Intelligent positioning system and positioning method applied to spraying robot

Abstract

The present invention relates to the field of intelligent positioning technology, specifically to an intelligent positioning system and positioning method applied to a spraying robot, wherein the positioning system includes a light field data acquisition module, a particle tracking calculation module, an acoustic wave precision ranging module, and a dynamic verification execution module. In the present invention, a multi-sensing technology synthesis is used to perform all-round perception of the operating environment of the spraying robot, and the precise position of the spray head is updated by real-time capture of light field data and precise calculation of particle dynamics strategies to ensure spraying accuracy, which can greatly improve the real-time response capability to environmental changes and the dynamic adjustment capability of the spraying process, reduce material waste and improve coating quality and production efficiency. The added acoustic wave precision ranging enhances the robustness and reliability of the system in complex industrial environments through the fusion of acoustic wave and light field information, and precise tracking is combined with real-time position adjustment to ensure that each spraying reaches the optimal quality.

Description

Technical Field

[0001] The present invention relates to the field of intelligent positioning technology, and in particular to an intelligent positioning system and a positioning method applied to a spraying robot. Background Art

[0002] The field of intelligent positioning technology covers various methods based on sensors, algorithms and data processing technologies to achieve location detection and tracking. Usually laser scanning (LiDAR) or visual recognition systems are used to obtain data. By analyzing the data, the intelligent system can determine the location of objects and navigate. In addition, intelligent positioning technology is also widely used in automation and robotics, where accurate positioning information is crucial for robots to perform tasks.

[0003] Among them, the main purpose of the intelligent positioning system applied to the spraying robot is to guide the operation path and spraying position of the spraying robot through high-precision positioning technology in the industrial manufacturing process (especially in the automobile manufacturing process). The spraying robot can automatically apply paint or coating on different surfaces according to the preset program, which can ensure that each spraying is accurate, thereby improving production efficiency and coating quality, reducing material waste, and adapting to complex and changing industrial environments.

[0004] Although existing technologies such as laser scanning and visual recognition perform well in position detection and tracking, their effectiveness is limited in dynamic and fast-changing production environments, when faced with special conditions such as dust and smoke. Laser scanning technology is inefficient in dusty environments, and visual systems are significantly affected by light and field of view obstructions. These factors may cause positioning errors in actual operations, affecting the robot's operating efficiency and coating quality. In addition, a single technology is difficult to adapt to fast-moving parts or different reflective materials on the production line, resulting in reduced system accuracy, increased production costs and material waste. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent positioning system and a positioning method for a spraying robot.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: the intelligent positioning system applied to the spraying robot includes:

[0007] The light field data acquisition module uses a camera to surround the spraying area, continuously capture the direction and intensity changes of light, record the light information reflected at different angles, and generate the light field information of the vehicle body;

[0008] The particle tracking calculation module captures the reflection and scattering data of paint particles through sensors, combines the vehicle body light field information, analyzes the time reverse flow of the interaction between light and particles, tracks the flight path of each particle according to the time reverse flow analysis results, and records the landing point to obtain the particle interaction positioning result;

[0009] The acoustic wave precision distance measurement module configures an acoustic wave sensor array in the spraying area, collects reflected acoustic wave signals, measures the time delay of reflected acoustic wave signals, calculates the distance between the spray head and the vehicle surface based on the time delay measurement results combined with the acoustic wave velocity, and outputs the acoustic wave distance data;

[0010] The dynamic verification execution module adjusts the position of the spray head according to the particle interaction positioning result and the acoustic wave distance data, monitors the position change during the real-time spraying process, confirms that each spraying is accurately aimed at the target position, and generates a positioning accuracy verification record.

[0011] As a further solution of the present invention, the step of acquiring the vehicle body light field information is:

[0012] Deploy cameras around the vehicle body spraying area to continuously monitor the direction and intensity of light, record the direction and intensity of light in real time, and generate light direction and intensity data;

[0013] Analyze the light changes under different reflection angles according to the light direction and intensity data to obtain angle reflection light change data;

[0014] Based on the angle reflected light change data, the formula is used:

[0015] ;

[0016] Calculate the total intensity of the light field , generate vehicle light field information; where, represents the incident light intensity, represents the reflectivity, and are the angles of incidence and reflection, respectively.

