Abstract: A method for robotic inspection of a part, includes the steps of: supporting the part with a robot mechanism; obtaining part-related sensor input with a sensor positioned to inspect the part supported by the robot mechanism; and controlling movement of the robot mechanism relative to the sensor, wherein the controlling is done by a feedback control unit which receives the sensor input, and the feedback control unit is configured to control the robot mechanism based upon the sensor input.

Abstract: A method for human-robot collaboration including: acquiring visual temporal data of a human partner to a robot; determining, using a generative module, predicted future visual temporal data in response to the visual temporal data, the visual temporal data including current visual temporal data and previous visual temporal data; and determining, using a discriminative module, a vector of probabilities indicating the likelihood that a future action of the human partner belongs to each class among a set of classes being considered in response to at least the future visual temporal data and the visual temporal data.

Abstract: A process for automated component inspection includes the steps of calibrating an imaging device mounted on a table; calibrating a coordinate measuring machine mounted on the table, the coordinate measuring machine comprising a fixture coupled to an arm of the coordinate measuring machine; coupling a component to the fixture; acquiring an image of said component with said imaging device; registering a baseline dimensioned image to the component image; applying the baseline dimensioned image to a damage detection algorithm; and determining component damage by the damage detection algorithm.

Abstract: A method for detecting a double-parked vehicle includes identifying a parking region in video data received from an image capture device monitoring the parking region. The method includes defining an enforcement region at least partially surrounding the parking region. The method includes detecting a stationary vehicle in the enforcement region. The method includes determining the occurrence of an event relative to the stationary vehicle. In response to the determined occurrence of the event, the method includes classifying the stationary vehicle as being one of double parked and not double parked.

Abstract: A system processes a set of images to verify whether the images depict a type of property damage, such as hail damage from a hail storm. The system receives digital images of a roof or other facet of the property that were taken by an image capturing device after the storm event. The system also receives storm data relating to the storm event and claim data related to a property damage claim. The system uses the claim data to process the digital images to automatically identify damage to the roof or other facet. The system then analyzes the storm data to determine whether the damage is consistent with an actual, naturally-occurring storm event, and it generates a report depicting its findings.

Abstract: A system segments a set of images of a property to identify a type of damage to the property. The system receives, from an image capturing device, a digital image of a roof or other feature of the property. The system processes the image to identify a set of segments, in which each segment corresponds to a piece of the feature, such as a tab or tooth of a shingle on the roof. The system saves a result of the processing to a data file as a segmented image of the property, and it uses the segmented image to identify a type of damage to the property.

Abstract: A method for robotic inspection of a part, includes the steps of: supporting the part with a robot mechanism; obtaining part-related sensor input with a sensor positioned to inspect the part supported by the robot mechanism; and controlling movement of the robot mechanism relative to the sensor, wherein the controlling is done by a feedback control unit which receives the sensor input, and the feedback control unit is configured to control the robot mechanism based upon the sensor input.

Abstract: A multi-camera system for a component inspection comprising a table having a table top or, alternatively, another sufficiently rigid surface; a first camera having a narrow field-of-view lens; a second camera having a wide field-of-view lens linked to said first camera, wherein said first camera and said second camera are configured to move identical distances along a common axis relative to said table top or surface; and a pre-defined pattern defined on said table top or surface.

Abstract: A method for robotic inspection of a part, includes the steps of: supporting the part with a robot mechanism; obtaining part-related sensor input with a sensor positioned to inspect the part supported by the robot mechanism; and controlling movement of the robot mechanism relative to the sensor, wherein the controlling is done by a feedback control unit which receives the sensor input, and the feedback control unit is configured to control the robot mechanism based upon the sensor input.

Abstract: A method for nondestructive inspection of a component, the method includes determining a first pulse-echo scan from a first side of a component; determining a second pulse-echo scan from a second side of the component; determining a through-transmission scan based on the first pulse-echo scan, the second pulse-echo scan, and a model of the component, the model comprises a rigid internal structure of the component; and classifying the component based on comparing the through-transmission scan to a “gold” model.

