Abstract: Techniques are described for converting a 2D map into a 3D mesh. The 2D map of the environment is generated using data captured by a 2D scanner. Further, a set of features is identified from a subset of panoramic images of the environment that are captured by a camera. Further, the panoramic images from the subset are aligned with the 2D map using the features that are extracted. Further, 3D coordinates of the features are determined using 2D coordinates from the 2D map and a third coordinate based on a pose of the camera. The 3D mesh is generated using the 3D coordinates of the features.

Abstract: A method and system for generating a three-dimensional (3D) map of an environment is provided. An example method includes receiving a 3D scan and portions of a 2D map of the environment and receiving coordinates of the scan position in the 2D map. The method further includes associating the coordinates of the scan position with the portion of the 2D map. The method further includes linking the coordinates with the portion of the 2D map. The method further includes storing submap data for each of the plurality of submaps into a data object associated respective submaps. The method further includes performing a loop closure algorithm on each of the plurality of submaps. The method further includes, for each of the plurality of submaps for which the position anchor of the submap changed during performing the loop closure algorithm, determining a new data object position for the data objects.

Abstract: A mobile three-dimensional (3D) measuring system includes a 3D measuring device configured to capture 3D data in a multi-level architecture, and an orientation sensor configured to estimate an altitude. One or more processing units coupled with the 3D measuring device and the orientation sensor perform a method that includes receiving a first portion of the 3D data captured by the 3D measuring device. The method further includes determining a level index based on the altitude. The level index indicates a level of the multi-level architecture at which the first portion is captured. The level index is associated with the first portion. Further, a map of the multi-level architecture is generated using the first portion, the generating comprises registering the first portion with a second portion of the 3D data responsive to the level index of the first portion being equal to the level index of the second portion.

Abstract: A mobile three-dimensional (3D) measuring system includes a 3D measuring device, and a support apparatus. The 3D measuring device is coupled to the support apparatus. The support apparatus includes a pole mount that includes a gimbal at the top of the pole mount, wherein the 3D measuring device is attached to the gimbal. The support apparatus further includes a counterweight at the bottom of the pole mount, the counterweight matches a weight of the 3D measuring device.

Abstract: A mobile 3D measuring system includes a 3D measuring device comprising a sensor that emits a plurality of scan lines in a field of view of the sensor. The 3D system further includes a field of view manipulator coupled with the 3D measuring device, the field of view manipulator comprising a passive optic element that redirects a first scan line from the plurality of scan lines. The 3D system further includes a computing system coupled with the 3D measuring device. The 3D measuring device continuously transmits a captured data from the sensor to the computing system as the 3D measuring device is moved in an environment, the captured data is based on receiving reflections corresponding to the plurality of scan lines, including a reflection of the first scan line that is redirected. The computing system generates a 3D point cloud representing the environment based on the captured data.

Abstract: A mobile three-dimensional (3D) measuring system includes a 3D measuring device comprising a first sensor and a second sensor. The 3D measuring system further includes a computing system coupled with the 3D measuring device. A computing device is coupled with the computing system. The 3D measuring device continuously transmits a first data from the first sensor, and a second data from the second sensor to the computing system as it is moved in an environment. The computing system generates a 3D point cloud representing the environment. The computing system generates a 2D projection corresponding to the 3D point cloud. The computing device displays the 2D projection as a live feedback of a movement of the 3D measuring 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: A system includes a transporter robot with a motion controller that changes the transporter robot's poses during transportation. A scanning device is fixed to the transporter robot. One or more processors are coupled to the transporter robot and the scanning device to generate a map of the surrounding environment. At a timepoint T1, when the transporter robot is stationary at a first location, a first pose of the transporter robot is captured. During transporting the scanning device, at a timepoint T2, the scanning device captures additional scan-data of a portion of the surrounding environment. In response, the motion controller provides a second pose of the transporter robot at T2. A compensation vector and a rotation for the scan-data are determined based on a difference between the first pose and the second pose. A revised scan-data is computed, and the revised scan-data is registered to generate the map.

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: 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 three dimensional coordinate measurement device and method of measuring is provided. The device including a housing having a first axis and a second axis. A first depth camera is coupled to the housing, the first depth camera having a first optical axis aligned with the first axis. A second depth camera is coupled to the housing, the second depth camera having a second optical axis disposed on a first angle relative to the first axis. A third depth camera is coupled to the housing, the third depth camera having a third optical axis disposed on a second angle relative to the first axis, the second angle being different than the first angle. A rotational device is coupled to rotate the housing about the second axis.

Abstract: Scanner stabilizing systems are described. The systems include a moving base configured to receive a scanner, at least one motor operably connected to the base to control at least one of an orientation and a position of the moving base about an axis, at least one mounting structure configured to fixedly attached to a mobile apparatus and wherein the at least one motor is attached to a respective one of the at least one mounting structures, and a stabilization controller operably connected to the at least one motor, wherein the stabilization controller is configured to maintain an orientation of the scanner relative to an environment.

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: Techniques are described for converting a 2D map into a 3D mesh. The 2D map of the environment is generated using data captured by a 2D scanner. Further, a set of features is identified from a subset of panoramic images of the environment that are captured by a camera. Further, the panoramic images from the subset are aligned with the 2D map using the features that are extracted. Further, 3D coordinates of the features are determined using 2D coordinates from the 2D map and a third coordinate based on a pose of the camera. The 3D mesh is generated using the 3D coordinates of the features.

Abstract: A method and system for generating a three-dimensional (3D) map of an environment is provided. An example method includes receiving a 3D scan and portions of a 2D map of the environment and receiving coordinates of the scan position in the 2D map. The method further includes associating the coordinates of the scan position with the portion of the 2D map. The method further includes linking the coordinates with the portion of the 2D map. The method further includes storing submap data for each of the plurality of submaps into a data object associated respective submaps. The method further includes performing a loop closure algorithm on each of the plurality of submaps. The method further includes, for each of the plurality of submaps for which the position anchor of the submap changed during performing the loop closure algorithm, determining a new data object position for the data objects.

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.