Faro Technologies, Inc.

Other

Daniel Flohr

Martin Ossig

Louis Bergmann

Dag Frommhold

Daniel Pompe

Oswin Horvath

Oliver Zweigle

Reinhard Becker

Manuel Caputo

Zia Ul Azam

Oliver Knörzer

Martin Heide

José Gerardo Gómez Méndez

Vadim Demkiv

Jörg Braunes

A method that includes providing a database for storing meta-data that describes steps in a workflow and an order of the steps in the workflow. The meta-data includes, for each of the steps: a reference to an input data file for the step; a description of a transaction performed at the step; and a reference to an output data file generated by the step based at least in part on applying the transaction to the input data file. Data that includes meta-data for a step in the workflow is received and the data is stored in the database. A trace of the workflow is generated based at least in part on contents of the database. The generating is based on receiving a request from a requestor for the trace of the workflow. At least a subset of the trace is output to the requestor.

Tracking data acquired by coordinate measurement devices through a workflow

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.

System and method for training a neural network to fill gaps between scan points in images and to de-noise point cloud images

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.

Artifact filtering using artificial intelligence

A system and method of providing remote control of a scanner is provided. The system includes a laser scanner device rotatable around a first axis and that includes a mirror rotatable around a second axis. The system also includes a mobile computing device operably coupled for communication to the laser scanner. The mobile computing device includes a sensor to detect movement of the mobile computing device. The mobile computing device also includes one or more processors and computer instructions to perform a method that includes connecting to the laser scanner to transmit signals therebetween; detecting a motion of the mobile computing device; and causing the laser scanner to modify at least one of the first angle of rotation of the laser scanner about the first axis and the second angle of rotation of the mirror about the second axis in response to detecting motion of the mobile computing device.

Remote control of a scanner using movement of a mobile computing device

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.

System and method of registering point cloud data using subsample data

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.

Artificial intelligence scan colorization

A method that includes providing a database for storing meta-data that describes steps in a workflow and an order of the steps in the workflow. The meta-data includes, for each of the steps: a description of an input data file for the step; a description of a transaction performed at the step; and a description of an output data file generated by the step based at least in part on applying the transaction to the input data file. Data that includes meta-data for a step in the workflow is received and the data is stored in the database. A trace of the workflow is generated based at least in part on contents of the database. The generating is based on receiving a request from a requestor for the trace of the workflow. At least a subset of the trace is output to the requestor.

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. The first 3D scanner acquires a first set of 3D coordinates, the first set of 3D coordinates having a first portion. The second 3D scanner acquires a second set of 3D coordinates, the second set of 3D coordinates having a second portion. The first portion and the second portion are simultaneously transmitted to the controller by the first 3D scanner and the second 3D scanner respectively, while the first set of 3D coordinates and the second set of 3D coordinates are being acquired. The controller registers the first portion and the second portion to each other while the first set of 3D coordinates and the second set of 3D coordinates are being acquired.

System and method of scanning an environment using multiple scanners concurrently

A method of registering three-dimensional (3D) point clouds may include obtaining a first 3D point cloud acquired at a first location; obtaining a second 3D point cloud acquired at a second location; calculating a first normal vector for each point of the first 3D point cloud to create a plurality of normal vectors; calculating, for each point of the first 3D point cloud, a normal deviation amount of the corresponding normal vector to other normal vectors in a predetermined neighborhood of the point; selecting, from the first 3D point cloud, a first registration region based on whether the normal deviation amount of each point meets a deviation threshold; and registering the first 3D point cloud and the second 3D point cloud to create the composite 3D point cloud, the registration utilizing the first registration region in place of the first 3D point cloud.

Method and apparatus for registering three-dimensional point clouds

A system and method for measuring three-dimensional (3D) coordinates is provided. The method includes rotating a 3D scanner about a first axis, the 3D scanner having a light source, a light receiver and a color camera. A light beams are emitted from the light source and reflected light beams are received with the light receiver. A processor determines 3D coordinates of points on the object based on the emitted light beams and the reflected light beams. For each of the points an intensity value is measured based on the reflected light beams. A color image of the object is acquired with the color camera. The intensity values are fused with the color image to generate an enhanced image, the enhanced image includes color data. Color data is merged with the 3D coordinates of the points. The 3D coordinates of the points are stored with the color data.

Laser scanner with enhanced dymanic range imaging

Individual bug fixed messages for software users that includes determining an occurrence of an error in software executing on a user processor. A unique error report identifier is stored in a memory accessible by the user processor and the error is reported. The reporting includes transmitting the unique error report identifier and error data that describes the error to a developer server. The error data is analyzed to determine a fix to correct the error. A message regarding the fix to correct the error is stored in a fixed error database. The software is launched and it is determined that the error was previously reported. The fixed error database is queried by the software with the unique error report identifier to locate the message. Based on locating the message, the message is downloaded and displayed by the user processor.

Individual bug fixed messages for software users

A collaborative virtual reality (VR) online meeting platform that includes a three-dimensional (3D) point cloud data defining a virtual space, identifiers of a plurality of meeting participants, and meeting data that includes positions in the virtual space of a plurality of avatars that correspond to meeting participants. The system includes a processor that includes instructions to initiate an online meeting of the plurality of meeting participants. The initiating includes providing an address of the 3D point cloud to each of the meeting participants and transmitting a copy of the 3D point cloud data and meeting data to each of the meeting participants. A current location of each of the avatars in the virtual space is communicated to all of the meeting participants.

Collaborative virtual reality online meeting platform

A method for optically scanning, measuring and displaying a point cloud is provided. The method includes emitting, by a laser scanner, an emission light beam and receiving a reflection light beam that is reflected from an object. A control device determines for measurement points projected on a plane corresponding to a screen, wherein at least some measurement points are displayed on a display device. One or more pixels are gap filled to generate a visual appearance of a surface on the display device. Wherein the gap filling includes a first horizontal search in a first direction of a first measured point of the measurement points followed by a second horizontal search in a second direction of the first measured point. The gap filling further includes a first vertical search in a third direction of the measured point, followed by a second vertical search in a fourth direction.

Method for optically scanning and measuring an environment

A method, system and computer program product are provided for displaying three-dimensional measurement points on a two-dimensional plane of a display screen having a plurality of pixels. The method includes projecting the measurement points onto the plane. Each of the measurement points is assigned to one of the pixels. A depth value is assigned to each of the pixels. A first pixel is selected having a first measurement point and a first depth value. A first side is searched for a second pixel having a second measurement point and a second depth value. A second side is searched for a third pixel having a third measurement point and a third depth value. It is determined whether the second and third measurement points are on a same plane. The first depth value of the first pixel is changed when the second and third measurement points are on the same plane.

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Stuttgart, Germany

Daniel Flohr