Track verification and generation method and generation system of spraying robot

Abstract

The invention relates to a track verification method, a track generation method and a track generation system for a spraying robot, and the verification method comprises the steps: defining a plurality of reference points before a target spraying track is generated, and forming a corresponding derivative vector based on the plurality of reference points; derivation vectors are obtained, the reference points are verified based on bidirectional vector closed-loop detection, and point position sequence verification information is obtained; checking the plurality of reference points based on an Euclidean distance measurement mode and obtaining point location distance checking information; checking the plurality of reference points based on the dot product ratio of the derivative vector, and obtaining parallelism checking information; and checking the plurality of reference points based on point multiplication of derivative vectors, and obtaining coplanarity checking information. According to the method, the target operation scene is fully evaluated through verification systems of the point position sequence, the point distance, the parallelism and the like, the operation reliability of the spraying robot is improved, and the operation efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent control, and in particular to trajectory verification, generation methods, and generation systems for painting robots. Background Technology

[0002] In traditional automotive, furniture, and general industrial parts painting operations, trajectory planning still primarily relies on "manual teaching + trial spraying correction." Operators record the spray gun's position point by point using a teaching pendant, followed by actual spraying tests, and then repeatedly fine-tuning based on film thickness deviations. This method has the following drawbacks: long teaching cycle: on average, it takes 3-5 days to complete the full trajectory calibration for a new car model; poor fault tolerance: even slight anomalies in the input point set (such as reversed order or two points being too close) can lead to trajectory distortion, with film thickness deviations reaching ±25μm; reliance on experience: when changing production lines for the same workpiece, the teaching results from different technicians vary greatly, making consistency difficult to guarantee.

[0003] In recent years, 3D vision + offline programming solutions have emerged in the market. A typical workflow is as follows: 3D line laser or structured light scans the workpiece → acquires a point cloud; extracts edge features → generates a primitive set; discretizes into six-dimensional pose points according to preset offset and spacing parameters; outputs a robot executable file. While this type of solution eliminates manual teaching, it only performs two-dimensional convex hull or minimum bounding box detection, failing to identify three-dimensional anomalies such as spatial coplanarity and sequence conflicts, and lacks comprehensive pre-generation verification of the generated trajectory. This can lead to situations where the target work scene is not adequately evaluated when following the generated work trajectory, resulting in work interruptions. Summary of the Invention

[0004] Therefore, it is necessary to provide trajectory verification and generation methods and systems for painting robots to address the problem of easy interruption during operation.

[0005] A trajectory verification method for a painting robot, the verification method comprising: before generating the target painting trajectory, Define several reference points within the target work area, and form a corresponding first derived vector based on the several reference points; The first derived vector is obtained, and based on bidirectional vector closed-loop detection, several reference points are verified to obtain point position order verification information. It is determined whether the point position order verification information is within the point position order threshold. If it is within the point position order threshold, the point position order verification is passed. Based on the Euclidean distance measurement method, several reference points are checked and point distance verification information is obtained. It is determined whether the point distance verification information is within the point distance threshold. If it is within the point distance threshold, the point distance verification is passed. The dot product ratio of the derived vectors is used to check several reference points and obtain parallelism verification information. It is then determined whether the parallelism verification information is within the parallelism threshold. If it is within the parallelism threshold, the parallelism detection is passed. The dot product of the derived vectors is used to test several reference points and obtain coplanarity test information. It is then determined whether the coplanarity test information is within the coplanarity threshold. If it is within the coplanarity threshold, the coplanarity test is passed.

[0006] In one preferred embodiment, the verification method further includes: Obtain the spraying scene information of the target spraying robot, and adjust the point distance threshold, parallelism threshold, and coplanarity threshold based on the spraying scene information.

[0007] In one preferred embodiment, adjusting the point distance threshold, parallelism threshold, and coplanarity threshold based on the spraying scene information includes: Based on the acquired spraying scene information, the spraying fan width of the spraying robot is adjusted; Based on the range to which the sprayed fan width belongs, the corresponding point distance threshold, parallelism threshold, and coplanarity threshold are obtained.

[0008] In one preferred embodiment, the point distance threshold is obtained based on the range to which the sprayed fan width belongs, satisfying:

[0009] Where BM is the base sector. This is the current point distance. As the transition center location, For the steepness coefficient of the transition, This is the transition width adjustment factor. This is the distance threshold between the points.

[0010] In one preferred embodiment, the verification method further includes: Select two of the reference points, and select the vertex of the arc on the arc generated between the two selected reference points; Based on the arc vertex and the two corresponding selected reference points, a derived vector is formed. The arc surface verification information is obtained according to the three-point collinearity detection method. It is determined whether the arc surface verification information is within the arc surface threshold. If it is within the arc surface threshold, the arc surface threshold detection is passed.

