Abstract: Systems and methods for tracking the location of a non-destructive inspection (NDI) scanner using scan data converted into images of a target object. Scan images are formed by aggregating successive scan strips acquired using one or two one-dimensional sensor arrays. An image processor computes a change in location of the NDI scanner relative to a previous location based on the respective positions of common features in partially overlapping scan images. The performance of the NDI scanner tracking system is enhanced by: (1) using depth and intensity filtering of the scan image data to differentiate features for improved landmark identification during real-time motion control; and (2) applying a loop-closure technique using scan image data to correct for drift in computed location. The enhancements are used to improve localization, which enables better motion control and coordinate accuracy for NDI scan data.

Abstract: End effectors and systems may capture, release, and/or create a mating engagement between the end effector and a target object. Said end effectors are tolerant of positional and rotational misalignment of the target object, and include a plurality of roller wheels, one or more of which is arranged in a non-parallel plane with respect to one or more other roller wheels. A first roller wheel configured to rotate in a first plane, a second roller wheel configured to rotate in a second plane, and a third roller wheel configured to rotate in a third plane may be arranged such that the end effector is configured to engage a passive receptacle of the target object, to capture the target object. Rotating the roller wheels in the opposite direction may cause the target object to be released or launched, by urging the passive receptacle off of or away from the roller wheels.

Abstract: Methods and apparatus for performing repair operations using an unmanned aerial vehicle. The methods are enabled by equipping the UAV with tools for rapidly repairing a large structure or object (e.g., an aircraft or a wind turbine blade) that is not easily accessible to maintenance personnel. In accordance with various embodiments disclosed below, the unmanned aerial vehicle may be equipped with an easily attachable/removable module that includes an additive repair tool. The additive repair tool is configured to add material to a body of material. For example, the additive repair tool may be configured to apply a sealant or other coating material in liquid form to a damage site on a surface of a structure or object (e.g., by spraying liquid or launching liquid-filled capsules onto the surface). In alternative embodiments, the additive repair tool is configured to adhere a tape to the damage site.

Abstract: Embodiments described herein utilize Non-Destructive Inspection (NDI) scan data obtained during a process performed on a surface of a structure to update a location of an NDI scanner on the surface. A subsurface feature within the structure is detected based on the NDI scan data, which are correlated with pre-defined position data for the subsurface feature. A measured location of the NDI scanner on the surface is corrected based on the pre-defined position data for the subsurface feature.

Abstract: Methods and apparatus for UAV-enabled marking of surfaces during manufacture, inspection, or repair of limited-access structures and objects. A UAV is equipped with a marking module that is configured to apply marking patterns (e.g., alignment features) of known dimensions to surfaces. The marking module may include a 2-D plotter that enables free-form drawing capability. The marking process may involve depositing material on the surface. The marking material may be either permanent or removable. A “clean-up” module may be attached to the UAV platform instead of the marking module, and may include solvents and oscillating or vibrating pads to remove the marks via scrubbing. The clean-up module can also be used for initial surface preparation.

Abstract: A method includes obtaining, at an unmanned aerial vehicle, a flight plan for the unmanned aerial vehicle. The flight plan is based on an aircraft type of an aircraft to be inspected. The method also includes coordinating, with a lighting control device onboard the aircraft, activation of a particular exterior light of the aircraft based on the flight plan such that the particular exterior light activates or deactivates when a particular sensor of the one or more sensors is located (i.e., positioned and oriented) to perform a sensing operation on the particular exterior light. The method further includes performing the sensing operation on the particular exterior light using the particular sensor. The method also includes determining a functionality metric associated with the particular exterior light based on the sensing operation.

Abstract: A temporal multi-configuration model dataset system comprises a computer system configured to: compare a prior parts list for a vehicle at a point in time to a current parts list in which comparing the prior parts list with the current parts list results in a comparison; determine change lists for the parts that changed using the comparison; append models to a model dataset for the vehicle in response to parts added to the vehicle, wherein models are not removed from the model dataset in response to parts being removed from the vehicle; determine display parts in the model dataset present for a selected point in time in response to receiving a request to visualize the vehicle at the selected point in time in which the display parts are determined using the set of change lists; and display a visualization of the vehicle using the display parts on a display system.

Abstract: Methods and apparatus for UAV-enabled marking of surfaces during manufacture, inspection, or repair of limited-access structures and objects. A UAV is equipped with a marking module that is configured to apply marking patterns (e.g., alignment features) of known dimensions to surfaces. The marking module may include a 2-D plotter that enables free-form drawing capability. The marking process may involve depositing material on the surface. The marking material may be either permanent or removable. A “clean-up” module may be attached to the UAV platform instead of the marking module, and may include solvents and oscillating or vibrating pads to remove the marks via scrubbing. The clean-up module can also be used for initial surface preparation.

Abstract: An aircraft inspection system is configured to inspect one or more components of an aircraft before a flight. The aircraft inspection system includes an inspection robot that is configured to inspect the component(s) of the aircraft. The inspection robot includes a conveying sub-system that is configured to efficiently move the inspection robot to different locations, and a sensing sub-system including one or more sensors that are configured to sense one or more characteristics of the component(s) during an inspection. The sensing sub-system is configured to record the characteristic(s) as inspection data.

Abstract: A method, apparatus, system, and computer program product for inspecting an aircraft. A computer system receives captured data associated with a flight path flown by an unmanned aircraft system to acquire the captured data for the aircraft. The computer system compares the captured data with reference data for the aircraft to form a comparison. The computer system determines whether the captured data is within a set of tolerances for valid captured data using a result of the comparison. Prior to detecting anomalies for the aircraft using the captured data, the computer system determines a set of corrective actions in response to the captured data being outside of the set of tolerances for the valid captured data in which the set of corrective actions is performed.

