Robotic repair control system and method

Abstract

An imaging and repair system (100) is presented that includes a first imaging system (110) configured to image and detect defects on a work surface. The first imaging system includes a first camera configured to capture a plurality of first images of the work surface. The plurality of first images are stored in a data source. The system further includes a second imaging system (110) configured to image and characterize orange peel in the work surface in a region proximate to a defect. Characterizing the work surface includes identifying delta values of the orange peel. The system further includes a defect repair processor configured to select a repair strategy based on a defect type. The system further includes a defect modifier configured to modify the selected repair strategy based on the orange peel characterization of the work surface. The system further includes a defect repair tool (120) configured to automatically implement the modified repair strategy.

Description

Background Technology

[0001] Clear coat repair is one of the final operations to be automated in automotive original equipment manufacturing (OEM) departments. Technologies are desired to automate this process, as well as other paint applications suitable for inspection and repair using abrasives and / or robots (e.g., primer sanding, clear coat defect removal, clear coat polishing, etc.).

[0002] Early work on automating the detection and repair of paint defects includes the system described in U.S. Patent Publication 2003 / 0139836, which discloses the use of electro-imaging to detect and repair paint defects on a vehicle body. This system references vehicle imaging data with vehicle CAD data to generate three-dimensional coordinates for each paint defect. The paint defect data and coordinates are used to develop repair strategies for automated repair using multiple automated robots performing various tasks, including sanding and polishing the paint defects. Summary of the Invention

[0003] An imaging and repair system is proposed, comprising a first imaging system configured to image and detect defects on a work surface. The first imaging system includes a first camera configured to capture multiple first images of the work surface. The multiple first images are stored in a data source. The system also includes a second imaging system configured to image and characterize orange peel texture on the work surface in regions adjacent to the defects. Characterizing the work surface includes identifying incremental values ​​of the orange peel texture. The system further includes a defect repair processor configured to select a repair strategy based on the defect type. The system also includes a defect modifier configured to modify the selected repair strategy based on the orange peel texture characterization of the work surface. Finally, the system includes a defect repair tool configured to automatically implement the modified repair strategy. Attached Figure Description

[0004] In accompanying drawings that are not necessarily drawn to scale, similar figures may describe similar components in different views. The drawings are generally shown by way of example but are not limited to the various embodiments discussed in this document.

[0005] Figure 1 This is a schematic diagram of a robotic paint repair system, in which an embodiment of the present invention is useful.

[0006] Figure 2 A method for repairing robot defects according to an embodiment of this paper is shown.

[0007] Figures 3A to 3B An image of orange peel wrinkles is shown.

[0008] Figure 4 A repair strategy generator according to the implementation scheme described herein is shown.

[0009] Figure 5A and Figure 5B An imaging system for detecting orange peel wrinkles on a work surface is shown in the embodiments described herein.

[0010] Figure 6 A method for characterizing the working surface region in the embodiments described herein is illustrated.

[0011] Figure 7 A method for modifying the repair strategy in the implementation scheme described herein is illustrated.

[0012] Figure 8 It is the system architecture for generating repair strategies.

[0013] Figures 9 to 10 An example of a mobile device that can be used in the implementation shown in the previous figures is illustrated.

[0014] Figure 11 It is a block diagram of a computing environment that can be used in the embodiments shown in the previous figures. Detailed Implementation

[0015] Recent advances in imaging technology and computing systems have made it feasible to inspect varnish coatings at production speeds. Specifically, stereoscopic deflection has recently proven capable of providing images and location information (coordinate location information and defect classification) of paint and varnish coating defects at appropriate resolution, allowing for subsequent automated spot repair.

[0016] As used herein, the term "vehicle" is intended to encompass a wide range of moving structures that receive at least one coat of paint or varnish during manufacturing. While many of the examples herein relate to automobiles, it is explicitly envisioned that the methods and systems described herein are also applicable to trucks, trains, ships (with or without motors), aircraft, helicopters, and the like.

[0017] As used herein, the term "working surface" is intended to cover any surface on which defect repair is attempted. The working surface includes the area with the detected defect, the area surrounding the detected defect affected during the polishing operation, and the area surrounding the affected area, which may include a textured surface, characterized by the presence of orange peel wrinkles.

[0018] The term "paint" is used broadly herein to refer to any of the various layers of paint, filler, primer, varnish, clear coat, etc., applied during the finishing process of a vehicle. Additionally, the term "paint repair" refers to locating and repairing any visual artifacts (defects) on or within any of the paint layers. In some embodiments, the systems and methods described herein use a clear coat as the target paint repair layer. However, the proposed systems and methods are applicable to any particular paint layer (electrophoretic paint, filler, primer, varnish, clear coat, etc.) with minimal modification.

[0019] As used herein, the term "defect" refers to an area on a work surface that interferes with visual aesthetics. For example, many vehicles appear glossy or metallic after being painted. "Defects" can include debris trapped within one or more of the various paint layers on a work surface. Defects can also include stains in the paint, including excess paint streaks or drips, as well as indentations.

[0020] Paint repair is one of the last remaining steps in the vehicle manufacturing process that remains largely manual. Historically, this has been due to two main factors: a lack of sufficient automated inspection and the difficulty of automating the repair process itself. Standards for paint and clear coat repair are related to aesthetics as judged by the human eye (the dealer receiving the vehicle and the end customer inspecting it before purchase). Traditionally, robots have been designed to provide “perfect” or highly “regular” repairs with clean, defined edges and uniform cuts (see...). Figure 4 B). Unfortunately, this makes the repair highly visible to the human eye. The system and method described in this paper propose a way to increase the irregularity of the paint repair process, allowing the repaired defects to blend better into the vehicle surface and become less detectable by the customer.

[0021] Figure 1 This is a schematic diagram of a robotic paint repair system, in which embodiments of the invention are useful. System 100 typically includes two units, a visual inspection system 110 and a defect repair system 120. The two systems can be controlled separately by motion controllers 112 and 122, which can receive instructions from one or more application controllers 150. The application controllers can receive input or provide output to a user interface 160. Repair unit 120 includes a force control unit 124 alignable with an end effector 126. Figure 1 As shown, the end effector 126 includes two tools 128, as further described in co-pending U.S. Provisional Patent Application 62 / 940950, filed November 27, 2019. However, other arrangements are also explicitly considered.

[0022] A more detailed discussion of the robot’s trajectory repair can be found in co-pending U.S. Provisional Patent Application 62 / 941286, filed November 27, 2019, which is incorporated herein by reference.

[0023] The first of the two main challenges, namely the inspection of vehicle 130 by inspection unit 110, is of interest due to the nature of the potential problem domain. Generally, the surface of interest is very large compared to the defect itself, with differences ranging from several orders of magnitude. This leads to a trade-off between field of view and resolution when sensor selection is involved. Additionally, each paint layer in the finishing process (electrophoretic paint, primer, varnish, clear coat, etc.) differs in its visual appearance, with specular reflectivity being particularly noteworthy. Highly specular surfaces (i.e., high-gloss or high-reflectivity surfaces) pose unique imaging challenges. These issues together make inspection difficult. Recent advances in this field, utilizing increasing computational resources, have led to the availability of several commercial solutions. The presence of a sufficiently capable inspection system 110 is important for identifying defects repaired by repair unit 120.