[0017] As a further solution of the present invention, the calculation steps of the time reversal are:

[0018] Arrange sensors around the vehicle body, and capture the reflection and scattering of paint particles by adjusting the sensitivity and position of the sensors to obtain preliminary reflection and scattering data;

[0019] The preliminary reflection and scattering data are combined with the vehicle body light field information to refine the light field environment of each data point using the formula:

[0020] ;

[0021] Calculate the average interaction strength , generating particle interaction data with comprehensive light field information; where, Representative The strength of the data points, Indicates The light field intensity value corresponding to the data point is is the total number of data points;

[0022] Based on the particle interaction data of the comprehensive light field information, the interaction process between particles and light is simulated, the interaction time and environment are calculated, and the time reverse flow analysis result is obtained.

[0023] As a further solution of the present invention, the step of obtaining the particle interaction positioning result is:

[0024] Utilizing the time reverse flow analysis results, extracting the spatial coordinates and state data of the particles at different time points, performing point-by-point analysis on each particle, analyzing the particle velocity vector and direction changes, reconstructing the particle flight path, and generating paint particle path data;

[0025] Integrate the paint particle path data with the spatial coordinates, measure the end point position of each paint particle, record the landing point of each paint particle, and obtain the paint particle landing point coordinate data;

[0026] The paint particle landing point coordinate data is analyzed to determine the distribution characteristics and interaction patterns of the paint particles, perform spatial positioning analysis of particle interaction, and generate particle interaction positioning results.

[0027] As a further solution of the present invention, the step of measuring the time delay is:

[0028] Install acoustic wave sensors at key points in the spraying area, confirm that each sensor fully covers the corresponding area, and generate a full coverage acoustic wave sensor array;

[0029] activating the full-coverage acoustic wave sensor array, synchronously emitting acoustic waves and recording the time and intensity of the acoustic wave signals reflected from the surface of the vehicle body, and generating a reflected acoustic wave signal record;

[0030] According to the reflected sound wave signal record, the formula is used:

[0031] ;

[0032] Calculate the propagation delay of sound waves , generate acoustic signal time delay data, where, represents the distance traveled by the sound wave in the medium, represents the speed of sound waves, Represents the baseline distance from the acoustic wave sensor to the reflecting surface.

[0033] As a further solution of the present invention, the step of acquiring the acoustic wave distance data is:

[0034] Collect the time delay data of the acoustic wave signal, extract the time for the acoustic wave to travel from the emission point to the vehicle body surface and then return to the sensor, perform time synchronization on each data point, and generate a processed time delay data set;

[0035] The processed time delay data set is combined with the acoustic wave velocity using the formula:

[0036] ;

[0037] Calculate the one-way distance of the sound wave from the spray head to the car body surface , generate one-way distance data, where is the speed of sound waves in air, For time delay;

[0038] The one-way distance data is analyzed, the data is verified and adjusted, it is confirmed that the distance between the spray head and the vehicle body surface is maintained within the optimal working range during the spraying process, and the acoustic wave distance data is output.

[0039] As a further solution of the present invention, the steps for obtaining the positioning accuracy verification record are:

[0040] Using the particle interactive positioning result and the acoustic wave distance data, the ideal position that the spray head should reach is determined through real-time monitoring feedback, and ideal spray head position information is generated;

[0041] According to the ideal spray head position information, the spray head position is adjusted and matched in real time, using the formula:

[0042] ;

[0043] Calculate the position difference that needs to be adjusted , get the spray position adjustment result, where Represents the ideal spray head position, Represents the current spray head position;

[0044] Monitor the deviation between the spray position adjustment result and the ideal position, using the formula:

[0045] ;

[0046] Calculate the percentage of position deviation , generate positioning accuracy verification records.

