Abstract: System and methods of automatically assessing power outage risks using geospatial data are provided. For example, a computing device may obtain geospatial data for an area, and may generate classification data based on classifying a plurality of points of the geospatial data. The computing device may also generate a plurality of segments of the area based on the classification data, where each of the plurality of segments includes a subset of the plurality of points. The computing device may also determine an impact value for each of the plurality of points based on the classification data. Further, the computing device may determine an attribute value for each of the plurality of segments based on the impact values of the corresponding subset of the plurality of points. In some examples, the computing device determines a risk value for a classified point based on one or more segment attribute values.

Abstract: A system and method of generating enhanced lidar data for a scene is provided. The system having a lidar point collection system, with a lidar sensor and a lidar point processing system, and an image collection system with an image sensor and an image processing system. The lidar point collection system can obtain lidar data of the scene with the lidar sensor, and the image collection system can obtain a plurality of images of the scene with the image sensor. The system further has a processing system for comparing the collected lidar data and plurality of images to generate enhanced lidar data of the scene.

Abstract: Various embodiments are directed to making partial selections of multidimensional information while maintaining a multidimensional structure. A server computing device may receive multidimensional data describing a structure of a physical object from one or more sources. The server computing device may then determine a data subset representative of the multidimensional data describing the structure of the physical object. The server computing device may then store the data subset on a storage device. Finally, the server computing device may send the data subset to a client computing device for displaying the structure of the physical object. The data subset may enable the client computing device to utilize fewer hardware computing processing, memory, and bandwidth resources to display the structure of the physical object than are associated with displaying the physical object using the multidimensional data. The client computing device may be incapable of displaying the multidimensional data.

Abstract: Various embodiments are directed to a docking station for the mechanical alignment of an autonomous robotic platform. A correlator may receive the wheels of a moving autonomous robotic platform. A first set of rollers in the correlator may align the wheels, in a substantially linear direction, into a space created by a second set of rollers attached to a frame of a backstop. The second set of rollers may continue to align the wheels of the moving autonomous robotic platform until the wheels come in contact with a stopping roller coupled to the backstop. The stopping roller may be vertically oriented at a height above a wheel radius of the autonomous robotic platform. The stopping roller provides a force to prevent further forward travel. Upon being stopped by the stopping roller, the autonomous robotic platform is positioned for mating with charging contacts in the docking station.

Abstract: Various embodiments are directed to facilitating imagery and point-cloud based facility modeling and remote change detection. A computing device may receive collected data for a facility. The collected data may include spatial image data obtained from light detection imaging and ranging systems (LiDAR), multispectral data, and thermal data. The computing device may then analyze, based on software models generated for previously collected data for the facility, the collected data to determine changes in the previously collected data. The computing device may then update the models upon determining changes in the previously collected data. Finally, the computing device may generate an alert based on the updated models when any changes in the previously collected data are above a predetermined threshold corresponding to a current security or operational condition associated with the facility.

Abstract: Various embodiments are directed to deriving spatial attributes for imaged objects utilizing three-dimensional (3D) information. A server may obtain 3D survey data about an object from a pre-existing source. The server may then receive image data describing the object from a user device. The server may then utilize range imagery techniques to build a 3D point cloud from imagery in a pixel space. The server may then utilize horizontal positioning to place the 3D point cloud in proximity to the 3D survey data. The server may then fit the 3D survey data to the 3D point cloud. Finally, the server may record measurements and absolute locations of interest from the 3D point cloud and send them to the user device.

Abstract: Disclosed systems and methods for the remote detection of atmospheric gas may include (1) receiving, at a collector, thermal infrared energy from at least one atmospheric column, (2) receiving, at optical subsystems, the thermal infrared energy over optical paths, (3) focusing the thermal infrared energy onto diffraction gratings that disperse the thermal infrared energy at a wavelength within a mid-wavelength infrared (MWIR) spectral region and a wavelength within a long-wavelength infrared (LWIR) spectral region, (4) receiving, at detectors, the thermal infrared energy dispersed from the diffraction gratings within the MWIR spectral region and the LWIR spectral region, (5) determining spectral component data associated with the thermal infrared energy in the MWIR spectral region and the LWIR spectral region, (6) sending the spectral component data to a computing device, and (7) identifying an atmospheric gas based on the spectral component data.