[0024] Current techniques in vehicle paint repair involve manually sanding / polishing defects with or without the aid of power tools using fine grinding and / or polishing systems, while maintaining the desired finish (e.g., matching specular reflectivity in the clear coat). Professionals performing such repairs utilize numerous hours of training, while simultaneously using their senses to monitor the repair's progress and make adjustments accordingly. This complex process is difficult to capture in robotic solutions with limited sensing capabilities.

[0025] Furthermore, abrasive material removal is a pressure-driven process, and many industrial manipulators typically operate naturally in orientation tracking / control mode, optimized for orientation accuracy and precision. The result is an extremely precise system with an extremely rigid error response curve (i.e., small orientation displacements result in very large correction forces), which is inherently poor under force control (i.e., joint torque and / or Cartesian force). Closed-loop force control methods have been used (with limited utility) to address the latter, along with newer (and more successful) force control flanges that provide softer (i.e., non-rigid) displacement curves more suitable for sensitive force / pressure-driven processing. However, the problem of robust process strategies / controls remains and is the focus of this work.

[0026] Figure 2 A method for repairing defects in a robot according to an embodiment of the present invention is illustrated. Method 200 is an overview of how a robot repair system according to at least some embodiments described herein repairs defects.

[0027] For example, in box 210, from the robot controller (such as...) Figure 1 The application controller 150 in the robot receives instructions. These instructions include movement instructions for different components of the robot repair unit.

[0028] In box 220, the robot motion controller moves the abrasive article mounted to the tool into position to prepare for engagement of the defect. The location of the defect on the vehicle is known from the inspection system. Moving the abrasive article into position involves moving the article to the top or vicinity of the defect. This orientation may be referred to as the nominal pose of the support pad.

[0029] In box 230, abrasive article bonding defects are shown. Bonding defects may include abrasion defect areas, as indicated in box 232, or polishing defect areas, as indicated in box 234. Bonding defects also include different repair parameters of the support pad relative to the nominal pose, such as the support pad speed 232, the force applied to the support pad 334, the orientation offset of the support pad 236, and the final repair shape 238 produced by the abrasion and polishing operations.

[0030] In box 240, the defective area is cleaned. Cleaning may include wiping away any fluids used in sanding or polishing, as well as removing debris. As indicated in box 242, after the cleaning step, the tool can re-engage the defect. For example, a dual-mount tool system may have both a sanding and polishing unit available, allowing the next repair step to be performed after cleaning.

[0031] In box 250, the defective area is examined to determine if the repair is sufficient. If additional repair is needed, method 200 may receive new instructions, as indicated by arrow 260, and the method may be repeated. Inspecting the defective repair may include capturing a post-repair image 252, which may be presented to the repair operator or saved as needed. Inspection may also include verifying the repair, as indicated in box 254, which may include comparing the before and after images, detecting whether the defect would be visible / perceptible to the human eye, or using another suitable verification technique.

[0032] Manual repair technicians introduce randomness into the defect repair process, often resulting in the repair blending into the surrounding surface. This is more difficult to replicate in robotic repair systems due to the texture of the work surface. When paint is applied to the work surface in a manufacturing environment, environmental disturbances (such as vehicle movement or vibration, movement of circulating air, and the nature of the applied paint) can lead to issues such as… Figure 3A and Figure 3B The textured surface shown is often referred to as "orange peel" due to its appearance. Orange peel can also be intentionally added to the surface of the clear coat to create different levels of orange peel texture and enhance the aesthetics of different surfaces on the vehicle.

[0033] Generally, the expectation is to "perfectly" repair any defects in the paint. However, the concept of a perfect repair is largely subjective and therefore cannot be formally defined. Informally, a "perfect" repair is one where the final result is visually indistinguishable from other defect-free areas of the work surface, while the concept of an optimal repair is considered to refer to the best possible repair given some initial conditions. For example, not all defects can be repaired to a perfect state. Furthermore, time is a critical parameter in defect repair because vehicle manufacturing is typically an assembly line process. Therefore, an effective repair can be characterized as one that makes the defective area indistinguishable in the shortest possible time.

[0034] The human eye is remarkably adept at noticing inherently "perfect" or "regular" items, as well as abrupt changes in boundaries or textures. This sensitivity to sudden visual boundary shifts necessitates controlling the transition between repaired and unrepaired areas. One objective of restoration is to maximize the concealment of defect repairs on finished products.

[0035] To better integrate the repair into the surrounding working surface area, a reliable method for characterizing the surface area is needed. Currently, orange peel wrinkles are typically characterized on a numerical scale of 1-10, for example... Figure 3A An example of "2" is shown, and Figure 3B An example of "5" is shown. However, different vehicle manufacturers may measure and characterize orange peel wrinkles differently.

[0036] Additionally, while handheld devices exist capable of providing a digital representation of orange peel wrinkles, these devices cannot be calibrated to match manufacturer standards. Furthermore, handheld devices are not networked to the restoration system and do not provide outputs that can be used to modify or adjust the restoration strategy. For example, it might be necessary to change the restoration strategy based on whether the surrounding orange peel wrinkles are rated as "1" or "8" (discussed in more detail in co-pending U.S. Provisional Patent Application 62 / 941286, filed November 27, 2019) to allow the restoration to better integrate into the surface.

[0037] Furthermore, while systems exist that can generally characterize orange peel wrinkles, it is still necessary to characterize orange peel wrinkles in the region immediately surrounding the defect, because orange peel wrinkles can vary, for example, from one area of ​​a car hood to another. Although some systems may rely on surface sampling to guess the orange peel wrinkle value at a given defect area, this is only an estimate and may be incorrect.

[0038] A system is needed that can automatically detect and characterize orange peel texture in the region surrounding a defect. This system should integrate orange peel texture characterization into a repair strategy generation sequence, such that the repair strategy is based on the orange peel texture of the surface immediately surrounding the defect. In some embodiments, the repair strategy automatically changes based on the automatic detection of orange peel texture, making the orange peel texture characterization an internal system parameter that requires no operator intervention. Alternatively or additionally, the orange peel texture characterization may also be presented to the operator in the context of the repair strategy or as a separate component.

[0039] The systems and methods described herein provide an integrated orange peel detection system for robotic repair systems that automatically detects and characterizes orange peel wrinkles in areas surrounding defects on vehicle surfaces. The system can also detect and characterize the contours of the vehicle surface. The orange peel system may include a camera and a structured light system, which may include components also used to detect the defects themselves. The systems and methods described herein also provide an orange peel detection system mounted on a robotic repair unit, enabling simultaneous measurement of orange peel wrinkles with defect repair.

