A waterjet-guided laser machine includes a laser source, an LED, a waterjet head, and a light sensor. The waterjet head includes a water inlet and a nozzle having an outlet for a discharging a waterjet. There is a laser optical path along which a pulsed laser beam travels to the nozzle outlet. There is also a light beam optical delivery path along which the light beam travels from the LED to the nozzle outlet. The light beam optical delivery path is coincident with the laser optical path in the nozzle. There is a light beam optical return path along which the light beam that is reflected off of a workpiece travels to the light sensor. The light beam optical return path is coincident with the laser optical path inside the nozzle and coincident with the light beam optical delivery path inside the nozzle.

A waterjet-guided laser machine includes a laser source, an LED, a waterjet head, and a light sensor. The waterjet head includes a water inlet and a nozzle having an outlet for a discharging a waterjet. There is a laser optical path along which a pulsed laser beam travels to the nozzle outlet. There is also a light beam optical delivery path along which the light beam travels from the LED to the nozzle outlet. The light beam optical delivery path is coincident with the laser optical path in the nozzle. There is a light beam optical return path along which the light beam that is reflected off of a workpiece travels to the light sensor. The light beam optical return path is coincident with the laser optical path inside the nozzle and coincident with the light beam optical delivery path inside the nozzle.

Systems, methods, and apparatus for acquiring surface profile information (e.g., depths at multiple points) from limited-access structures and objects using an autonomous or remotely operated flying platform (such as an unmanned aerial vehicle). The systems proposed herein use a profilometer to measure the profile of an area on a surface where visual inspection has indicated that the surface has a potential anomaly. After the system has gathered data representing the surface profile in the area containing the potential anomaly, a determination may be made whether the collected image data indicates that the structure or object should be repaired or may be used as is.

Systems, methods, and apparatus for acquiring surface profile information (e.g., depths at multiple points) from limited-access structures and objects using an autonomous or remotely operated flying platform (such as an unmanned aerial vehicle). The systems proposed herein use a profilometer to measure the profile of an area on a surface where visual inspection has indicated that the surface has a potential anomaly. After the system has gathered data representing the surface profile in the area containing the potential anomaly, a determination may be made whether the collected image data indicates that the structure or object should be repaired or may be used as is.

A distance sensor is used for automatically detecting whether an outer wheel of a dual-wheel axle is present. The distance sensor is mounted to detect a distance between the sensor and an outer wheel of a dual-wheel axle. A controller compares the distance information with an expected range of distances if the outer wheel is present and determines that the wheel is not present if the measured distance falls outside the expected range. The methods and systems are particularly suitable for mobile machines, such as a combine harvester, having a rollover risk reduction system and/or a stability control system reliant on accurate width data for the machine, and which can be configured to apply different limits for maximum steering angle and/or maximum speed depending on whether the outer wheel is found to be present.

A distance sensor is used for automatically detecting whether an outer wheel of a dual-wheel axle is present. The distance sensor is mounted to detect a distance between the sensor and an outer wheel of a dual-wheel axle. A controller compares the distance information with an expected range of distances if the outer wheel is present and determines that the wheel is not present if the measured distance falls outside the expected range. The methods and systems are particularly suitable for mobile machines, such as a combine harvester, having a rollover risk reduction system and/or a stability control system reliant on accurate width data for the machine, and which can be configured to apply different limits for maximum steering angle and/or maximum speed depending on whether the outer wheel is found to be present.

The tire sensing and analysis system may comprise a measurement device and local application software. The measurement device may make contact with a tire of a vehicle such that the measurement device is positioned at a specific distance and orientation relative to the tire. The measurement device may capture multiple images of the tire using an RGB camera and a pair of infrared cameras. The local application software may analyze the images and may construct a 3D mesh describing the 3-dimensional contours of the tread. The local application software may determine a tread depth and may display status and warning messages on a display unit that is coupled to the measurement device. The measurements may be communicated to remote application software for additional analysis. As non-limiting examples, the remote application software may detect specific tire wear patterns and may transmit a report to share results of the analysis.

Systems and methods are provided for processing lidar data. The lidar data can be obtained in a particular manner that allows reconstruction of rectilinear images for which image processing can be applied from image to image. For instance, kernel-based image processing techniques can be used. Such processing techniques can use neighboring lidar and/or associated color pixels to adjust various values associated with the lidar signals. Such image processing of lidar and color pixels can be performed by dedicated circuitry, which may be on a same integrated circuit. Further, lidar pixels can be correlated to each other. For instance, classification techniques can identify lidar and/or associated color pixels as corresponding to the same object. The classification can be performed by an artificial intelligence (AI) coprocessor. Image processing techniques and classification techniques can be combined into a single system.

Systems and methods are provided for processing lidar data. The lidar data can be obtained in a particular manner that allows reconstruction of rectilinear images for which image processing can be applied from image to image. For instance, kernel-based image processing techniques can be used. Such processing techniques can use neighboring lidar and/or associated color pixels to adjust various values associated with the lidar signals. Such image processing of lidar and color pixels can be performed by dedicated circuitry, which may be on a same integrated circuit. Further, lidar pixels can be correlated to each other. For instance, classification techniques can identify lidar and/or associated color pixels as corresponding to the same object. The classification can be performed by an artificial intelligence (AI) coprocessor. Image processing techniques and classification techniques can be combined into a single system.

A system for inspecting a reflective surface includes a first imaging assembly configured to take a first image of the reflective surface, the first image including depth information, a second imaging assembly configured to take a second image of the reflective surface, the second image including contrast information, and a processor configured to acquire the first image and the second image. The processor is configured to perform: estimating a depth profile of the surface based on the depth information, correlating the depth profile with the second image, and identifying a feature of the reflective surface based on the correlation.