Abstract: A system and method for performing vehicle-velocity aware image enhancement. Embodiments generally include a video capture module configured to receive image data of the scene being monitored, an image extraction module configured to extract still images from incoming video data, a vehicle detection module that detects the approximate location of a target vehicle in the scene being monitored, a velocity determination module configured to determine the amplitude and direction of a vector that describes the velocity of the target vehicle in image pixel coordinates, and a velocity-aware enhancing module configured to enhance the image(s) of the target vehicle extracted from the video feed based on the vehicle's velocity. Embodiments may also include an infraction detection module configured to detect the occurrence of a violation of traffic law(s) by a target vehicle.

Abstract: A method of compressing data in the context of a decision-making task includes receiving raw data, analyzing the raw data to determine content of the raw data, and adjusting one or more one data compression parameters in a compression algorithm. The adjustment of the one or more compression parameters is based on the content of the raw data and a received decision-making task to produce a modified compression algorithm. The raw data is thereafter compressed using the modified compression algorithm and output as compressed data.

Abstract: A material characterization system includes an imaging unit, a material characterization controller, and an imaging unit controller. The electronic imaging unit generates a test image of a specimen composed of a material. The electronic material characterization controller determines values of a plurality of parameters and maps the parameters to corresponding ground truth labeled outputs. The mapped parameters are applied to at least one test image to predict a presence of at least one target attribute of the specimen in response to applying the learned parameters. The test image is convert to a selected output image format so as to generate a synthetic image including the predicted at least one attribute. The electronic imaging unit controller performs a material characterization analysis that characterizes the material of the specimen based on the predicted at least one attribute included in the synthetic image.

Abstract: A system for assessing a property damage claim uses an imaging device to capture images of a property that has reportedly been damaged by an incident. The system receives a property damage incident type, along with image processing criteria for processing images that are associated with the incident type. The system automatically processes the images according to the image processing criteria to identify one or more characteristics in the images and, based on the identified characteristics, determines whether certain claim processing criteria are satisfied. The claim processing criteria may help the system determine whether the property actually was damaged by the reported incident. The system will generate a command to process the property damage claim only if the system determines that one or more images show that the claim processing criteria are satisfied.

Abstract: A material characterization system includes an imaging unit, a material characterization controller, and an imaging unit controller. The electronic imaging unit generates a test image of a specimen composed of a material. The electronic material characterization controller determines values of a plurality of parameters and maps the parameters to corresponding ground truth labeled outputs. The mapped parameters are applied to at least one test image to predict a presence of at least one target attribute of the specimen in response to applying the learned parameters. The test image is convert to a selected output image format so as to generate a synthetic image including the predicted at least one attribute. The electronic imaging unit controller performs a material characterization analysis that characterizes the material of the specimen based on the predicted at least one attribute included in the synthetic image.

Abstract: A method for nondestructive vibrothermography inspection of a component, the method includes generating ultrasonic excitations in a component over a range of frequencies; determining a thermal signature in the component from the excitations; registering a model with the thermal signature; determining damage based on the thermal signal and model; and classifying the component based on the determining.

Abstract: A multi-camera system for a component inspection comprising a table having a table top or, alternatively, another sufficiently rigid surface; a first camera having a narrow field-of-view lens; a second camera having a wide field-of-view lens linked to said first camera, wherein said first camera and said second camera are configured to move identical distances along a common axis relative to said table top or surface; and a pre-defined pattern defined on said table top or surface.

Abstract: A method for nondestructive vibrothermography inspection of a component, the method includes generating ultrasonic excitations in a component over a range of frequencies; determining a thermal signature in the component from the excitations; registering a model with the thermal signature; determining damage based on the thermal signal and model; and classifying the component based on the determining.

Abstract: A method for nondestructive inspection of a component, the method includes determining a first pulse-echo scan from a first side of a component; determining a second pulse-echo scan from a second side of the component; determining a through-transmission scan based on the, first pulse-echo scan, the second pulse-echo scan, and a model of the component, the model comprises a rigid internal structure of the component; and classifying the component based on comparing the through-transmission scan to a “gold” model.

Abstract: A method for robotic inspection of a part, includes the steps of: supporting the part with a robot mechanism; obtaining part-related sensor input with a sensor positioned to inspect the part supported by the robot mechanism; and controlling movement of the robot mechanism relative to the sensor, wherein the controlling is done by a feedback control unit which receives the sensor input, and the feedback control unit is configured to control the robot mechanism based upon the sensor input.