Abstract: Embodiments automate the timely remediation of issues by matching failed operations to a script or set of scripts that is configured to fix the problem. A method detects a backup operation alert message sent from a data manager or storage system that encodes one or more attributes affected by the backup operation, wherein the attributes are weighted to reflect a percentage importance of the a corresponding script to fix the problem. A script library is scanned to identify scripts that match the alert message. A component generates a score for each script, where the score factors the relevance of the script to the backup operation based on the weighted attributes. Scores for each single script each possible combination of multiple scripts are computed and compared, and the script or script combination with the highest score is executed by the self-healing process.

Abstract: One example method includes defining object groups by classifying each object in a backup saveset based on respective object types of the objects such that all objects in an object group are the same object type, assigning a different respective storage media type to each of the object groups, storing each object group at a respective storage target, representing each object group with a respective Merkle tree that includes a base hash, and mapping each base hash to the storage target where the object group associated with the Merkle tree that includes the base hash is stored.

Abstract: Embodiments for a method performing data migration such as backups and restores in a network by identifying characteristics of data in a data saveset to separate the data into defined types based on respective characteristics, assigning a data label to each defined type by receiving user selection or automatically merging or selecting a priority label, from among many labels associated with a file, defining migration rules for each data label, discovering assigned labels during a migration operation; and applying respective migration rules to labeled data in the data saveset. The migration rules can dictate storage location, access rights, replication periods, retention periods, and similar parameters.

Abstract: Embodiments are described for preventing undesired data deletion on protection storage by using delete restrictions. A delete restriction component prevents data from being staged for permanent erasure, such as by preventing files from being moved to a trash folder. A well-known process (WKP), such as a backup or migration operation that is known to request data expiration, is used to validate data deletions. The WKP identifies data that is no longer to be retained. The WKP uses a well-known process expiration list (WEL) that holds hashes of the data. A bucket confirmation count indicates candidates for data deletion. Separately, Garbage Collection maintains another list of hashes that are deletion candidates. A separate process finds common hashes between the WKP and GC hashes, and then removes the data pointed to by the common hashes.

Abstract: Embodiments automate the timely remediation of issues by matching failed operations to a script that is configured to fix the problem or problems without causing additional side effects, thus minimizing unavailability of services and loss of data. A method detects a backup operation alert message sent from a data manager or storage system that encodes one or more attributes affected by the backup operation, wherein the attributes are weighted to reflect a percentage importance of the a corresponding script to fix the problem. A script library is scanned to identify scripts that match the alert message. A component generates a score for each script, where the score factors the relevance of the script to the backup operation based on the weighted attributes, and executes the script with the highest score, as the script most likely to fix the issue causing the alert message.

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: Tracking changes to a document by defining a document record having a unique document record and comprising an index and a file name of the document, and defining a backup record for the document in a series of backups, which includes a timestamp for each backup, and a bitmask for the document. The bitmask has a single bit position for each document in the container which is set to a first binary value to indicate that the corresponding document is unchanged and a second binary value to indicate whether the document is changed or deleted. A primary query is received and resolved for the document by analyzing the document record to find the file name. A secondary query using the document record ID is resolved to find all tracked versions of the document, and the results are returned to the user in the form of a version history list.

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: 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 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 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 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: 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.