[0011] In one preferred embodiment, the verification method further includes: after generating the target spraying trajectory, evaluating the deviation between the generated trajectory and the theoretical trajectory using the Fraser distance; if the deviation is greater than the deviation threshold, the verification fails. Trajectory abrupt changes are generated by detecting the rate of change of acceleration. When the rate of change of acceleration is greater than the acceleration threshold, the generated estimate is corrected.

[0012] In one preferred embodiment, the verification method further includes: after generating the target spraying trajectory, The generated spraying trajectory of the spraying robot is compared with the actual spraying trajectory using a discrete verification model for verification. The discrete verification model satisfies the following:

[0013] Among them, the This represents the actual spraying trajectory. For the generated spray pattern, Let the velocity along the actual spraying trajectory be a continuously monotonically increasing function from the interval [0,1] to itself. Let the velocity of the generated spraying trajectory be a continuously monotonically increasing function from the interval [0,1] to itself. This is the current time.

[0014] The trajectory verification method described in this embodiment generates a spraying trajectory after verification by using a verification system that includes point sequence, point distance, and parallelism. This allows for a thorough evaluation of the target work scenario before generating the spraying trajectory, solving problems such as work interruptions caused by the spraying trajectory not matching the work scenario. This improves the reliability of the spraying robot's operation and increases its efficiency.

[0015] A method for generating the trajectory of a painting robot, the method comprising: Perform the trajectory verification method according to any one of claims 1 to 5; If the verification is successful, the reference point is imported into the trajectory generation model to generate a spraying trajectory within the target work area.

[0016] In one preferred embodiment, if the reference point passes the reference point verification, the reference point is imported into the trajectory generation model to generate a spraying trajectory within the target work area. The spraying trajectory includes a spraying height trajectory, which satisfies the following:

[0017] in, For spraying height, As the reference spraying height, This is the atomization correction factor. The atomization index, For reference to the atomization index, The fan width attenuation coefficient is... For fan width sensitivity, As the base fan width, This is the minimum effective sector.

[0018] In one preferred embodiment, if the reference point passes the reference point verification, the reference point is imported into the trajectory generation model to generate a spraying trajectory within the target work area. The spraying trajectory includes a spraying angle trajectory, which satisfies the following:

[0019] in, For the final spraying angle, As the reference spraying angle, This is the atomization correction factor. The atomization index, The fan width attenuation coefficient is... For fan width sensitivity, The atomization index.

[0020] The trajectory generation method described in this embodiment obtains a verification system for point order, point distance, parallelism, etc. before generating the trajectory. After verification, the spraying trajectory is generated. In this way, the target operation scenario is fully evaluated before the spraying trajectory is generated, which solves the problem of operation interruption caused by the spraying trajectory not conforming to the operation scenario. This improves the reliability of the spraying robot's operation and increases the operation efficiency.

[0021] A trajectory generation system for a painting robot, comprising: The trajectory verification module is used to define several reference points in the target work area and to verify the reference points. The reference point verification includes verifying the positional order of the several reference points, detecting the point distance, detecting parallelism, and detecting coplanarity. The trajectory generation module is used to import the reference points into the trajectory generation model if the reference points are verified, so as to generate a spraying trajectory in the target working area.

[0022] The trajectory verification method described in this embodiment generates a spraying trajectory after verification by using a verification system that includes point sequence, point distance, and parallelism. This allows for a thorough evaluation of the target work scenario before generating the spraying trajectory, solving problems such as work interruptions caused by the spraying trajectory not matching the work scenario. This improves the reliability of the spraying robot's operation and increases its efficiency. Attached Figure Description

[0023] Figure 1 This is a first flowchart of the trajectory verification method disclosed in the first preferred embodiment of the present invention; Figure 2 This is a second flowchart of the trajectory verification method disclosed in the first preferred embodiment of the present invention; Figure 3 This is a schematic diagram of the trajectory generation system disclosed in the second preferred embodiment of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0025] It should be noted that when an element is referred to as being "set on" another element, it can be directly on the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0027] like Figure 1 As shown, in a first preferred embodiment of the present invention, a trajectory verification method for a painting robot includes: before generating the target painting trajectory, S10: Define several reference points within the target work area, and form a corresponding first derived vector based on the several reference points.

[0028] Specifically, in this embodiment, the number of reference points defined in the target working area is 4. For example, the 4 reference points can be defined as A, B, C, and D. The first derived vector is formed based on the 4 reference points. For example, the first derived vector can be AB / BC / BD / CD / DA / DC, etc.