[0047] The intelligent positioning method applied to the spraying robot includes the following steps:

[0048] S1: Deploy cameras around the vehicle body spraying area to continuously monitor the light direction and intensity, analyze the light changes under different reflection angles, calculate the total intensity of the light field, and generate the vehicle body light field information;

[0049] S2: Arrange sensors around the vehicle body to capture the reflection and scattering data of paint particles, combine them with the light field information of the vehicle body, refine the light field environment of each data point, calculate the average interaction intensity, simulate the interaction process between particles and light, and obtain the time reverse flow analysis results;

[0050] S3: using the time backflow analysis result, analyzing the particle velocity vector and direction change, reconstructing the particle flight path, measuring and recording the end position of each paint particle, performing spatial positioning analysis of particle interaction, and generating particle interaction positioning results;

[0051] S4: Installing acoustic wave sensors at key points in the spraying area, synchronously emitting acoustic waves and recording the time and intensity of acoustic wave signals reflected from the vehicle body surface, calculating the acoustic wave propagation delay, and generating acoustic wave signal time delay data;

[0052] S5: collecting the time delay data of the acoustic wave signal, performing time synchronization on each data point, combining it with the acoustic wave velocity, calculating the one-way distance of the acoustic wave from the spray head to the vehicle body surface, verifying and adjusting the data, and outputting the acoustic wave distance data;

[0053] S6: using the particle interaction positioning result and the acoustic wave distance data, determining the ideal position that the spray head should reach, adjusting and matching the spray head position in real time, calculating the deviation between the adjustment result and the ideal position, and generating a positioning accuracy verification record.

[0054] Compared with the prior art, the advantages and positive effects of the present invention are:

[0055] In the present invention, multi-sensing technology synthesis is utilized to perform all-round perception of the operating environment of the spray robot. The precise position of the spray head is updated by real-time capture of light field data and accurate calculation of particle dynamics to ensure spraying accuracy. This can greatly improve the real-time response capability to environmental changes and the dynamic adjustment capability of the spraying process, reduce material waste, and improve coating quality and production efficiency. The added acoustic wave precise ranging can enhance the robustness and reliability of the system in complex industrial environments through the fusion of acoustic wave and light field information. Accurate tracking combined with real-time position adjustment ensures that each spraying achieves optimal quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 is a flow chart of the positioning system of the present invention;

[0057] Figure 2 This is a flow chart for obtaining vehicle body light field information of the present invention;

[0058] Figure 3 It is a calculation flow chart of time reverse flow of the present invention;

[0059] Figure 4 A flowchart for obtaining the particle interaction positioning result of the present invention;

[0060] Figure 5 It is a flow chart of measuring time delay of the present invention;

[0061] Figure 6 This is a flow chart for obtaining the acoustic wave distance data of the present invention;

[0062] Figure 7 This is a flow chart for obtaining the positioning accuracy verification record of the present invention. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0064] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0065] See also Figure 1 , the intelligent positioning system used in spraying robots includes:

[0066] The light field data acquisition module uses a camera to surround the spraying area, continuously capture the direction and intensity changes of light, record the light information reflected at different angles, and generate the light field information of the vehicle body;

[0067] The particle tracking calculation module captures the reflection and scattering data of paint particles through sensors, combines the light field information of the vehicle body, analyzes the time reverse flow of the interaction between light and particles, tracks the flight path of each particle based on the time reverse flow analysis results, and records the landing point to obtain the particle interaction positioning results;

[0068] The acoustic wave precision distance measurement module configures an acoustic wave sensor array in the spraying area, collects reflected acoustic wave signals, measures the time delay of reflected acoustic wave signals, calculates the distance between the spray head and the vehicle surface based on the time delay measurement results combined with the acoustic wave velocity, and outputs the acoustic wave distance data;

[0069] The dynamic verification execution module adjusts the position of the spray head according to the particle interaction positioning results and the acoustic wave distance data, monitors the position changes during the real-time spraying process, confirms that each spray is accurately aimed at the target position, and generates a positioning accuracy verification record.

[0070] The vehicle light field information includes angle index results, light intensity level records and reflection mode records; the particle interaction positioning results include trajectory vectors, impact points and backflow calculation results; the sound wave distance data includes delay time, propagation rate and measurement accuracy; the positioning accuracy verification records include position adjustment detail records, monitoring feedback records and precise alignment verification results.

[0071] See also Figure 2 , the steps to obtain the vehicle light field information are:

[0072] Deploy cameras around the vehicle body spraying area to continuously monitor the direction and intensity of light, record the direction and intensity of light in real time, and generate light direction and intensity data;

[0073] After arranging multiple high-precision cameras around the car body spraying area, the system starts to continuously monitor the direction and intensity of light. These cameras will capture light data at a preset sampling frequency, including the incident angle and light intensity value of each moment. Through the high-speed data processing unit, the data stream sent back from each camera is received in real time, and the data is preliminarily screened and sorted. During the screening process, abnormal data points caused by environmental factors, such as sudden light increase or decrease, are removed, and stable and representative light data are retained. The screened data will be used to further analyze the behavior of light on the surface of the car body, such as reflection, refraction and absorption, etc., to provide accurate basic data for the next step of light characteristic analysis.

