includes displaying the colorized scan, wherein the colorized scan combines the scan and the predicted colorization data by assigning the predicted colorization data to the one or more patterns in the scan. Also provided are embodiments for a system for performing the colorization of scans.

Abstract: Methods and systems for capturing image information of an environment using a laser scanner are described. The systems include a rotatable mirror arranged to direct light received onto an imaging camera of the laser scanner. The mirror is rotatable relative to the imaging camera and the camera is stationary relative to a rotational axis of the mirror. The methods include rotating the mirror relative to the camera and capturing, via the camera, an image containing image information of the received light. Each pixel of the image contains image information of an accumulation of the received light along a corresponding trajectory during a mirror rotation and each individual trajectory has a trajectory that crosses another of the individual trajectories within the image.

Abstract: A method for scanning and measuring using a 3D measurement device is provided. The method includes providing the 3D measurement device having a light emitter, a light receiver and a command and evaluation device. The 3D measurement device is further includes a first near-field communication (NFC) device having a first antenna. A second NFC device having a second antenna is positioned adjacent the 3D measurement device. An NFC link is established between the first NFC device and the 3D measurement device. An identifier is transmitted from the second NFC device to the 3D measurement device. It is determined that the second NFC device is authorized to communicate with the 3D measurement device. Commands are transferred to the 3D measurement device from the second NFC device based at least in part on the determination that the second NFC device is authorized to communicate with the 3D measurement device.

Abstract: A system for generating an automatically segmented and annotated two-dimensional (2D) map of an environment includes processors coupled to a scanner to convert a 2D map from the scanner into a 2D image. Further, a mapping system categorizes a first set of pixels from the image into one of room-inside, room-outside, and noise by applying a trained neural network to the image. The mapping system further categorizes a first subset of pixels from the first set of pixels based on a room type if the first subset of pixels is categorized as room-inside. The mapping system also determines the room type of a second subset of pixels from the first set of pixels based on the first subset of pixels by using a flooding algorithm. The mapping system further annotates a portion of the 2D map to identify the room type based on the pixels corresponding to the portion.

Abstract: 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.

Abstract: A three-dimensional (3D) measuring instrument includes a registration camera and a surface measuring system having a projector and an autofocus camera. For the instrument in a first pose, the registration camera captures a first registration image of first registration points. The autofocus camera captures a first surface image of first light projected onto the object by the projector and determines first 3D coordinates of points on the object. For the instrument in a second pose, the registration camera captures a second registration image of second registration points. The autofocus camera adjusts the autofocus mechanism and captures a second surface image of second light projected by the projector. A compensation parameter is determined based at least in part on the first registration image, the second registration image, the first 3D coordinates, the second surface image, and the projected second light.

Abstract: Generating a three-dimensional (3D) map of an environment includes receiving, via a 3D-scanner that is mounted on a moveable platform, a 3D-scan of the environment while the moveable platform moves through the environment. The method further includes receiving via a two-dimensional (2D) scanner that is mounted on the moveable platform, a portion of a 2D-map of the environment, and receiving first coordinates of the scan position in the 2D-map. The method further includes associating the scan position with the portion of the 2D-map as a virtual landmark. In response to the movable platform being brought back at the virtual landmark, a displacement vector for the 2D-map is determined based on a difference between the first coordinates and a second coordinates that are determined for the scan position. A revised scan position is calculated based on the displacement vector, and the revised scan position is used to register the 3D-scan.

Abstract: A system and method of automatic re-localization of a handheld scanning device in a previously mapped environment is provided. The system includes a two-dimensional (2D) scanner and one or more processors operably coupled to the 2D scanner. The one or more processors are responsive to non-transitory executable instructions for performing operations that include determining a current location of the 2D scanner in the environment relative to a location in a previously generated 2D image of the environment that was generated based on an image of a non-digital floorplan. The operations also include generating a new 2D image of at least a subset of the environment. The at least a subset of the environment includes the current location of the 2D scanner and at least one other location in the environment. The operations further include overlapping portions of the previously generated 2D image and the new 2D image.

Abstract: Techniques for localizing a portable articulated arm coordinate measuring machine (AACMM) are described. An example localization method includes in response to an AACMM base being placed at a first position, capturing a first set of images of a positioning element in a predetermined area. The method further includes determining first 3D coordinates of the positioning element using the first set of images. 3D coordinates corresponding to a position of a first measurement probe in the predetermined area are computed using the first 3D coordinates. Further, the method includes, in response to the base being moved to a second position, determining second 3D coordinates of the positioning element from the second position using a second set of images. Further, the localization method includes determining a translation matrix to convert the second 3D coordinates to the first 3D coordinates.