[0040] Figure 4 A repair strategy generator according to an embodiment of this document is illustrated. A first imaging system 310 has a light source 312, a camera (or other imaging device) 314, an analyzer 316, and may have other components 318. A second imaging system 320 also has a light source 322, a camera 324, an analyzer 326, and other components 328. Although imaging systems 310 and 320 are shown as separate systems with individual components, it is also contemplated that in some embodiments, the systems may share components. For example, a single light source 312 may be used for both the defect detection system 310 and the orange peel characterization system 320. Additionally, a single analyzer with a processing unit may support both the defect detection system 310 and the orange peel characterization system 320. Furthermore, although each of systems 310, 320 is shown as having processors 316, 326, it is explicitly contemplated that in some embodiments, systems 310, 320 may only capture images of the surface, and analysis and processing may be performed within a separate device receiving images from systems 310, 320.

[0041] Database 350 may be connected to repair strategy generator 300, for example, via network communication, or may be incorporated into the memory of repair strategy generator 300. Database 350 may include information, including but not limited to, abrasive articles 352 currently being used or available by robotic repair unit 370. Database 350 may also include information about a plurality of defects 354 detectable on the surface, such as excess paint, scratches, paint stains, particles trapped under the paint layer, or other defects. Database 350 may also store historical repair information 356, such as categorized by detected defects, repair trajectories used, or orange peel texture on the surface during repair, or another characteristic. Database 350 may also include information about available repair trajectories 358, and may also include information about which trajectories are suitable for a given defect or based on detected orange peel texture. As discussed in more detail in U.S. Provisional Patent Application Serial No. 62 / 941286, filed November 27, 2019, trajectories may be based on repair paths designed to integrate repairs into the working surfaces of a vehicle. Database 350 may also include information about orange peel wrinkles 362, such as calibration information for converting the calculated orange peel wrinkles into standard orange peel wrinkle names used by a given vehicle manufacturer. Other orange peel wrinkle characteristic information may also be stored, such as deviations in the trajectory required based on the detected orange peel wrinkle depth or frequency. Database 350 may also include other information 364.

[0042] A repair strategy generator 300 is communicatively coupled to a robotic repair unit 370, which includes a robotic arm 372 coupled to a force control unit 375 associated with an end effector 376. The robotic repair unit may also have other features 378, such as a track unit allowing movement along a production line. The end effector 376 may be coupled to a tool having an abrasive article 380 that contacts a defect on a vehicle surface and performs a grinding operation. The robotic repair unit 370 is configured to move the abrasive article 380 along a path on the vehicle surface, thereby applying a certain amount of force at a series of points on the vehicle surface for a given time. Depending on the abrasive article, the force may also be applied at a given angle. The repair strategy generator 300 generates a trajectory for the robotic repair unit 370 to execute. The trajectory is generated based on the detected defect, known features of the vehicle surface (e.g., coating color, quantity, and thickness), known features of the abrasive article (e.g., wear level), and orange peel texture at the defect location.

[0043] Defect detector 302 detects defects on the vehicle surface, for example, by receiving images from first imaging system 310 and analysis from analyzer 316 indicating the presence of defects. Defect analyzer 304 can detect the type of defect and other characteristics of the detected defect. For example, defects can be detected based on light refracting away from the surface in an undesirable manner. Defect analyzer 304 can determine whether the detected defect is debris trapped under one or more layers of paint or clear coat. The trapped debris may affect the area on the vehicle surface detected by defect analyzer 304. The depth of the debris is also important for repair.

[0044] The orange peel analyzer 306 can receive images from the second image system 320 and determine the intensity of orange peel wrinkles on the surface based on the images. Orange peel wrinkles are characterized by a series of repeating bumps on the vehicle surface, similar to those on the outer surface of orange peel. (Return to Reference) Figure 3A and Figure 3B Orange peel refers to rolled ridges and valleys within the glossy surface of a painted surface. Depending on the process conditions, the rolled ridges can be larger (3B) or smaller (3A). Currently, many vehicle manufacturers use single numbers to characterize orange peel, where one refers to a tight formation of the orange peel pattern, and ten refers to a very soft orange peel.

[0045] The orange peel characterizer 308 can characterize orange peel based on analysis from the orange peel analyzer 306. Most orange peel characterization is currently performed using handheld devices or reference cards held in the area, and is done periodically in the paint shop to ensure the desired level of orange peel is maintained in specific areas of the vehicle. This process is highly subjective. In addition to providing numerical values ​​for orange peel on the vehicle, the orange peel characterizer 308 can provide other characterization information, including the average height and frequency of detected orange peel, and any other features that may help modify the repair trajectory.

[0046] The trajectory retrieval unit 332 retrieves trajectories for repair, for example, from trajectory data source 358. The retrieved trajectory may be based on, for example, the type or size of the detected defect, and / or on the location of the defect—for example, based on the relative flatness or curvature of the vehicle surface. The trajectory modifier 334 may modify the retrieved trajectory based on orange peel wrinkle features identified by the orange peel wrinkle characterizer 308. The retrieved trajectory may be retrieved from a database, for example, as a pre-generated trajectory template, or may be retrieved from a trajectory generator.

[0047] For example, if the scanned area is flat with minimal orange peel wrinkles, the processing time for the selected trajectory can be reduced by 25% of the total time to compensate for the fact that the process of smoothing the orange peel wrinkles through the defect is not required. However, if the scanned area has much more pronounced orange peel wrinkles than expected, the repair trajectory can have a 20% increase in total time to allow the process to compensate for the depth and frequency of the orange peel wrinkles.

[0048] The output communicator 342 can also provide information to another device about the detected defects, the characterized orange peel texture, and / or the repair trajectory. For example, an operator can receive such information on a mobile device such as a smartphone or computer. Alternatively, such information can be presented on a user interface associated with a given repair area.

[0049] Repair strategy communicator 340 transmits the modified trajectory to robotic repair unit 370. In some embodiments, the process of retrieving and modifying the trajectory of robotic repair unit 370 occurs in situ, allowing imaging systems (310, 320) to verify the location of the defect, detect and characterize orange peel wrinkles on the vehicle surface surrounding the defect, and provide the robotic repair unit 370 with the modified trajectory to perform all operations when the vehicle is in the repair position. During vehicle manufacturing, the vehicle may be on a moving line, preventing it from stopping at any given station. In such implementations, repair strategy generator 300 needs to rapidly gather information about the defect and the surface, and determine an appropriate repair trajectory within minutes or seconds so that the repair can be completed in a timely manner. Even in manufacturing scenarios where the vehicle is envisioned to be in the appropriate position at the repair station, long repair times are not permissible.

[0050] The repair strategy generator 300 may also include other components, such as any of those discussed in U.S. Provisional Patent Application Serial No. 62 / 941286, filed November 27, 2019.

