A method includes: scanning a first QR code on a first physical object to obtain first parameters, wherein the first parameters include specifications for making a product using a manufacturing process, and the specifications include at least one material used to build the product. The method further includes scanning a second QR code on a second physical object to obtain second parameters, wherein the second parameters correspond to the manufacturing process; comparing, by a computing device, the first parameters and the second parameters; based on comparing the first parameters and the second parameters, determining whether the first object corresponds to the second object; and in response to determining that the first object corresponds to the second object, building the product using the at least one material.

Systems and methods provide for the determination and correction of tooling deviation by comparing two different three-dimensional surface scans of a composite panel after curing. Such methods and systems may allow for less accurate post-cure fixturing (e.g., holding the panel in a less constrained state, as compared to prior art techniques), while still maintaining a sufficient amount of precision for predictive shimming and shimless techniques. Methods include performing a first three-dimensional surface scan, performing a second three-dimensional surface scan, and comparing the two to determine a deformation function corresponding to tooling deviation. In some systems, a header structure is used to hold the composite panel in a nominal configuration for the second three-dimensional surface scan. In some systems, scanning devices perform mirrored scanning on either side of the composite panel, using a common reference frame.

This disclosure describes systems, methods, and devices related to robotic control for tool sharpening. The device may determine a first location associated with a first cutting tool of the one or more cutting tools relative to the first container. The device may grip the first cutting tool based on the first location of the first cutting tool relative to the first container. The device may move the robotic device to one more scanning sensors. The device may collect three dimensional data. The device may extract a profile of the first cutting tool. The device may determine a top edge and a bottom edge based on the profile. The device may determine a tip of the first cutting tool. The device may generate a sharpening path based on the tip and the profile of the first cutting tool.

An imaging device for an additive manufacturing system is provided. The additive manufacturing system includes a material. The imaging device includes a high resolution imaging bar including at least one detector array, and an imaging element positioned between the at least one detector array and the material. The high resolution imaging bar is displaced from the material along a first direction and extends along a second direction. The high resolution imaging bar is configured to generate an image of a build layer within the material.

An automated hand tool sharpening and cleaning system for sharpening the two opposed cutting edges of domestic, industrial, sport, or hobby hand tool like a knife blade is provided by the invention. The apparatus comprises a six-axis robotic arm, a pneumatic gripper, a vision sensor camera for profiling the blade edges, a robotic controller, and sequentially-arranged grinding, coarse sharpening, fine sharpening, and buffing rotating wheel assemblies used to grind, sharpen, and buff or polish the cutting edges of the knife blade. The blade cutting edges are profiled by the camera image that is processed by associated software to define the blade by multiple points defined along its edge, followed by a set of algorithms that are used to clean up any discrepancies in the profile data. The resulting corrected profile data is then translated into a set of machine control commands fed to the robotic arm and pneumatic gripper via the robot controller for manipulating the knife blade edges via the robotic arm with respect to each of the grinding, coarse sharpening, fine sharpening, and buffing/polishing wheels and an associated wash station for remove bits of metal and other residue resulting from the sharpened knife blade.

A position detector includes a detection unit configured to detect light from a first diffraction grating including a first pattern disposed in a first direction, and light from a second diffraction grating including a second pattern disposed in the first direction, and a control unit configured to obtain a relative position between the first and the second diffraction gratings based on the light detected by the detection unit. The position detector has a third pattern formed in a second direction different from the first direction at edges of the first pattern of the first diffraction grating, the third pattern has a width smaller than a width of the first pattern of the first diffraction grating.

Disclosed is 3D scanning using a 3D scanner configured for detecting when the scanned object is at rest in the scan volume of the 3D scanner.

A system is placed upon a target object and a machining tool. The system comprises a variety of sensors to detect adverse relative movement and position loss of the target object as it is affected by the machining tool. The system further comprises portable sensors in communication with a printed control board, configured to communicate position data to a remote computing device. The remote computing device may receive the position data, process it, and present output to a display. The system may detect position, kinematic, and mechanical issues present during the machining process by comparing the position data to thresholds, including position loss, and automatically adjust the operation of the machining tool in response.

In various embodiments, a scanner optimizer system may generate a virtual model of a predicted flitch based on a 3D model of a log/cant and a cut solution for the log/cant. The scanner optimizer system may compare a virtual model of an actual flitch to virtual models of predicted flitches by comparing data points at a fixed elevation relative to one or both faces of the models. Based on the comparisons, the scanner optimizer system may identify the source log from which the actual flitch was cut. In addition, the scanner optimizer system may identify the saw used to cut the actual flitch, and/or other relevant information, and use the additional information to monitor and adjust the saws and other equipment. Embodiments of corresponding apparatuses and methods are also described.

Methods and apparatuses for controlling a projector are provided. In some embodiments, a method includes: controlling the light source to emit point structured light to a reflector; and adjusting a tilt angle of the reflector to change the tilt angle of the reflector, and to enable the point structured light reflected from the reflector to an optical conversion device to deflect towards a preset scanning direction. The optical conversion device is used for converting the point structured light incident onto the optical conversion device into line structured light. The line structured light is used for forming a pattern that is projected onto a surface of a target object and extends along a direction intersecting with the preset scanning direction. Improved efficiency in three-dimensional scanning of a target object can be achieved.