[0074] According to the light direction and intensity data, analyze the light changes under different reflection angles to obtain the angle reflection light change data;

[0075] Based on the light direction and intensity data, we enter a deeper data processing stage, which focuses on identifying the reflection characteristics of light at different angles and analyzing the light reflection patterns in these data, especially how light is reflected differently by the materials on the surface of the vehicle under different lighting conditions. By comparing and analyzing the light intensity and direction data collected at different angles, we can identify the regularity and randomness of light reflection. This analysis relies on the detailed segmentation of light data, and each segment of data is mapped to a specific reflection angle and light intensity, which can accurately simulate the overall behavior of light on the surface of the vehicle.

[0076] Based on the angle reflected light change data, the formula is used:

[0077] ;

[0078] Calculate the total intensity of the light field , generate vehicle light field information; where, represents the incident light intensity, represents the reflectivity, and are the angles of incidence and reflection, respectively;

[0079] Incident light intensity It is constant at each measurement point, such as 500 lux. It is also assumed to be uniform at all measurement points, i.e., 0.5.

[0080] Recalculate the formula:

[0081]

[0082] ;

[0083] In order to reflect the actual situation, consider only calculating the integral of the light on the hemisphere, that is, from 0 to , because in reality, one side of the car body will receive more light, especially considering the geometric characteristics of the car body and the position of the light source.

[0084]

[0085] ;

[0086] The total light field intensity obtained is about 1570 lux, indicating that under uniform distribution conditions, the overall light field intensity of the vehicle body is mainly concentrated on one side, which quantitatively understands the distribution of light on the vehicle body when light is irradiated from a specific direction.

[0087] See also Figure 3 , the analysis steps of time reversal are:

[0088] Arrange sensors around the vehicle body, and capture the reflection and scattering of paint particles by adjusting the sensitivity and position of the sensors to obtain preliminary reflection and scattering data;

[0089] The deployment of sensors first determines the optimal position based on the results of optical simulation. The installation point of each sensor is to capture the maximum reflection and scattering effects of paint particles at different angles. In addition, the sensitivity of each sensor is precisely adjusted according to the physical properties of the particles, such as size and reflectivity, as well as the material and color of the vehicle surface, to ensure that weak light signals can be detected. The output of each sensor is instantly converted into an electrical signal, which is converted into digital data after being processed by an analog-to-digital converter. The digital data is transmitted to the central processing unit in real time. By comparing the differences in data received by different sensors, the distribution and concentration of the particles are preliminarily determined, and a preliminary reflection and scattering data set is generated.

[0090] Combine the preliminary reflection and scattering data with the vehicle light field information to refine the light field environment of each data point using the formula:

[0091] ;

[0092] Calculate the average interaction strength , generating particle interaction data with comprehensive light field information; where, Representative The strength of the data points, Indicates The light field intensity value corresponding to the data point is is the total number of data points;

[0093] There are three data points, corresponding to three different sensor positions, and the particle reflection intensity at each position is and the corresponding light field intensity As shown below:

[0094] Position 1: units, lux;

[0095] Position 2: units, lux;

[0096] Position 3: units, lux.

[0097] Plugging the values ​​into the formula calculates the contribution of each term:

[0098] Position 1:

[0099] ;

[0100] Position 2:

[0101] ;

[0102] Position 3:

[0103] ;

[0104] Adding these three values ​​together gives the total combined data strength:

[0105] ;

[0106] Divide the sum by the number of data points to calculate the mean:

[0107] ;

[0108] The result shows that considering the particle reflection intensity and light field intensity at different positions, the combined average interaction intensity is 777.78. This means that on average, the interaction intensity between the particle and the light field at each sensor position is about 777.78 units / lux. This value reflects the average efficiency of the interaction between the particle and the light field under given experimental settings and environmental conditions.