[0051] Imaging systems 310 and 320 in Figure 4 The system is shown as two separate systems. However, as shown in Figure 5, in some embodiments, they may share at least some components. Additionally, either or both of imaging systems 310 and 320 may be mounted to the robotic repair unit 370. For example, in one embodiment, the orange peel imaging system 320 may be mounted on the end effector unit 376, or elsewhere on the robotic repair arm 370, such that the orange peel is imaged, analyzed, and characterized just before the abrasive article 380 contacts the vehicle surface and performs repairs. In some embodiments, both the first system 310 and the second system 320 are mounted separately from the robotic repair unit 370.

[0052] Figures 5A to 5B A repair imaging system according to an embodiment of this document is shown. Figure 5AAn imaging system 400 is shown that images a surface 410. Surface 410 is a reflective surface, for example, having one or more layers of transparent coating applied to the surface. The system has a distance 408 between a camera 406 and surface 410. A light bar 404 provides light to surface 410 in a focusing region 412. The system 400 has a processing unit 402 that provides power, control, and network access to the camera 406 and the light bar 404. In some embodiments, separate control and power are provided for each of the camera 406 and the light bar 404, such as... Figure 5A As shown. However, it is considered that both camera 406 and light bar 404 can be powered and controlled by a single source 402. Although light bar 404 is shown, other lighting sources are also explicitly considered.

[0053] In some implementations, the light stripe 404 is positioned at a certain angle relative to the focusing area 412, such as... Figure 5A As shown, the preferred angle is one where the reflective strip is placed at 25% of the center of the image, which reduces optical distortion. In some embodiments, the light from the light strip 404 is brighter than any other potential interfering light source. In some embodiments, blue and / or yellow hues are isolated from interference. In some embodiments, light diffusion renders individual LED point sources undetectable.

[0054] In some implementations, the distance 408 between the camera 406 and the surface 410 is relatively small, for example, less than 1000 mm, or even less than 900 mm, or even less than 800 mm, or even less than 700 mm, or even less than 600 mm, or even less than 500 mm, or even less than 400 mm, or even less than 300 mm.

[0055] In one embodiment, the light length 408 is greater than the focusing region 412. The light length 408 can be ten times the size of the focusing region 412. In one embodiment, the light length 408 is approximately 450 mm, while the focusing region 412 is 10 mm.

[0056] In one embodiment, system 400 is part of a robotic repair unit, for example, mounted on a robotic arm. System 400 may be included as part of an end effector assembly or may be mounted upstream of a force control unit. System 400 may also be configured to move while capturing images of a surface; for example, system 400 may move on a vehicle surface to collect images. In another embodiment, system 400 may be configured to be stationary while capturing images.

[0057] Figure 5B Another view of the camera system 450 is shown. A light source 460 is positioned between the first camera and the second camera 470. In some embodiments, the camera 470 and the light source 460 may pivot relative to a mounting.

[0058] In some implementations, cameras 406 and 470 are general-purpose cameras configured to capture images that may be stored in a database, such as database 350, as part of repair database 356 (e.g., before or after repair images) and may be retrieved later, for example, to display to an operator or for later analysis. Cameras 406 and 470 may also be used for other monitoring purposes, such as monitoring the repair process to detect wear on abrasive articles, or other functional problems with robotic repair units or other production line equipment.

[0059] In some implementations, cameras 406 and 470 are also networked to the production line and can receive information about the vehicle being imaged. This allows cameras 406 and 570 to be calibrated to parameters of a given vehicle, including paint color, paint and clear coat thickness, curvature of surfaces where defects are detected, etc. For example, many surfaces on a car are not flat. Knowing the location of defects on the car and having access to the vehicle's CAD model provides information on the car's curvature at the defect point, allowing for better analysis of the images retrieved by cameras 406 or 470.

[0060] Figure 6 A method for characterizing a working surface according to an embodiment of this document is illustrated. Method 500 provides a characteristic working surface that can be used to modify or generate a repair trajectory for repairing defects in or near the characteristic working surface.

[0061] In box 510, an image of the work surface is acquired. In some embodiments, acquiring the image includes setting a light source, as shown in box 502, which may include positioning a light strip or other suitable light source at an angle relative to the surface to be imaged. The light source may also be confirmed, for example, by confirming that sufficient reflections are captured from the correct area on the surface to be imaged, as shown in box 504.

[0062] Image acquisition may include image capture by a camera, as shown in box 512. The camera may be, for example, a high-resolution camera, such that there are a sufficient number of pixels in the image to detect surface features. However, due to the number of pixels, characterizing orange peel wrinkles on a surface can be time-consuming. Therefore, in some embodiments, it is desirable to reduce the amount of computation required. Because the time frame for detecting and repairing defects is short, the calculation of orange peel wrinkles and other surface features must be performed quickly so that the production line does not slow down to accommodate defect repair.

[0063] As shown in box 514, the image can be sampled, which includes sampling pixels in the image for processing. As shown in box 516, smearing can also be used to generalize the image, making the computation manageable in size. Other processing can also be performed, as shown in box 518. For example, confirmation of the presence of hotspots can be saved or output to the operator.

[0064] In box 520, contours are detected. Contours can be detected by recording differences in nearby pixels representing curves unrelated to the planned curvature of the working surface. For example, a car may have a planned curvature known from a CAD model of the surface. Contours with curvatures much smaller than the planned curvature can be detected, at least an order of magnitude smaller. Contours can be detected by detecting changes in the color of pixels indicating curvature. For example, returning to a reference... Figure 3A and Figure 3B The orange peel-like image can detect contours by observing changes in the color of adjacent pixels.

[0065] In box 530, the contour is characterized. Characterizing orange peel wrinkles typically involves calculating incremental values ​​representing the level of orange peel wrinkles, for example, by referring to... Figure 3A and Figure 3B The numbers “2” and “5”. Additionally, the calculated incremental values ​​can be calibrated to the manufacturer’s standards. Since many manufacturers have responded to the cellulite problem by developing their own cellulite scales, one benefit of using a cellulite characterization system networked to the manufacturer’s repair system is the ability to output a cellulite characterization that matches the standards used by the manufacturer. However, other characterizations are also possible, as shown in box 536.

[0066] In box 540, output characterization. Output characterization may include outputting the calculated or calibrated incremental values ​​to an operator-visible user interface. Output may also include storing the calculated or calibrated incremental values ​​in a database. Output may also include providing the calculated or calibrated incremental values ​​to a repair strategy generator.

[0067] In some implementations, method 500 is performed automatically. Method 500 may begin, for example, when a defect is detected by analyzing the same imaging used to detect the defect. In another implementation, method 500 is performed automatically only when the repair robot is within a given distance of the defect, for example, as... Figure 5A As shown, this allows for the calculation of orange peel wrinkles for a given defect essentially at the repair time. Method 500 can also be performed automatically at different times, such as essentially at the time the defect is detected.

[0068] Figure 7 A method for generating a repair strategy for defects, according to an embodiment of this document, is illustrated. Method 600 can be used by a repair strategy generation system to provide a repair strategy for a robotic repair unit.