[0029] S20: Obtain the first derived vector, and based on bidirectional vector closed-loop detection, verify several reference points and obtain point position order verification information. Determine whether the point position order verification information is within the point position order threshold. If it is within the point position order threshold, then pass the point position order verification.

[0030] Specifically, a first derived vector is formed based on the aforementioned reference points. The point order verification includes verifying the reference points using bidirectional vector closed-loop detection to obtain point order verification information. It is then determined whether the point order verification information is within a point order threshold. If it is within the threshold, the point order verification passes. This method improves reliability compared to the traditional single-fork product method and is compatible with both left-handed and right-handed painting robots.

[0031] In this embodiment, the input point set preprocessing involves defining four points (ABCD), selecting and calculating their derived vectors. , , , The above-mentioned bidirectional vector closed-loop detection verifies several reference points and obtains point position order verification information. It then determines whether the point position order verification information is within a point position order threshold. Specifically, the bidirectional vector closed-loop detection includes using the derived vector based on the right-handed spraying principle. , Perform the cross product to obtain its normal vector. The right-handed normal vector is obtained based on the following formula:

[0032] Next, based on the left-handed spraying principle, the aforementioned derived vectors are used... , Perform the cross product to obtain its normal vector. The left-handed normal vector is obtained based on the following formula:

[0033] Finally, based on the above right-hand normal vector and left-hand normal vector Having obtained the above point sequence verification information, more specifically, calculate... and dot product value The dot product value This is the above point sequence verification information. If the point sequence verification information... Greater than the above point order threshold If so, the verification is successful. The above point sequence verification information is obtained based on the following formula:

[0034] In this embodiment, the above-mentioned point order threshold The value is 0.95. Conversely, if the above point sequence verification information... Less than or equal to the above point order threshold If the input order is not met, the validation will fail. In this case, this step can prompt the user to check the input order of the point set.

[0035] S30: Based on the Euclidean distance measurement method, several reference points are checked and point distance verification information is obtained. It is determined whether the point distance verification information is within the point distance threshold. If it is within the point distance threshold, the point distance verification is passed.

[0036] Specifically, in this embodiment, step S30 uses the Euclidean distance formula to calculate the vectors AB, BC, and BD, and determines the distance between each point. If any one of them is less than the distance tolerance, the verification fails.

[0037] Euclidean distance is a measure of the straight-line distance between two points in three-dimensional space, and its mathematical essence is the calculation of vector magnitude. In the trajectory verification of painting robots, reference points usually refer to the trajectory feature points input by the user (such as path start points, inflection points, arc control points, etc.). If adjacent reference points are too close, it will cause the robot's motion trajectory to overlap, the paint to be too thick, or the motion acceleration to change abruptly. If they are too far apart, it may cause paint omissions or trajectory breaks.

[0038] More specifically, let's assume the spatial coordinates of the selected base point are P. i (x) i y i , z i The spatial coordinates of the next base point adjacent to the selected base point are P. i+1 (x) i+1 y i+1 , z i+1 ), then the adjacent point (P) i P i+1 The difference vector of )

[0039] Based on the above formula, the Euclidean distance is obtained using the above Euclidean distance test method. The specific Euclidean distance test method includes the following:

[0040] The actual distance L between each adjacent point is obtained using the Euclidean distance metric method described above.

[0041] By comparing the actual distance L between each of the above adjacent points with the point distance threshold In comparison, a point distance verification is performed. Specifically, if the actual distance L ≥ the point distance threshold... If the distance is less than the point distance threshold, the system will determine that the point distance verification has been passed, allowing the system to proceed to the subsequent trajectory generation stage. The system triggered an error and terminated trajectory generation, prompting the user to adjust the distribution of reference points.

[0042] In this embodiment, the aforementioned point spacing threshold is adjusted dynamically. Adjustments will be made; specifically, the aforementioned point distance thresholds will be adjusted. The point distance threshold is adjusted based on the spraying scene information. More specifically, based on the acquired spraying scene information, the spraying fan width W of the spraying robot is adjusted, and the corresponding point distance threshold is obtained based on the range to which the spraying fan width W belongs. In this embodiment, the above-mentioned spraying scene information includes narrow-width spraying scene, standard spraying scene, and wide-width spraying scene. In the narrow-width spraying scene, the spraying fan width W < 100mm, and the dot pitch threshold is... Approaching 0.3mm, due to the concentrated flow field in the narrow area, it is necessary to improve the trajectory accuracy and adjust the point spacing threshold accordingly. This avoids the problem of coating overlap caused by trajectory deviation.