[0109] Based on the particle interaction data of comprehensive light field information, the interaction process between particles and light is simulated, the interaction time and environment are calculated, and the time reverse flow analysis results are obtained;

[0110] Based on the particle interaction data of comprehensive light field information, the time reversal algorithm is used to simulate and reconstruct the dynamic process of particle interaction with light. By analyzing the motion trajectory of each particle and its interaction point with light in detail, the motion history of the particle can be reversed. By processing the data in segments, each segment independently calculates the state of the particle at a specific time and space. Through continuous time point analysis, a complete interaction timeline is gradually constructed. Each step of the calculation relies on the physical model's accurate description of particle motion and light path. In addition, the algorithm also considers the impact of environmental factors such as temperature and humidity on particle behavior. Finally, this complex calculation process integrates all data and simulation results, and outputs a particle dynamic interaction diagram, showing how particles interact with light at different times and locations, providing a detailed perspective for understanding particle dynamics.

[0111] See also Figure 4 , the steps to obtain the particle interaction positioning results are:

[0112] Using the time-reversal analysis results, the spatial coordinates and state data of the particles at different time points are extracted, each particle is analyzed point by point, the particle velocity vector and direction changes are analyzed, the particle flight path is reconstructed, and the paint particle path data is generated;

[0113] In the preparation stage, all sensors are precisely calibrated. First, the performance of each sensor is tested through standardized test procedures to ensure that stable output can be maintained under different environmental conditions (such as changing temperature and humidity). The process includes adjusting the sensitivity of the sensor to adapt to the slight changes in the data collected from particle reflection and scattering. After that, the collected raw data is pre-processed to filter out environmental noise and possible errors from the data and optimize the quality of the data. Through these steps, it is ensured that each sensor can accurately record the dynamic state of the particles in the experiment, laying a solid foundation for accurately tracking the flight path of the particles.

[0114] Integrate the paint particle path data with the spatial coordinates, measure the end point position of each paint particle, record the landing point of each paint particle, and obtain the paint particle landing point coordinate data;

[0115] After obtaining accurate particle path data, advanced spatial positioning technology is used to accurately measure the landing point of each particle. This technology combines laser ranging and high-speed camera technology to collect high-resolution spatial data by continuously monitoring the terminal position of each particle. Whenever a particle reaches the end point, the laser rangefinder records the exact position of the particle, while the high-speed camera captures the instantaneous image of the particle landing point. The data is automatically transmitted to the central data processing system, where the position data is analyzed and the landing coordinates of each particle are automatically identified and recorded. Through this integrated approach, a comprehensive and detailed particle landing point distribution map can be created, providing the necessary data support for in-depth analysis of the distribution of particles in space.

[0116] Analyze the paint particle landing point coordinate data, determine the distribution characteristics and interaction patterns of paint particles, conduct spatial positioning analysis of particle interaction, and generate particle interaction positioning results;

[0117] After collecting the particle landing data, the next step is to conduct in-depth analysis of the data to reveal the interactive behavior of the particles. This process involves statistical analysis of the coordinates of the particle landing points. By calculating the distance and distribution density between the particle landing points, the aggregation or dispersion trend of the particles in space can be obtained. In addition, it is also necessary to consider the time series data of the particles, compare the changes in the particle landing points at different time points, observe the changes in their dynamic distribution, and clearly display the analysis results through graphics and charts.

[0118] See also Figure 5 , the measurement steps of time delay are:

[0119] Install acoustic wave sensors at key points in the spraying area, confirm that each sensor fully covers the corresponding area, and generate a full coverage acoustic wave sensor array;

[0120] When selecting the key points of the acoustic wave sensor, a detailed acoustic wave propagation simulation is performed on the geometric model of the spraying area to identify which positions can achieve the maximum coverage efficiency of the acoustic wave. To this end, multiple simulation experiments are carried out using the acoustic wave propagation characteristics, including its diffusion angle and energy attenuation. Through these simulations, the reception effect and propagation coverage of the sensor at different positions are determined. Based on the simulation results, the sensor position that can maximize the acoustic wave coverage area while minimizing signal overlap and interference is selected. After installing the sensor at each selected location, preliminary tests are carried out to verify whether the coverage meets the expected design and ensure that each sensor can effectively monitor the area it is responsible for, thereby forming a continuous and blind-spot-free monitoring network.