[0069] In box 610, defects on the work surface are identified. Characterizing a defect may include the type, severity, or location of the defect on the vehicle. For example, defect type may include stains or scratches. Defect severity may refer to the area of ​​the work surface affected by the defect, the length of the defect, the height or depth of the defect, or another feature. Defect location may include its coordinate position on the vehicle's work surface. Characterizing a defect may also include the height of the defect relative to the work surface or its depth relative to a paint layer, such as whether the defect is located within a paint layer or a clear coat. Characterizing a defect may also include retrieving a pre-repair image of the work surface. Other features associated with the defect may also be retrieved.

[0070] Defect identification may include identifying the type of defect. Defect types may include excess paint, embedded debris, scratches, dents, cavitation, stains, or another defect in the painted surface. Defect identification may include identifying the location of the defect relative to the vehicle surface. Identifying the defect location may also include associating the defect with a point on the vehicle surface using a CAD model of the vehicle or a surface mesh. Defect identification may also include identifying the affected area of ​​the vehicle surface—for example, embedded debris may affect not only the area of ​​the debris but also the surface area immediately surrounding it. For example, this can be achieved using information about... Figure 6 The method discussed is 500 for characterizing orange peel wrinkles. However, other methods may also be suitable, as long as they occur automatically and consistently from defect to defect.

[0071] In box 620, the orange peel texture of the surface at the defect point is characterized. Previous attempts to repair defects relied on sampling the orange peel texture of the surface—identifying the average orange peel texture of a portion of a vehicle (e.g., the "hood" of a car) and assuming that the average remains locally close to the defect. The benefits of the system and method presented in this paper include the ability to detect and characterize the orange peel texture at the defect point in order to better tailor repair strategies to the defect.

[0072] In box 630, a repair trajectory is selected. Although box 630 is shown after box 620, this order is explicitly considered to be reversed. The trajectory can be selected based on the detected defect size, defect type, defect location, vehicle color, or another suitable parameter. The selected trajectory may include shape 632 or a path that the abrasive article will follow for repair. Path 632 may be a closed path that begins and ends at the same point, or an open path that begins and ends at different points. In one embodiment, orientation corresponds to a regular shape, including circular, elliptical, rosette, helical, or involute shapes. In another embodiment, orientation 1442 corresponds to an irregular shape. The shape may include curvature or straight lines, convex or concave portions, or other features. Generating a path may also include generating one or more orientations. For example, a support pad may uniformly contact the work surface such that uniform pressure is applied to the surface of the support pad and to the work surface. In another embodiment, the support pad is inclined with respect to at least a portion of the generated path. In some embodiments, the inclination may be inward or outward and may change during repair.

[0073] As shown in box 634, the generated path is time-parameterized to generate a repair trajectory. Time-parameterizing the path involves assigning velocity and acceleration along the generated path. Generating the time parameterization requires satisfying dynamic constraints such as the maximum velocity and acceleration achievable by the end effector tool and the robot itself, as well as jerk. Time parameterization may also include verifying the constraints after trajectory generation to ensure that the robot and end effector can achieve the trajectory. The abrasive workpiece may contact the work surface at multiple locations along the path for a given amount of time 634, or may experience different velocities at different points along the path 632. The trajectory may also include other parameters 636 at different points, such as applied force, grinding angle, etc.

[0074] In box 640, the selected trajectory is modified based on the characteristic orange peel texture at the defect point. For example, mild orange peel texture may allow for a reduction in time 634 at one or more points along path 632, while more severe orange peel texture may require additional time 636 at different points.

[0075] Executable method 600 allows the modified trajectory to be immediately implemented by the robotic repair unit. In some embodiments, the modification of the selected trajectory may never be presented to a human operator, so that the cellulite characterization remains as internal parameters calculated and used only by the repair strategy generator. However, in other embodiments, some information about the detected cellulite is presented to the operator or stored so that the operator can retrieve it later.

[0076] Figure 8This is a block diagram of a repair strategy generation architecture. Remote server architecture 800 illustrates one implementation of a specific implementation of the repair strategy generator 810. As an example, remote server architecture 800 can provide computing, software, data access, and storage services without requiring end users to know the physical location or configuration of the system delivering these services. In various implementations, the remote server can deliver these services over a wide area network (such as the Internet) using appropriate protocols. For example, the remote server can deliver applications over a wide area network, and these applications can be accessed via a web browser or any other computing component. Figures 1 to 7 The software or components shown or described herein, along with the corresponding data, may be stored on servers at remote locations. Computing resources in a remote server environment may be consolidated at remote data center locations, or they may be distributed. Remote server infrastructure can deliver services through shared data centers, even if they appear as a single access point for a user. Therefore, the components and functions described herein can be provided from remote servers at remote locations using a remote server architecture. Alternatively, they may be provided by conventional servers, installed directly on client devices, or otherwise provided.

[0077] exist Figure 8 In the examples shown, some items are similar to those shown in the previous figures. Figure 8 Specifically, the repair strategy generation system can be located at a remote server location 802. Therefore, the computing device 820 accesses those systems through the remote server location 802. The operator 850 can also use the computing device 820 to access the user interface 822.

[0078] Figure 8 It also depicts another example of a remote server architecture. Figure 8 The illustration also shows that some components of the system described herein are located at a remote server location 802, while other components are not located at that remote server location. By way of example, storage devices 830, 840, or 860, or repair system 870, may be located at a location separate from location 802 and accessed from location 802 via a remote server. Regardless of their location, they can be accessed directly by computing device 820 via a network (WAN or LAN), hosted at a remote site, provided as a service, or accessed by a connection service residing at a remote location. Furthermore, the data can be stored in substantially any location and can be accessed intermittently by interested parties or forwarded to interested parties. For example, a physical carrier may be used instead of an electromagnetic carrier, or a physical carrier may be used in addition to an electromagnetic carrier.

[0079] It should also be noted that the components or parts thereof of the systems described in this article can be mounted on a variety of different devices. Some of these devices include servers, desktop computers, laptop computers, embedded computers, industrial controllers, tablet computers, or other mobile devices such as handheld computers, cellular phones, smartphones, multimedia players, personal digital assistants, etc.

[0080] Figures 9 to 10 An example of a mobile device that can be used in the implementation shown in the previous figures is illustrated.

[0081] Figure 9 It is a handheld device 916 that can be used as a user or client (e.g., Figure 8 A simplified block diagram illustrating a handheld or mobile computing device (computing device 820) in which the system (or part thereof) of the present invention may be deployed. For example, the mobile device may be deployed in the operator compartment of the computing device 820 for generating, processing, or displaying data. Figure 10 This is another example of a handheld or mobile device.

[0082] Figure 9 A general block diagram of the components of a client device 916, which can operate some of the components shown and described herein, is provided. The client device 916 interacts with these components, or operates some of the components and interacts with others. In the device 916, a communication link 913 is provided that allows the handheld device to communicate with other computing devices and, in some embodiments, provides a channel for automatically receiving information (such as through scanning). Examples of the communication link 913 include those that allow communication via one or more communication protocols, such as wireless services for providing cellular access to a network and protocols for providing local wireless connectivity to a network.