[0043] More specifically, the above-mentioned point distance threshold Adjustments are made using the hyperbolic tangent function to achieve a smooth transition; more specifically, the aforementioned point-to-point threshold... satisfy:

[0044] Where BM is the base sector. This is the current point distance. As the transition center location, For the steepness coefficient of the transition, This is the transition width adjustment factor. In this embodiment, the aforementioned current point distance... The value range is [0, 1], and the above transition center position The default value can be 0.5, and the aforementioned transition steepness coefficient... The transition width adjustment factor can be between 5 and 10. It can be between 0.1 and 0.3.

[0045] S40: Based on the dot product ratio of the derived vectors, several reference points are checked to obtain parallelism verification information. It is determined whether the parallelism verification information is within the parallelism threshold. If it is within the parallelism threshold, the parallelism detection is passed.

[0046] In this step, the parallelism verification based on the derivative vector dot product is the key link in the geometric integrity detection of the spraying robot trajectory in this embodiment. Its core is to quantify the spatial angle relationship between the edges by performing the dot product operation between the vectors formed by adjacent reference points, and to determine whether there are geometric deformities caused by excessive parallelism in the trajectory, such as "collapsed edges" or "acute angle turns".

[0047] Specifically, the derived vectors are first normalized. More specifically, a reference point set (such as A, B, C, and D) is used to verify the distances between points in the previous steps to ensure the correct point order and compliant point distances. Then, for consecutive adjacent point pairs, vectors are calculated. , , , Finally, normalization is performed, specifically converting the above vectors into unit vectors, for example: ，

[0048] Next, the dot product of the aforementioned unit vectors of adjacent units is calculated to obtain the parallelism verification information. For example, the parallelism verification information can be the following dot product result: dot product result =

[0049] Finally, the dot product result is compared with the parallelism threshold. In this embodiment, the preset parallelism threshold can be... Set the corresponding minimum allowed angle. ,like At that time, the above parallelism threshold More specifically, the above dot product result is ≤ the parallelism threshold. If the result is positive, the parallelism test is passed; otherwise, if the dot product result is greater than the parallelism threshold, the parallelism test is passed. If not, then it will not pass the parallel detection.

[0050] The aforementioned parallelism threshold can be dynamically adapted to the spraying scenario of the target spraying robot. Specifically, the spraying scenario information of the target spraying robot is obtained, and the parallelism threshold is adjusted based on the spraying scenario information. More specifically, the spraying fan width of the spraying robot is adjusted based on the obtained spraying scenario information; and the corresponding parallelism threshold information is obtained based on the range to which the spraying fan width belongs. In this embodiment, in a conventional scenario, the spraying fan width... Between 100mm and 300mm, the above... The value is set to 0.99, which balances the trajectory flexibility and safety of the painting robot in this scenario. In high-pressure scenarios, the spray pattern of the painting robot is adjusted to achieve this spray pattern. When the adjustment is less than 100mm, the above parallelism threshold information is obtained. The value is set to 0.99. In high-pressure scenarios, this results in finer atomized particles, a thinner coating, and a smaller trajectory turning angle to avoid paint buildup. In low-pressure scenarios, the spray pattern of the aforementioned spraying robot is adjusted. Adjusted to greater than 300mm, the above parallelism threshold information is now available. The value is 0.95. At this value, large-scale spraying allows for a larger turning angle and a wider coverage area. The threshold is relaxed to reduce unnecessary system errors.

[0051] S50: Based on the dot product of the derived vectors, several reference points are tested to obtain coplanarity test information. It is determined whether the coplanarity test information is within the coplanarity threshold. If it is within the coplanarity threshold, the coplanarity test is passed.

[0052] In this embodiment, step S50, which involves checking the coplanarity of derived vector dot products, is the core step in verifying the spatial geometry of the spraying robot's trajectory. By determining whether the four reference points are coplanar, it avoids trajectory generation failure or uneven spraying thickness caused by distortion of the spatial point set. The following is a detailed description of this step: In this step, selecting four reference points (such as ABCD) to be coplanar is a prerequisite for generating a continuous and smooth trajectory. If spatial distortion exists (such as point D deviating from the ABC plane), the robot will produce a normal angle deviation during spraying, resulting in a coating thickness difference greater than 5μm. Traditional two-dimensional plane detection (such as least squares fitting) cannot handle three-dimensional spatial problems.

[0053] More specifically, based on the selected reference points, three non-collinear vectors are constructed, for example... , , Next, the three vectors are multiplied by a dot product, specifically:

[0054] In the above formula, This is information for coplanarity testing.

[0055] Next, the above coplanarity test information will be... Coplanarity threshold In comparison, if the coplanarity test information ≤ After passing the coplanarity test, the process proceeds to subsequent trajectory generation. If the coplanarity test information... > If the coplanarity is not detected, then it will not pass the coplanarity test.