[0121] Activate the full-coverage acoustic wave sensor array, synchronously emit acoustic waves and record the time and intensity of the acoustic wave signals reflected from the vehicle body surface, and generate a reflected acoustic wave signal record;

[0122] After the acoustic sensor array is activated, each sensor begins to emit sound waves according to a predetermined program and captures the sound wave signals reflected from the vehicle surface. In order to synchronize the operation of each sensor, a precise time synchronization device is used to ensure that all sensors emit sound waves at the same time and synchronously record the received sound wave signals. The received sound wave data is collected by a high-precision data acquisition system and transmitted to the central processing unit. During this process, the analysis software performs real-time analysis of the time and intensity of the received sound wave signals and calculates the time delay and energy attenuation of each signal. In this way, the characteristics of each sound wave signal can be recorded and analyzed in detail, providing accurate input data for subsequent data processing and distance calculation.

[0123] According to the reflected sound wave signal record, the formula is used:

[0124] ;

[0125] Calculate the propagation delay of sound waves , generate acoustic signal time delay data, where, represents the distance traveled by the sound wave in the medium, represents the speed of sound waves, Represents the baseline distance from the acoustic wave sensor to the reflecting surface;

[0126] Represents the distance that the sound wave travels in the medium, and its value is 10 meters. Represents the speed of sound waves in the medium, usually 340m / s, Represents the baseline distance from the acoustic wave sensor to the reflecting surface, assuming it is 5 meters, and is calculated as follows: First, calculate the ratio of the distance traveled by the acoustic wave in the medium to its speed:

[0127] ;

[0128] Next, calculate the rate of change of the relative distance:

[0129] ;

[0130] Then, take the square root of the rate of change:

[0131] ;

[0132] Finally, multiply the above two results to get:

[0133] ;

[0134] The results show that the time delay from transmitting the sound wave to receiving the reflected sound wave is seconds, which reflects the actual distance between the acoustic sensor and the vehicle surface.

[0135] See also Figure 6 , the steps to obtain the acoustic wave distance data are:

[0136] Collect the time delay data of the acoustic wave signal, extract the time it takes for the acoustic wave to travel from the emission point to the vehicle surface and then return to the sensor, synchronize the time of each data point, and generate a processed time delay data set;

[0137] In the process of collecting time delay data from the acoustic sensor array, a central monitoring system is first set up, which connects all sensors and receives data in real time. Through the central monitoring system, the working status and data transmission quality of each sensor can be viewed in real time to ensure that every data point collected is accurate. In order to verify the accuracy of the data, each data point is time synchronized, and the network time protocol (NTP) is used to ensure that the clocks of all devices are strictly synchronized. During the data collection process, the time of sound wave emission and reception recorded by each sensor is accurately marked and then transmitted to the data processing center. At the data processing center, these time marks are initially processed to screen out any possible abnormal data points, such as records with abnormally high or low time delays, to ensure the accuracy of subsequent calculations.

[0138] The processed time delay data set is combined with the acoustic wave velocity using the formula:

[0139] ;

[0140] Calculate the one-way distance of the sound wave from the spray head to the car body surface , generate one-way distance data, where is the speed of sound waves in air, For time delay;

[0141] Speed ​​of sound Under standard air conditions, the speed is about 340 m / s, while the time delay is obtained from the acoustic wave sensor through a real-time monitoring system, assuming a typical time delay value of seconds, calculated as follows: First, determine the speed of sound waves m / s; then, take Seconds; Calculation Meters represent the one-way distance of sound wave propagation. The results show that the distance from the spray head to the car body surface is rice.

[0142] Analyze the one-way distance data, verify and adjust the data, confirm that the distance between the spray head and the vehicle surface is kept within the optimal working range during the spraying process, and output the acoustic wave distance data;

[0143] After calculating the acoustic distance data, detailed data analysis and verification are necessary. First, the deviation range of the newly calculated data is checked by comparing it with standard test data of known distances. If the data deviation is found to be beyond the acceptable range, troubleshooting is immediately carried out. Possible causes include slight movement of the sensor position, interference in data transmission, or changes in environmental conditions. In addition, each measurement is verified in the field, using independent measurement tools such as laser rangefinders to directly measure the actual distance from the spray head to the vehicle surface. These field measurement results are compared with the data from the acoustic sensor system to verify the accuracy of the system. Through this series of inspections and adjustments, it is ensured that the output data of the system can accurately guide the operation of the spray machine, thereby ensuring the quality and uniformity of the coating.