[0083] In other examples, an application can be received on a removable secure digital (SD) card connected to interface 915. Interface 915 and communication link 913 communicate with processor 917 (which may also be embodied as a processor) along bus 919, which is also connected to memory 921 and input / output (I / O) components 923, as well as clock 925 and positioning system 927.

[0084] In one embodiment, I / O components 923 are provided to facilitate input and output operations, and device 916 may include input components such as buttons, touch sensors, optical sensors, microphones, touchscreens, proximity sensors, accelerometers, orientation sensors, and output components such as display devices, speaker and / or printer ports. Other I / O components 923 may also be used.

[0085] Clock 925 exemplarily includes a real-time clock component that outputs the time and date. It can also provide timing functions for processor 917.

[0086] Examplely, positioning system 927 includes a component that outputs the current geographic location of device 916. This positioning system may include, for example, a Global Positioning System (GPS) receiver, a LoRAN system, a dead reckoning system, a cellular triangulation system, or other positioning systems. It may also include, for example, mapping software or navigation software that generates desired maps, navigation routes, and other geographic functions.

[0087] Memory 921 stores operating system 929, network settings 931, application programs 933, application configuration settings 935, data storage 937, communication drivers 939, and communication configuration settings 941. Memory 921 may include all types of tangible, volatile, and non-volatile computer-readable storage devices. It may also include computer storage media (described below). Memory 921 stores computer-readable instructions that, when executed by processor 917, cause the processor to perform computer-implemented steps or functions. Processor 917 may also be activated by other components to facilitate its functionality.

[0088] Figure 10 The device shown is a smartphone 1071. The smartphone 1071 has a touch-sensitive display 1073 that displays icons or tiles or other user input mechanisms 1075. Mechanism 1075 can be used by the user to run applications, make calls, perform data transfer operations, etc. Generally, the smartphone 1071 is built on a mobile operating system and provides more advanced computing power and connectivity than non-smartphones.

[0089] It should be noted that other forms of device 1016 are possible.

[0090] Figure 11 It is a block diagram of a computing environment that can be used in the embodiments shown in the previous figures.

[0091] Figure 11 This is an example of a computing environment in which elements or, for example, portions of, the systems and methods described herein can be deployed. References Figure 11An exemplary system for implementing some embodiments includes a general-purpose computing device in the form of a computer 1110. Components of the computer 1110 may include, but are not limited to, a processing unit 1120 (which may include a processor), system memory 1130, and a system bus 1121 that connects various system components, including the system memory, to the processing unit 1120. The system bus 1121 may be any of several types of bus architectures, including a memory bus or memory controller, a peripheral bus, and a local bus using any of various bus architectures. The memory and programs described relative to the systems and methods described herein may be deployed on... Figure 11 In the corresponding part.

[0092] Computer 1110 typically includes a variety of computer-readable media. Computer-readable media can be any available medium accessible to computer 1110, and includes both volatile / non-volatile media and removable / non-removable media. By way of example and without limitation, computer-readable media can include computer storage media and communication media. Computer storage media are distinct from, and do not include, modulated data signals or carrier waves. Computer storage media include hardware storage media, which includes volatile / non-volatile and removable / non-removable media implemented in any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical disc storage devices, magnetic tape cassettes, magnetic tape, disk storage devices or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to computer 1110. Communication media can embody computer-readable instructions, data structures, program modules, or other data in a transport mechanism and includes any information delivery medium. The term "modulated data signal" refers to a signal whose characteristics are set or altered by encoding information in the signal.

[0093] System memory 1130 includes computer storage media in the form of volatile and / or non-volatile memory, such as read-only memory (ROM) 1831 and random access memory (RAM) 1132. A basic input / output system 1133 (BIOS) containing basic routines that facilitate the transfer of information between components within computer 1110 is typically stored in ROM 1131. RAM 1132 typically includes data and / or program modules that are immediately accessible and / or currently in operation by processing unit 1120. This is by way of example and not limitation. Figure 11 The operating system 1134, application program 1135, other program modules 1136, and program data 1137 are shown.

[0094] Computer 1110 may also include other removable / non-removable and volatile / non-volatile computer storage media. This is just one example. Figure 11 A hard disk drive 1141 is shown that reads from or writes to non-removable, non-volatile magnetic media, a non-volatile disk 1152, an optical disk drive 1155, and a non-volatile optical disk 1156. The hard disk drive 1141 is typically connected to the system bus 1121 via a non-removable memory interface such as interface 1140, and the optical disk drive 1155 is typically connected to the system bus 1121 via a removable memory interface such as interface 1150.

[0095] Alternatively or additionally, the functions described herein can be performed at least in part by one or more hardware logic components. For example, but not limited to, illustrative types of hardware logic components that can be used include field-programmable gate arrays (FPGAs), application-specific integrated circuits (e.g., ASICs), dedicated standard products (e.g., ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), etc.

[0096] The above discussion and Figure 11 The driver and its associated computer storage media shown provide computer 1110 with storage for computer-readable instructions, data structures, program modules, and other data. Figure 11 For example, hard disk drive 1141 is shown storing operating system 1144, application program 1145, other program modules 1146, and program data 1147. Note that these components may be the same as or different from operating system 1134, application program 1135, other program modules 1136, and program data 1137.

[0097] Users can input commands and information into computer 1810 via input devices such as keyboard 1162, microphone 1163, and pointing devices 1161 such as mouse, trackball, or touchpad. Other input devices (not shown) may include joysticks, gamepads, satellite receivers, scanners, etc. These and other input devices are typically connected to processing unit 1120 via user input interface 1160, which is connected to the system bus, but may be connected via other interfaces and bus structures. Visual display 1191 or other types of display devices are also connected to system bus 1121 via an interface such as video interface 1190. In addition to a monitor, the computer may also include other peripheral output devices, such as speakers 1197 and printer 1196, which may be connected via output peripheral interface 1195.

[0098] Computer 1110 operates in a networked environment of one or more remote computers, such as remote computer 1180, using a logical connection such as a local area network (LAN) or a wide area network (WAN).

[0099] When used in a LAN networking environment, computer 1110 connects to LAN 1171 via a network interface or adapter 1170. When used in a WAN networking environment, computer 1110 typically includes a modem 1172 or other devices for establishing communication via WAN 1173 (e.g., the Internet). In a networking environment, program modules may be stored in remote memory storage devices. For example, Figure 11 This demonstrates that remote application 1185 can reside on remote computer 1180.

[0100] An imaging and repair system is proposed, comprising a first imaging system configured to image defects on a working surface. The system also includes a second imaging system configured to image and characterize the working surface at the defect location. The system further includes a defect repair processor configured to select a repair strategy based on defect type. The system also includes a defect modifier configured to modify the selected repair strategy based on the characterization of the working surface. Finally, the system includes a defect repair tool configured to automatically implement the modified repair strategy.