[0056] The aforementioned coplanarity threshold can be dynamically adapted to the spraying scenario of the target spraying robot. Specifically, the spraying scenario information of the target spraying robot is obtained, and the coplanarity threshold is adjusted based on the spraying scenario information. More specifically, the spraying fan width of the spraying robot is adjusted based on the obtained spraying scenario information; based on the range to which the spraying fan width belongs, the corresponding coplanarity threshold information is obtained. In this embodiment, in a high-pressure scenario, the spraying fan width of the spraying robot is adjusted to... When the adjustment is less than 100 mm, the aforementioned coplanarity threshold is reached. satisfy: In low-pressure scenarios, adjust the spray pattern of the aforementioned spraying robot to achieve the desired spray pattern. Adjusted to a value greater than 300 mm, the aforementioned coplanarity threshold is now... satisfy: .

[0057] In typical scenarios, spraying fan width Between 100mm and 300mm, the aforementioned coplanarity threshold is... satisfy:

[0058] In the above formula, W represents the spray pattern width. Furthermore, the above formula can be used to smoothly transition the coplanarity threshold from the high-pressure scenario to the low-pressure scenario.

[0059] Based on the coplanarity test of derived vector dot products, a hybrid product mathematical model is used to quantify three-dimensional spatial relationships. Combined with dynamic thresholds of process parameters, high-precision spatial verification of industrial-grade trajectory planning is achieved. Its core innovation lies in transforming abstract vector geometry into an engineeringable "deviation value-threshold" judgment standard, filling the gap in the application of traditional two-dimensional detection in three-dimensional space.

[0060] In addition to the steps mentioned above, combined with Figure 2 As shown, this method also includes a semi-circular expansion check, which includes: S61: Select two of the reference points, and select the vertex of the arc on the arc generated between the two selected reference points; Specifically, in the above steps, two of the four reference points (A, B, C, D) are selected (e.g., A and B). Based on the two selected reference points (A and B), point M is selected on the arc trajectory corresponding to the line connecting the two. Point M is the vertex of the arc. Point M is the "third vertex" on the arc corresponding to chord AB, and point M cannot be collinear with A and B.

[0061] S62: Based on the arc vertex and the two corresponding selected reference points, a derived vector is formed. The arc surface verification information is obtained according to the three-point collinearity detection method. It is determined whether the arc surface verification information is within the arc surface threshold. If it is within the arc surface threshold, the arc surface threshold detection is passed.

[0062] In this embodiment, a derived vector for verification is constructed based on the arc vertex M and the corresponding two reference points (A, B) determined in step S61. Specifically, the derived vector includes a base vector and an associated vector. The base vector points from reference point A to the base vector of reference point B (denoted as...). The aforementioned associated vector is the vector pointing from the reference point A to the vertex M of the arc (denoted as...). ), representing the geometric relationship from A to the vertex of the arc; the vector pointing from the reference point B to the vertex M of the arc (denoted as ). This is used to assist in verifying the rationality of the position of the arc vertex. The coordinate calculation of the above derived vectors must be based on the robot coordinate system (compatible with left-handed / right-handed systems, determined through the previous point position sequence verification). The coordinate values ​​are directly derived from the three-dimensional coordinates of points A, B, and M obtained in the input preprocessing stage to ensure the geometric accuracy of the vectors.

[0063] In this embodiment, the aforementioned arc surface verification information is obtained through vector cross multiplication. Specifically, the aforementioned vector is taken... and Then perform a cross product operation to obtain its normal vector. ,like:

[0064] Based on the above normal vector The normal vector is obtained. Length of the module The length of the module This refers to the aforementioned arc surface verification information.

[0065] In this embodiment, the aforementioned arc surface threshold is 1E-5, and the aforementioned arc surface verification information is... Compared with the threshold of the arc surface, if the calculated normal vector magnitude is... If points A, B, and M form a valid arc, the arc surface threshold is detected. Subsequently, the center and radius of the arc will be calculated based on these three points to provide the geometric basis for generating the arc spraying trajectory. If the error occurs, an error reporting mechanism will be triggered. At this time, the selection position of point M needs to be readjusted, or the reference points A and B need to be re-taught until the arc surface threshold detection is passed, so as to avoid spraying defects caused by invalid arc trajectory.

[0066] More specifically, the aforementioned semi-circular expansion verification can also be adjusted according to the spraying scenario. Specifically, for high-pressure narrow-width spraying scenarios: by accurately verifying the position of point M, high-energy flow field coating defects (such as paint film thickness deviation) caused by arc trajectory deviation can be avoided; for ultra-wide-width spraying scenarios (W>300mm): although the coplanarity threshold can be relaxed, the validity verification of the arc vertex still needs to be performed to ensure the trajectory continuity within the coverage area of ​​the wide-width atomized plume.

