Abstract: An inspection system includes an inspection controller that is electronically connected to a first camera and a second camera, each of which is aligned to cooperatively examine a surface of an object. The first camera defines the first field of view of the object and the second camera defines a second field of view of the object with the first field of view and the second field of view encompassing different areas of the surface of the object. The first camera includes a first clock, and the second camera includes a second clock. The first camera generates a plurality of first images of the object defined by the first field of view and the second camera generates a plurality of second images of the object defined by the second field of view.

Abstract: A system for determining geometric disposition of an object within a coordinate system includes a processor and a sensor array. The sensor array includes a plurality of sensors oriented to scan a first edge and a second edge of an object for identifying a disposition of the first edge and the second edge within a coordinate system. The sensor array is electronically connected to the processor for signaling the identified disposition of the first edge and the second edge of the object within the coordinate system. The processor is programmed to calculate a location of an intersecting point of the first edge and the second edge. The processor calculates disposition of the object within the coordinate system from the calculated location of the of the intersecting point.

Abstract: A system identifying an area of interest of an inspection surface is disclosed. A controller includes a machine learning model trained using stored images defining an area of interest on the inspection surface. A laser projector for projecting laser indicia onto the inspection surface is spatially located relative to the inspection surface enabling the laser projector to project the laser indicia onto the area of interest. An imager includes an image sensor system generates a current image of the inspection surface and signals the current image to the controller. The machine learning model is directed to the area of interest of the current image as identified by the laser indicia and the machine learning model implementing the neural network to inspect the current image of the area of interest as defined by the laser indicia enabling localized inspection of the inspection surface.

Abstract: A system for identifying accurate assembly of a component to a workpiece is disclosed. The system includes a light source for projecting light indicia onto the component assembled to the workpiece. A controller includes an artificial intelligence (AI) element defining a machine learning model that establishes a convoluted neural network trained by stored images of light indicia projected onto the component assembled to the workpiece. An imager includes an image sensor system for imaging the workpiece and signaling a current image of the workpiece to the controller. The machine learning model directs inspection of the workpiece to the light indicia imaged by said imager. The AI element determines disposition of the component disposed upon the workpiece through the neural network identifying distortions of the light indicia in the current image.

Abstract: Systems and methods for UAV collision detection and avoidance are provided. A UAV may include a camera configured to capture a stream of images of a scene, the stream of images including a first frame and a second frame captured after the first frame. The UAV may further include a logic device configured to identify an object in the stream of images, perform a depth estimation between the UAV and the detected object based on a comparison between the first frame and the second frame, and determine a collision path of the UAV to the object based on the depth estimation and a direction of travel of the UAV.

Abstract: Systems and methods for unmanned aerial vehicle (UAV) search and rescue operations are provided. A UAV may include a camera configured to capture one or more images of a search area. The UAV may include at least one logic device configured to calculate a flight pattern for searching the search area, receive a target image, and analyze the one or more images of the search area to identify a target matching the target image.