[0101] The system can be implemented such that a first imaging system includes a first camera configured to capture multiple first images of a working surface. These multiple first images are stored in a data source.

[0102] The system can be implemented such that the second imaging system includes a second camera configured to capture multiple second images of the working surface. These multiple second images are stored in a database. The second camera is separate from the first camera.

[0103] The system can be implemented such that the second or more images include images of the working surface close to the defect.

[0104] The system may also include a light source.

[0105] The system may also include a defect detector configured to detect defects in a first plurality of images.

[0106] The system can be implemented to detect defects including defect type, defect size, defect severity, or defect location.

[0107] The system can be implemented such that it also includes a defect analyzer configured to associate the location of a defect with its location on a 3D representation of the working surface.

[0108] The system can be implemented such that a second imaging system is guided to image the working surface based on the location.

[0109] The system can be implemented such that characterizing the working surface includes incremental values ​​that identify orange peel wrinkles.

[0110] The system can be implemented such that it also includes an orange peel wrinkle processor configured to sample pixels from the plurality of second images and calculate incremental values ​​based on the sampled pixels.

[0111] The system can be implemented such that it includes an orange peel wrinkle processor configured to: smear the images in the plurality of second images and calculate incremental values ​​based on the sampled images.

[0112] The system can be implemented such that the defect repair tool includes: a powered robotic arm, a force control unit coupled to the powered robotic arm, an end effector coupled to the force control unit, and a grinding tool coupled to the end effector. The grinding tool is configured to engage the working surface at the defect.

[0113] The system can be implemented such that it includes an imaging system mount configured to be coupled to a second imaging system.

[0114] The system can be implemented such that the second imaging system includes a light source.

[0115] The system can be implemented such that the light source is at an angle relative to the working surface.

[0116] The system can be implemented such that when a second or more images are captured, the second imaging system is within 1 meter of the surface.

[0117] The system can be implemented such that the working surface is a vehicle. The working surface is characterized as a flat surface, and based on the characterized flat surface, the modified repair strategy includes a shorter processing time than the selected repair strategy.

[0118] An orange peel imaging system is proposed, comprising an orange peel light source configured to direct light onto an area on a work surface. The system also includes an orange peel camera configured to capture an image of the orange peel in the area. Furthermore, the system includes a processing camera configured to capture an image of defects in the area. Finally, the system includes a processor configured to analyze the orange peel image, detect contours in the area, calculate incremental values ​​of the detected contours, and output the calculated incremental values.

[0119] The cellulite imaging system may also include a cellulite communicator configured to transmit the output incremental values ​​to a second system.

[0120] The cellulite imaging system may also include a mounting component configured to connect the cellulite camera to the robotic repair unit.

[0121] The orange peel wrinkle imaging system can be implemented such that the robotic repair unit is a power unit capable of bringing the orange peel wrinkle camera within 2 meters of the work surface.

[0122] The orange peel wrinkle imaging system can be implemented such that the robotic repair unit includes a force control unit coupled to an end effector. This end effector is coupled to an abrasive workpiece that contacts the working surface at the detected defect.

[0123] This orange peel wrinkle imaging system can be implemented such that analyzing orange peel wrinkle images includes sampling pixels in the image of the region.

[0124] This orange peel wrinkle imaging system can be implemented such that analyzing orange peel wrinkle images includes smearing the image of the region.

[0125] The orange peel wrinkle imaging system can be implemented such that the image of the area is stored in a database.

[0126] This orange peel wrinkle imaging system can be implemented such that images of defects are stored in a database.

[0127] The orange peel wrinkle imaging system may also include a repair generation system configured to generate a repair strategy for defects. This repair strategy is generated, at least in part, by analyzing the orange peel wrinkle image.

[0128] A method for characterizing orange peel texture on vehicle surfaces is proposed. The method includes acquiring images of a region of the vehicle surface using a camera. The method also includes processing the acquired images using a processor to detect contours within the region. Furthermore, the method includes identifying incremental values ​​of the contours using the processor. Finally, the method includes outputting analysis results using a communication channel. These analysis results include indications of the detected contours and incremental values ​​of the detected contours.

[0129] This method can be implemented such that processing the acquired image includes color correction of the image.

[0130] This method can be implemented such that processing the acquired image includes applying a Gaussian blur to the image.

[0131] The method may also include determining the scale of the detected contour.

[0132] The method may also include directing a focused beam of light from a light source to an area on the vehicle surface.

[0133] This method can be implemented such that the camera is positioned within a certain range of the area. This range is within one meter.

[0134] This method can be implemented such that the camera is brought into the range by a powered robotic arm.

[0135] This method can be implemented such that, in response to a detected defect in the area, the camera is automatically brought into the range.

[0136] This method can be implemented to automatically perform the steps of acquisition, processing, identification, and output in response to defects detected in the region.

[0137] This method can be implemented such that a communication channel outputs analysis results to a repair strategy generator, which generates a repair strategy for the detected defects based on the detected contours and the detected incremental values.

[0138] A method for generating a repair process for defects on a working surface is proposed. The method includes detecting defects in a region of the working surface. The method also includes characterizing the region of the working surface. The method further includes selecting a repair strategy based on the detected defects. The method also includes modifying the selected repair strategy based on the characterized parameters to obtain the repair process. The characterization, selection, and modification steps occur automatically based on the detected defects on the working surface.

[0139] This method can be implemented such that the detected defects include the type of defect, the size of the defect, or the severity of the defect.

[0140] This method can be implemented such that the detection includes detecting a defect that is repairable.

[0141] This method can be implemented such that selecting a repair strategy includes selecting a repair path along the working surface for the abrasive article.

[0142] The method can be implemented such that the repair path includes a series of time-parameterized positions of the abrasive article on the working surface, and for each position, the abrasive article experiences a certain pressure, velocity, contact angle, or duration.

[0143] This method can be implemented such that the selected repair strategy is modified based on the characterized region, including modifications to the experienced pressure, velocity, contact angle, or duration.

[0144] The method can be implemented such that the region characterizing the working surface further includes: acquiring an image of the region of the working surface using an orange peel camera, analyzing the image of the region to detect contours, and calculating the incremental value of the detected contours.

[0145] The method may also include calibrating the calculated incremental values.

[0146] This method can be implemented such that the modified repair strategy is provided to the robotic repair unit for automatic execution.

[0147] The method may also include outputting an image of the detected defect.

[0148] The method may also include outputting the characterization of the working surface as a numerical value.

[0149] This method can be implemented to characterize the region as flatter than expected, and the selected repair strategy can be modified to reduce the repair time used to compensate for the flatter surface.

[0150] This method can be implemented to characterize the region as having more pronounced orange peel wrinkles than expected. Modifying the chosen repair strategy includes increasing the repair time used for compensation.