[0067] After completing the above verification, if the verification passes, the present invention further includes a trajectory generation method. This method imports the reference point into a trajectory generation model to generate a spraying trajectory within the target work area. Specifically, the spraying trajectory includes a spraying height trajectory and a spraying angle trajectory. The spraying height trajectory satisfies the following:

[0068] in, For spraying height, As the reference spraying height, This is the atomization correction factor. The atomization index, For reference to the atomization index, The fan width attenuation coefficient is... For fan width sensitivity, As the base fan width, This is the minimum effective sector.

[0069] The above spraying angle trajectory satisfies:

[0070] in, For the final spraying angle, As the reference spraying angle, This is the atomization correction factor. The atomization index, The fan width attenuation coefficient is... For fan width sensitivity, The atomization index.

[0071] After generating the target spraying trajectory, the above verification method also includes evaluating the deviation between the generated trajectory and the theoretical trajectory using the Fréchet distance. If the deviation exceeds a deviation threshold, the verification fails. Specifically, the generated trajectory is the robot-executable trajectory finally generated after the above verification method, consisting of a discretized three-dimensional trajectory point set; the theoretical trajectory is an ideal trajectory preset based on the workpiece geometric model (such as edge features obtained from 3D scanning) and spraying process requirements (such as fan width and number of coatings), also existing in the form of a three-dimensional discrete point set; the generated spraying trajectory and the actual spraying trajectory of the spraying robot are imported into a discrete verification model for verification, wherein the discrete verification model satisfies:

[0072] Among them, the This represents the actual spraying trajectory. For the generated spray pattern, Let the velocity along the actual spraying trajectory be a continuously monotonically increasing function from the interval [0,1] to itself. Let the velocity of the generated spraying trajectory be a continuously monotonically increasing function from the interval [0,1] to itself. This is the current time.

[0073] If the calculated discrete Frescher distance This indicates that the geometry of the generated trajectory is consistent with the theoretical trajectory, with no significant spatial distortion, and it can proceed to the next step of motion school testing. This is the deviation threshold.

[0074] If the above discrete Frechet distance If the error is identified as "geometric distortion of the trajectory," a three-stage response mechanism for geometric distortion is triggered, which is processed according to the magnitude of the deviation. More specifically, the above deviation magnitude classification includes slight distortion (1mm < deviation < 3mm), moderate distortion (3mm < deviation < 5mm), and severe distortion (deviation > 5mm). If it is slight distortion, local trajectory regeneration is automatically triggered, without the need for overall recalculation, reducing verification time. If it is moderate distortion, the robot's movement is paused, and a "manual intervention prompt" pops up on the teach pendant interface, allowing operators to manually correct the reference point or adjust the threshold coefficient. After correction, the verification is re-executed. If it is severe distortion, the robot's movement is stopped immediately, the trajectory generation system is locked, and the deviation data is recorded. Technicians must investigate the root cause and unlock the system before it can be restarted.

[0075] On the other hand, after generating the target spraying trajectory, the above verification method also includes detecting abrupt changes in the generated trajectory by the rate of change of acceleration. When the rate of change of acceleration is greater than the acceleration threshold, the generation estimate is corrected.

[0076] The trajectory verification method described in this embodiment generates a spraying trajectory after verification by using a verification system that includes point sequence, point distance, and parallelism. This allows for a thorough evaluation of the target work scenario before generating the spraying trajectory, solving problems such as work interruptions caused by the spraying trajectory not matching the work scenario. This improves the reliability of the spraying robot's operation and increases its efficiency.

[0077] like Figure 3 As shown, the second preferred embodiment of the present invention is a trajectory generation system 100 for a painting robot, which includes a trajectory verification module 110 and a trajectory generation module 120.

[0078] The trajectory verification module 110 is used to define a number of reference points in the target work area and to verify the reference points. The reference point verification includes verifying the positional order of the reference points, detecting the distance between them, detecting parallelism, and detecting coplanarity. Specifically, the trajectory verification module 110 includes a point position sequence verification unit 111, a point distance detection unit 112, a parallelism verification unit 113, and a coplanarity verification unit 114. The point position sequence verification unit 111 defines several reference points within the target working area, forms corresponding first derived vectors based on these reference points, obtains the first derived vectors, and verifies the reference points based on bidirectional vector closed-loop detection to obtain point position sequence verification information. It then determines whether the point position sequence verification information is within a point position sequence threshold. If it is within the threshold, the point position sequence verification is passed. A more detailed verification method is described in the first embodiment above, which will not be repeated here. The point distance detection unit 112 verifies the reference points based on Euclidean distance measurement to obtain point distance verification information. It then determines whether the point distance verification information is within a point distance threshold. If it is within the threshold, the point distance verification is passed. A more detailed verification method is described in the first embodiment above, which will not be repeated here. Parallelism verification unit 113 verifies several reference points based on the dot product ratio of derived vectors and obtains parallelism verification information. It then determines whether the parallelism verification information is within a parallelism threshold. If it is within the threshold, a more detailed verification method is performed through parallelism detection, as described in the first embodiment above, which will not be repeated here. Coplanarity verification unit 114 verifies several reference points based on the dot product of derived vectors and obtains coplanarity verification information. It then determines whether the coplanarity verification information is within a coplanarity threshold. If it is within the threshold, a more detailed verification method is performed through coplanarity detection, as described in the first embodiment above, which will not be repeated here.