[0144] See also Figure 7 , the steps to obtain the positioning accuracy verification record are:

[0145] Using the particle interaction positioning results and the acoustic wave distance data, the ideal position that the spray head should reach is determined through real-time monitoring feedback, and the ideal spray head position information is generated;

[0146] In the process of calculating the spray head position, the data from the particle interaction positioning system and the feedback from the acoustic distance sensor are first integrated. This process analyzes the position, velocity and interaction of each particle captured by the sensor in detail and transmits it to the processing unit in real time. The acoustic sensor provides the distance data between the spray head and the target surface. The distance data is obtained through precise time measurement technology. In each measurement cycle, the acoustic sensor transmits and receives the acoustic signal, calculates the round-trip time of the signal, and accurately determines the distance. The processing unit fuses these particle positioning data and acoustic distance data, and uses data fusion technology to comprehensively analyze this information, so as to evaluate in real time the ideal position of the spray head in the current environment. During the data processing process, each data point is tested for its validity to ensure data quality and filter out possible noise or outliers, thereby ensuring the accuracy and reliability of subsequent calculations. Through this coherent and detailed data processing and analysis, an accurate spray head positioning information is generated, which serves as the basis for adjusting the spray head position and ensures the accuracy and efficiency of the spraying process.

[0147] According to the ideal spray head position information, the spray head position is adjusted and matched in real time, using the formula:

[0148] ;

[0149] Calculate the position difference that needs to be adjusted , get the spray position adjustment result, where Represents the ideal spray head position, Represents the current spray head position;

[0150] represents the ideal position, assuming it is 200 units, Indicates the current position, measured by real-time monitoring, assumed to be 195 units. Substitute the value into the formula for calculation:

[0151] ;

[0152] The results show that the spray head needs to move forward 5 units to reach the ideal position. This value will be used to adjust the mechanical control system to ensure the correct position adjustment of the spray head.

[0153] Monitor the deviation between the spray position adjustment result and the ideal position, using the formula:

[0154] ;

[0155] Calculate the percentage of position deviation , generate positioning accuracy verification records;

[0156] is the position deviation of the spray head, the above calculation result is 5 units; is the ideal position, which is 200 units. Substitute it into the formula for calculation:

[0157] ;

[0158] The results showed that the positioning accuracy of the spraying process was 97.5%, indicating that the spray head was very close to the ideal position and demonstrating the effectiveness of the adjustment measures.

[0159] The intelligent positioning method applied to the spraying robot includes the following steps:

[0160] S1: Deploy cameras around the vehicle body spraying area to continuously monitor the light direction and intensity, analyze the light changes under different reflection angles, calculate the total intensity of the light field, and generate the vehicle body light field information;

[0161] S2: Arrange sensors around the car body to capture the reflection and scattering data of paint particles, refine the light field environment of each data point, calculate the average interaction intensity, simulate the interaction process between particles and light, and obtain the time reverse flow analysis results;

[0162] S3: Using the time backflow analysis results, analyze the particle velocity vector and direction changes, reconstruct the particle flight path, measure and record the end position of each paint particle, perform spatial positioning analysis of particle interaction, and generate particle interaction positioning results;

[0163] S4: Installing acoustic wave sensors at key points in the spraying area, synchronously emitting acoustic waves and recording the time and intensity of acoustic wave signals reflected from the vehicle body surface, calculating the acoustic wave propagation delay, and generating acoustic wave signal time delay data;

[0164] S5: Collect the time delay data of the acoustic wave signal, synchronize the time of each data point, combine it with the acoustic wave speed, calculate the one-way distance of the acoustic wave from the spray head to the vehicle body surface, verify and adjust the data, and output the acoustic wave distance data;

[0165] S6: Use the particle interaction positioning results and the acoustic wave distance data to determine the ideal position that the spray head should reach, adjust the spray head position in real time and match it, calculate the deviation between the adjustment result and the ideal position, and generate a positioning accuracy verification record.

