Abstract: Embodiments help timely remediation of issues in a data protection system by automatically evaluating scripts configured to address the issues. The system has a bounded list of possible attributes that are deemed important by system administrators. Each attribute is assigned a System Impact Score (SIS) along a defined scale. A self-healing processing component monitors the state of each attribute over time. The scripts are evaluated through repeated execution and use of the attribute monitoring to determine which attributes are affected by a script. Weights are assigned to each attribute affected by a script to aid in the selection of scripts most likely to remediate an actionable issue. Regularly performing script evaluation and attribute weighting allows for updating of scripts with an accurate list of attributes to overcome problems associated with manual updates.

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 three-phase full quorum commit method enabling backing up of network devices that do not offer direct hooks in order to have application consistent protection. Devices are verified to be ready to perform a backup, and a condition of reaching and maintaining a full quorum of devices within a maximum time period is required before the system can be backed up. The three phase backup process reduces the chance of changes to network devices from corrupting consistency among the saved states of the different and disparate network devices. Multiple devices of different makes and models participate together as a unified backup as a network partition and all devices are verified as being in a ready state. The device configuration data is moved from device memory to local disk, and can then be tiered to secondary storage.

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 method for performing a simultaneous location and mapping of a scanner device includes detecting a set of lines in a point cloud, and identifying a semantic feature based on the set of lines. The method further includes assigning a first scan position of the scanner device in the surrounding environment at the present time t1 as a landmark, and linking the landmark with the portion of the map. The method further includes determining that the scanner device has moved, at time t2, to the scan position that was marked as the landmark based on identifying said semantic feature in another scan-data. In response, a second scan position at time t2 is determined. Also, a displacement vector is determined for the map based on a difference between the first scan position and the second scan position. Subsequently, a revised second scan position is computed based on the displacement vector.

Abstract: A method is provided that includes recording a landmark at a first scan position of a scanner, the landmark based at least in part on a semantic feature of scan data captured by the scanner. The semantic feature is identified using line-segments of the scan data. The method further includes capturing, by the scanner while moving through the environment, additional scan data at a second scan position. The method further includes, responsive to the scanner returning to the first scan position associated with the landmark, computing a measurement error. The method further includes correcting, using the measurement error, at least a portion of the scan data or the additional scan data.

Abstract: A method for performing a simultaneous location and mapping of a scanner device includes detecting a set of lines in a point cloud, and identifying a semantic feature based on the set of lines. The method further includes assigning a first scan position of the scanner device in the surrounding environment at the present time t1 as a landmark, and linking the landmark with the portion of the map. The method further includes determining that the scanner device has moved, at time t2, to the scan position that was marked as the landmark based on identifying said semantic feature in another scan-data. In response, a second scan position at time t2 is determined. Also, a displacement vector is determined for the map based on a difference between the first scan position and the second scan position. Subsequently, a revised second scan position is computed based on the displacement vector.

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 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: In a prediction game, the potential value of a participant’s prediction depends on the time when the prediction is submitted. The prediction may pertain to the outcome of a competition in a bracket-style tournament (e.g., the NCAA Division I Men’s Basketball Championship, or “March Madness”).

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 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 and method of generating a two-dimensional (2D) image of an environment is provided. The system includes a scanner having a first light source, an image sensor, a second light source and a controller, the second light source emitting a visible light, the controller determining a distance to points based on a beam of light emitted by the first light source and receiving of the reflected beam of light from the points. Processors are operably coupled to the scanner execute a method comprising: generating a map of the environment; emitting light from the second light source towards an edge defined by at least a pair of surfaces; detecting the edge based on emitting a second beam of light and receiving the reflected second beam of light; and defining a room on the map based on the detecting of the corner or the edge.

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 method for performing a simultaneous location and mapping of a scanner device in a surrounding environment includes capturing a scan-data of a portion of a map of the surrounding environment. The scan-data comprises a point cloud. Further, at runtime, a user-interface is used to make, a selection of a feature from the scan-data, and a selection of a submap that was previously captured. The submap includes the same feature. The method further includes determining a first scan position as a present position of the scanner device, and determining a second scan position as a position of the scanner device. The method further includes determining a displacement vector for the map based on the first and the second scan positions. Further, a revised first scan position is computed based on the second scan position and the displacement vector. The scan-data is registered using the revised first scan position.

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: 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 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: An example method includes receiving, via a 3D scanner, a 3D scan of the environment. The 3D scan includes a global position and is partitioned into a plurality of 3D submaps. The method further includes receiving, via a two-dimensional (2D) scanner accessory, a plurality of 2D submaps of the environment. The method further includes receiving coordinates of the scan position in the plurality of 2D submaps in response to the 3D scanner initiating the acquisition of the 3D scan. The method further includes associating the coordinates of the scan position with the plurality of 2D submaps. The method further includes performing real-time positioning by linking the coordinates of the scan position with the plurality of 2D submaps using a SLAM algorithm. The method further includes performing, based at least in part on the real-time positioning, a registration technique on the plurality of 3D submaps to generate a global map.

Abstract: Techniques are described to determine a constraint for performing a simultaneous location and mapping. A method includes detecting a first set of planes in a first scan-data of an environment, and detecting a second set of planes in a second scan-data. Further, a plane that is in the first set of planes and the second set of planes is identified. Further, a first set of measurements of a landmark on the plane is determined from the first scan-data, and a second set of measurements of said landmark is determined from the second scan-data. The constraint is determined by computing a relationship between the first set of measurements and the second set of measurements.