[0079] If the trajectory verification module 110 completes the above verification and passes the verification, the trajectory generation module 120 imports the reference point into the trajectory generation model to generate a spraying trajectory within the target work area. Specifically, the spraying trajectory includes a spraying height trajectory and a spraying angle trajectory, and the spraying height trajectory satisfies the following:

[0080] in, For spraying height, As the reference spraying height, This is the atomization correction factor. The atomization index, For reference to the atomization index, The fan width attenuation coefficient is... For fan width sensitivity, As the base fan width, This is the minimum effective sector.

[0081] The above spraying angle trajectory satisfies:

[0082] in, For the final spraying angle, As the reference spraying angle, This is the atomization correction factor. The atomization index, The fan width attenuation coefficient is... For fan width sensitivity, The atomization index.

[0083] After generating the target spraying trajectory, the trajectory verification module 110 further includes evaluating the deviation between the generated trajectory and the theoretical trajectory using the Friesian distance. If the deviation exceeds a deviation threshold, the verification fails. Specifically, the generated trajectory is the robot-executable trajectory finally generated after the verification method, consisting of a discretized set of three-dimensional trajectory points; the theoretical trajectory is an ideal trajectory preset based on the workpiece geometric model (such as edge features obtained from 3D scanning) and spraying process requirements (such as fan width and number of coatings), also existing in the form of a three-dimensional discrete point set; the generated spraying trajectory and the actual spraying trajectory of the spraying robot are imported into a discrete verification model for verification, wherein the discrete verification model satisfies:

[0084] Among them, the This represents the actual spraying trajectory. For the generated spray pattern, Let the velocity along the actual spraying trajectory be a continuously monotonically increasing function from the interval [0,1] to itself. Let the velocity of the generated spraying trajectory be a continuously monotonically increasing function from the interval [0,1] to itself. This is the current time.

[0085] If the calculated discrete Frescher distance This indicates that the geometry of the generated trajectory is consistent with the theoretical trajectory, with no significant spatial distortion, and it can proceed to the next step of motion school testing. This is the deviation threshold.

[0086] If the above discrete Frechet distance If the error is identified as "geometric distortion of the trajectory," a three-stage response mechanism for geometric distortion is triggered, which is processed according to the magnitude of the deviation. More specifically, the above deviation magnitude classification includes slight distortion (1mm < deviation < 3mm), moderate distortion (3mm < deviation < 5mm), and severe distortion (deviation > 5mm). If it is slight distortion, local trajectory regeneration is automatically triggered, without the need for overall recalculation, reducing verification time. If it is moderate distortion, the robot's movement is paused, and a "manual intervention prompt" pops up on the teach pendant interface, allowing operators to manually correct the reference point or adjust the threshold coefficient. After correction, the verification is re-executed. If it is severe distortion, the robot's movement is stopped immediately, the trajectory generation system is locked, and the deviation data is recorded. Technicians must investigate the root cause and unlock the system before it can be restarted.

[0087] On the other hand, after generating the target spraying trajectory, the above verification method also includes detecting abrupt changes in the generated trajectory by the rate of change of acceleration. When the rate of change of acceleration is greater than the acceleration threshold, the generation estimate is corrected.

[0088] The trajectory verification method described in this embodiment generates a spraying trajectory after verification by using a verification system that includes point sequence, point distance, and parallelism. This allows for a thorough evaluation of the target work scenario before generating the spraying trajectory, solving problems such as work interruptions caused by the spraying trajectory not matching the work scenario. This improves the reliability of the spraying robot's operation and increases its efficiency.