Abstract: Methods and apparatus for performing repair operations using an unmanned aerial vehicle (UAV). The methods are enabled by equipping the UAV with tools for rapidly repairing a large structure or object (e.g., an aircraft or a wind turbine blade) that is not easily accessible to maintenance personnel. A plurality of tools are available for robotic selection and placement at the repair site. The tools are designed to perform respective repair operations in sequence in accordance with a specified repair plan, which plan may take into account the results of a previously performed UAV-enabled inspection.

Abstract: A system and method for detecting an anomaly of an optically transparent or translucent object are disclosed. The system and method include a light source configured to emit light, a light transmission element having a textured surface, and an optical couplant configured to be disposed between the light transmission element and the object. At least a portion of the light emitted by the light source is configured to pass into the light transmission element through the textured surface and pass into the object through the optical couplant. At least a portion of the light that passes into the object internally reflects within the object and impinges on the anomaly to provide an illumination that indicates the location of the anomaly.

Abstract: Embodiments described herein utilize Non-Destructive Inspection (NDI) scan data obtained during a process performed on a surface of a structure to update a location of an NDI scanner on the surface. A subsurface feature within the structure is detected based on the NDI scan data, which are correlated with pre-defined position data for the subsurface feature. A measured location of the NDI scanner on the surface is corrected based on the pre-defined position data for the subsurface feature.

Abstract: Systems and methods for tracking the location of a non-destructive inspection (NDI) scanner using scan data converted into images of a target object. Scan images are formed by aggregating successive scan strips acquired using one or two one-dimensional sensor arrays. An image processor constructs and then compares successive partially overlapping scan images that include common features corresponding to respective structural features of the target object. The image processor is further configured to compute a change in location of the NDI scanner relative to a previous location based on the respective positions of those common features in the partially overlapping scan images. This relative physical distance is then added to the previous (old) absolute location estimate to obtain the current (new) absolute location of the NDI scanner.

Abstract: End effectors and systems may capture, release, and/or create a mating engagement between the end effector and a target object. Said end effectors are tolerant of positional and rotational misalignment of the target object, and include a plurality of roller wheels, one or more of which is arranged in a non-parallel plane with respect to one or more other roller wheels. A first roller wheel configured to rotate in a first plane, a second roller wheel configured to rotate in a second plane, and a third roller wheel configured to rotate in a third plane may be arranged such that the end effector is configured to engage a passive receptacle of the target object, to capture the target object. Rotating the roller wheels in the opposite direction may cause the target object to be released or launched, by urging the passive receptacle off of or away from the roller wheels.

Abstract: Systems and methods for tracking the location of a non-destructive inspection (NDI) scanner using images of a target object acquired by the NDI scanner. The system includes a frame, an NDI scanner supported by the frame, a system configured to enable motorized movement of the frame, and a computer system communicatively coupled to receive sensor data from the NDI scanner and track the location of the NDI scanner. The NDI scanner includes a two-dimensional (2-D) array of sensors. Subsurface depth sensor data is repeatedly (recurrently, continually) acquired by and output from the 2-D sensor array while at different locations on a surface of the target object. The resulting 2-D scan image sequence is fed into an image processing and feature point comparison module that is configured to track the location of the scanner relative to the target object using virtual features visible in the acquired scan images.

Abstract: Methods and apparatus for performing repair operations using an unmanned aerial vehicle (UAV). The methods are enabled by equipping the UAV with tools for rapidly repairing a large structure or object (e.g., an aircraft or a wind turbine blade) that is not easily accessible to maintenance personnel. A plurality of tools are available for robotic selection and placement at the repair site. The tools are designed to perform respective repair operations in sequence in accordance with a specified repair plan, which plan may take into account the results of a previously performed UAV-enabled inspection.

Abstract: Embodiments described herein utilize Non-Destructive Inspection (NDI) scan data obtained during a process performed on a surface of a structure to update a location of an NDI scanner on the surface. A subsurface feature within the structure is detected based on the NDI scan data, which are correlated with pre-defined position data for the subsurface feature. A measured location of the NDI scanner on the surface is corrected based on the pre-defined position data for the subsurface feature.

Abstract: A method for navigating a sensor-equipped mobile platform through an through an environment to a destination, the method including: capturing a first image in a first state of illumination; capturing a second image in a second state of illumination; generating a difference image from said first image and said second image; locating an imaging target based on said difference image, said imaging target including a machine-readable code embedded therein, said machine-readable code including navigation vector data; extracting said navigation vector data from said machine-readable code; and using said extracted navigation vector data to direct the navigation of the mobile platform through the environment to a destination.

Abstract: Systems and methods for tracking the location of a non-destructive inspection (NDI) scanner using scan data converted into images of a target object. Scan images are formed by aggregating successive scan strips acquired using one or two one-dimensional sensor arrays. An image processor computes a change in location of the NDI scanner relative to a previous location based on the respective positions of common features in partially overlapping scan images. The performance of the NDI scanner tracking system is enhanced by: (1) using depth and intensity filtering of the scan image data to differentiate features for improved landmark identification during real-time motion control; and (2) applying a loop-closure technique using scan image data to correct for drift in computed location. The enhancements are used to improve localization, which enables better motion control and coordinate accuracy for NDI scan data.