Claims

1. An imaging and repair system, comprising: A first imaging system configured to image and detect defects on a work surface, wherein the first imaging system includes a first camera configured to capture a plurality of first images of the work surface, wherein the plurality of first images are stored in a data source. A second imaging system is configured to image and characterize orange peel wrinkles on the working surface in a region adjacent to the defect, wherein characterizing the working surface includes identifying incremental values ​​of orange peel wrinkles. A defect repair processor, configured to select a repair strategy based on the defect type; A defect modifier configured to modify a repair strategy for the defect based on the characterization of the orange peel texture on the working surface in the region adjacent to the defect. and A defect repair tool, which is configured to automatically implement the modified repair strategy.

2. The system of claim 1, wherein the second imaging system includes a second camera configured to capture a plurality of second images of the working surface, wherein the plurality of second images are stored in a database, wherein the second camera is separate from the first camera.

3. The system of claim 2, wherein the plurality of second images includes an image of the working surface in proximity to the defect.

4. The system according to claim 1, further comprising a structured light source.

5. The system of claim 1, wherein the second imaging system is guided to image the working surface based on the location of the detected defects received from the first imaging system.

6. The system according to claim 2 or 3, further comprising an orange peel wrinkle processor, the orange peel wrinkle processor being configured to: Pixels are sampled from the images in the plurality of second images; and The incremental value is calculated based on the sampled pixels.

7. The system of claim 2, further comprising an orange peel wrinkle processor, the orange peel wrinkle processor being configured to: Smear the images in the plurality of second images; and The incremental value is calculated based on the sampled image.

8. The system of claim 1, further comprising an imaging system mount configured to be coupled to the second imaging system.

9. The system of claim 4, wherein the light source is at an angle relative to the working surface.

10. The system of claim 2, wherein when the plurality of second images are captured, the second imaging system is within 1 meter of the surface.

11. The system of claim 1, wherein the working surface is a vehicle, and wherein the characterization of the working surface includes a flat surface, and wherein, Based on the characterized flat surface, the modified repair strategy includes a shorter processing time than the selected repair strategy.

12. An orange peel wrinkle imaging system, comprising: Orange peel wrinkle light source, the orange peel wrinkle light source being configured to direct light onto a working surface near a defect area; An orange peel camera, the orange peel camera being configured to capture orange peel images of the region; An orange peel wrinkle processor is configured to analyze the orange peel wrinkle image, detect contours indicating orange peel wrinkles in the region, calculate the increment value of the detected orange peel wrinkle contours, and output the calculated orange peel wrinkle increment value. A repair generation system configured to generate a repair strategy for the defect by at least partly analyzing the orange peel wrinkle image of the working surface in the region adjacent to the defect.

13. The orange peel wrinkle imaging system according to claim 12, further comprising: An orange peel wrinkle communicator is configured to transmit the output orange peel wrinkle increment value to a second system.

14. The orange peel wrinkle imaging system according to claim 12 or 13, wherein the orange peel wrinkle imaging system further comprises: Mounting device configured to connect the orange peel camera to the robotic repair unit.

15. The orange peel imaging system according to claim 14, wherein the robotic repair unit is a power unit capable of bringing the orange peel camera within 2 meters of the working surface.

16. The orange peel wrinkle imaging system of claim 15, wherein the robotic repair unit includes a force control unit coupled to an end effector, wherein the end effector is coupled to an abrasive article that contacts the working surface at the detected defect.

17. The orange peel wrinkle imaging system of claim 12, wherein analyzing the orange peel wrinkle image includes sampling pixels in the orange peel wrinkle image.

18. The orange peel wrinkle imaging system of claim 12, wherein analyzing the orange peel wrinkle image includes smearing the orange peel wrinkle image.

19. The orange peel wrinkle imaging system according to claim 12, wherein the orange peel wrinkle images are stored in a database.

20. A method for characterizing orange peel wrinkles on a vehicle surface, the method comprising: An orange peel wrinkle camera is used to acquire images of the area on the vehicle surface that is close to the area where defects are detected; The acquired image is processed using a processor to detect contours in the region adjacent to the detected defect; The contour was identified as an orange peel wrinkle contour; The processor is used to identify the orange peel wrinkle increment value of the orange peel wrinkle contour; as well as The analysis results are output to the repair strategy generator using a communication channel. These results include indicators of the detected orange peel wrinkle contours and the detected orange peel wrinkle increment values. The repair strategy generator uses the orange peel contour and the orange peel increment value detected in the region of the vehicle surface near the defect to generate a repair strategy for the defect.

21. The method of claim 20, wherein processing the acquired image includes applying a Gaussian blur to the image.

22. The method according to any one of claims 20 to 21, the method further comprising determining the scale of the detected contour.

23. The method of claim 20, further comprising directing a focused beam from the orange peel wrinkle light source to the region on the vehicle surface.

24. The method of claim 20, wherein the orange peel wrinkle camera is located within a certain range of the area, wherein the range is within one meter.

25. The method of claim 24, wherein the orange peel wrinkle camera is brought into the range by a powered robotic arm.

26. The method of claim 25, wherein the orange peel camera is automatically brought into the range in response to a defect detected in the area.

27. The method of claim 20, wherein the steps of acquiring, processing, identifying, and outputting are automatically performed in response to a defect detected in the region.

28. A method for generating a repair process for defects on a working surface, the method comprising: Detect defects in areas on the working surface; Orange peel wrinkles characterizing the region of the working surface adjacent to the detected defect, wherein characterizing the orange peel wrinkles includes: Images of the area on the working surface are acquired using an orange peel wrinkle camera; Analyze the image of the region to detect the contours of orange peel wrinkles; and Calculate the incremental value of the detected orange peel wrinkle contour; Based on the detected defects, select a remediation strategy; The repair strategy for the defect is modified based on the characterization of the orange peel texture on the working surface in the region adjacent to the defect to obtain the repair process; and The characterization, selection, and modification steps occur automatically based on the defects detected on the working surface.

29. The method of claim 28, wherein detecting the defect includes detecting the defect type, defect size, or defect severity.

30. The method according to any one of claims 28 to 29, wherein selecting a repair strategy includes selecting a repair path along the working surface for the abrasive article.

31. The method of claim 30, wherein the repair path comprises a time-parameterized series of positions of the abrasive article on the working surface, and wherein, For each location, the abrasive article is subjected to a certain pressure, speed, contact angle, or duration.

32. The method according to claim 31, wherein, The repair strategy selected based on the characterized orange peel wrinkle modification includes modifying the pressure, speed, contact angle, or duration experienced.

33. The method of claim 32, further comprising calibrating the calculated orange peel wrinkle increment value.

34. The method of claim 28, wherein the region is characterized as being flatter than expected, and wherein modifying the selected repair strategy includes reducing the repair time used to compensate for the flatter surface.

35. The method of claim 28, wherein the region is characterized as having more pronounced orange peel wrinkles than expected, and wherein modifying the selected repair strategy includes increasing the repair time for compensation.

Images