[0089] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0090] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A trajectory verification method for a painting robot, characterized in that, The verification method includes: before generating the target spraying trajectory, Define several reference points within the target work area, and form a corresponding first derived vector based on the several reference points; The first derived vector is obtained, and based on bidirectional vector closed-loop detection, several reference points are verified to obtain point position order verification information. It is determined whether the point position order verification information is within the point position order threshold. If it is within the point position order threshold, the point position order verification is passed. Based on the Euclidean distance measurement method, several reference points are checked and point distance verification information is obtained. It is determined whether the point distance verification information is within the point distance threshold. If it is within the point distance threshold, the point distance verification is passed. The dot product ratio of the derived vectors is used to check several reference points and obtain parallelism verification information. It is then determined whether the parallelism verification information is within the parallelism threshold. If it is within the parallelism threshold, the parallelism detection is passed. The dot product of the derived vectors is used to test several reference points and obtain coplanarity test information. It is then determined whether the coplanarity test information is within the coplanarity threshold. If it is within the coplanarity threshold, the coplanarity test is passed.

2. The trajectory verification method for a painting robot according to claim 1, characterized in that, The verification method further includes: Obtain the spraying scene information of the target spraying robot, and adjust the point distance threshold, parallelism threshold, and coplanarity threshold based on the spraying scene information.

3. The trajectory verification method for a painting robot according to claim 2, characterized in that, The adjustment of the point distance threshold, parallelism threshold, and coplanarity threshold based on the spraying scene information includes: Based on the acquired spraying scene information, the spraying fan width of the spraying robot is adjusted; Based on the range to which the sprayed fan width belongs, the corresponding point distance threshold, parallelism threshold, and coplanarity threshold are obtained.

4. The trajectory verification method for a painting robot according to claim 3, characterized in that, Based on the range to which the sprayed fan width belongs, the corresponding point distance threshold is obtained, satisfying: Where BM is the base sector. This is the current point distance. As the transition center location, For the steepness coefficient of the transition, This is the transition width adjustment factor. This is the distance threshold between the points.

5. The trajectory verification method for a painting robot according to claim 1, characterized in that, The verification method further includes: Select two of the reference points, and select the vertex of the arc on the arc generated between the two selected reference points; Based on the arc vertex and the two corresponding selected reference points, a derived vector is formed. The arc surface verification information is obtained according to the three-point collinearity detection method. It is determined whether the arc surface verification information is within the arc surface threshold. If it is within the arc surface threshold, the arc surface threshold detection is passed.

6. The trajectory verification method for a painting robot according to claim 1, characterized in that, The verification method further includes: after generating the target spraying trajectory, evaluating the deviation between the generated trajectory and the theoretical trajectory by the Fraser distance; if the deviation is greater than the deviation threshold, the verification fails. Trajectory abrupt changes are generated by detecting the rate of change of acceleration. When the rate of change of acceleration is greater than the acceleration threshold, the generated estimate is corrected.

7. The trajectory verification method for a painting robot according to claim 6, characterized in that, The method of evaluating the deviation between the generated trajectory and the theoretical trajectory using the Fraser distance includes: The generated spraying trajectory of the spraying robot is compared with the actual spraying trajectory using a discrete verification model for verification. The discrete verification model satisfies the following: Among them, the This represents the actual spraying trajectory. For the generated spray pattern, Let the velocity along the actual spraying trajectory be a continuously monotonically increasing function from the interval [0,1] to itself. Let the velocity of the generated spraying trajectory be a continuously monotonically increasing function from the interval [0,1] to itself. This is the current time.

8. A method for generating the trajectory of a painting robot, characterized in that, The generation method includes: Perform the trajectory verification method according to any one of claims 1 to 5; If the verification is successful, the reference point is imported into the trajectory generation model to generate a spraying trajectory within the target work area.

9. The trajectory generation method for a painting robot according to claim 8, characterized in that, If the reference point passes the reference point verification, the reference point is imported into the trajectory generation model to generate a spraying trajectory within the target work area. The spraying trajectory includes a spraying height trajectory, which satisfies the following: in, For spraying height, As the reference spraying height, This is the atomization correction factor. The atomization index, For reference to the atomization index, The fan width attenuation coefficient is... For fan width sensitivity, As the base fan width, This is the minimum effective sector.

10. The trajectory generation method for a painting robot according to claim 8, characterized in that, If the reference point passes the reference point verification, the reference point is imported into the trajectory generation model to generate a spraying trajectory within the target work area. The spraying trajectory includes a spraying angle trajectory, which satisfies the following: in, For the final spraying angle, As the reference spraying angle, This is the atomization correction factor. The atomization index, The fan width attenuation coefficient is... For fan width sensitivity, The atomization index.

11. A trajectory generation system for a painting robot, characterized in that, include: The trajectory verification module is used to define several reference points in the target work area and to verify the reference points. The reference point verification includes verifying the positional order of the several reference points, detecting the point distance, detecting parallelism, and detecting coplanarity. The trajectory generation module is used to import the reference points into the trajectory generation model if the reference points are verified, so as to generate a spraying trajectory in the target working area.

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