[0166] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. Intelligent positioning system for spraying robots, characterized by: The positioning system comprises: The light field data acquisition module uses a camera to surround the spraying area, continuously capture the direction and intensity changes of light, record the light information reflected at different angles, and generate the light field information of the vehicle body; The particle tracking calculation module captures the reflection and scattering data of paint particles through sensors, combines the vehicle body light field information, analyzes the time reverse flow of the interaction between light and particles, tracks the flight path of each particle according to the time reverse flow analysis results, and records the landing point to obtain the particle interaction positioning result; The acoustic wave precision distance measurement module configures an acoustic wave sensor array in the spraying area, collects reflected acoustic wave signals, measures the time delay of reflected acoustic wave signals, calculates the distance between the spray head and the vehicle surface based on the time delay measurement results combined with the acoustic wave velocity, and outputs the acoustic wave distance data; The dynamic verification execution module adjusts the position of the spray head according to the particle interaction positioning result and the acoustic wave distance data, monitors the position change during the real-time spraying process, confirms that each spraying is accurately aligned with the target position, and generates a positioning accuracy verification record; The steps for acquiring the vehicle body light field information are as follows: Deploy cameras around the vehicle body spraying area to continuously monitor the direction and intensity of light, record the direction and intensity of light in real time, and generate light direction and intensity data; Analyze the light changes under different reflection angles according to the light direction and intensity data to obtain angle reflection light change data; Based on the angle reflected light change data, the formula is used: Calculate the total intensity of the light field , generate vehicle light field information; where, represents the incident light intensity, represents the reflectivity, and are the angles of incidence and reflection, respectively; The calculation steps of the time reversal are: Arrange sensors around the vehicle body, and capture the reflection and scattering of paint particles by adjusting the sensitivity and position of the sensors to obtain preliminary reflection and scattering data; The preliminary reflection and scattering data are combined with the vehicle body light field information to refine the light field environment of each data point using the formula: Calculate the average interaction strength , generating particle interaction data with comprehensive light field information; where, Representative The strength of the data points, Indicates The light field intensity value corresponding to the data point is is the total number of data points; Based on the particle interaction data of the comprehensive light field information, the interaction process between particles and light is simulated, the interaction time and environment are calculated, and the time reverse flow analysis result is obtained; The steps for obtaining the particle interaction positioning result are: Utilizing the time reverse flow analysis results, extracting the spatial coordinates and state data of the particles at different time points, performing point-by-point analysis on each particle, analyzing the particle velocity vector and direction changes, reconstructing the particle flight path, and generating paint particle path data; Integrate the paint particle path data with the spatial coordinates, measure the end point position of each paint particle, record the landing point of each paint particle, and obtain the paint particle landing point coordinate data; Analyze the paint particle landing point coordinate data, determine the distribution characteristics and interaction mode of the paint particles, perform spatial positioning analysis of particle interaction, and generate particle interaction positioning results; The steps of measuring the time delay are: Install acoustic wave sensors at key points in the spraying area, confirm that each sensor fully covers the corresponding area, and generate a full coverage acoustic wave sensor array; activating the full-coverage acoustic wave sensor array, synchronously emitting acoustic waves and recording the time and intensity of the acoustic wave signals reflected from the surface of the vehicle body, and generating a reflected acoustic wave signal record; According to the reflected sound wave signal record, the formula is used: Calculate the propagation delay of sound waves , generate acoustic signal time delay data, where, represents the distance traveled by the sound wave in the medium, represents the speed of sound waves, Represents the baseline distance from the acoustic wave sensor to the reflecting surface.

2. The intelligent positioning system for a spraying robot according to claim 1, characterized in that: The steps for obtaining the acoustic wave distance data are as follows: Collect the time delay data of the acoustic wave signal, extract the time for the acoustic wave to travel from the emission point to the vehicle body surface and then return to the sensor, perform time synchronization on each data point, and generate a processed time delay data set; The processed time delay data set is combined with the acoustic wave velocity using the formula: Calculate the one-way distance of the sound wave from the spray head to the car body surface , generate one-way distance data, where is the speed of sound waves in air, For time delay; The one-way distance data is analyzed, the data is verified and adjusted, it is confirmed that the distance between the spray head and the vehicle body surface is maintained within the optimal working range during the spraying process, and the acoustic wave distance data is output.

3. The intelligent positioning system for a spraying robot according to claim 2, characterized in that: The steps for obtaining the positioning accuracy verification record are: Using the particle interactive positioning result and the acoustic wave distance data, the ideal position that the spray head should reach is determined through real-time monitoring feedback, and ideal spray head position information is generated; According to the ideal spray head position information, the spray head position is adjusted and matched in real time, using the formula: Calculate the position difference that needs to be adjusted , get the spray position adjustment result, where Represents the ideal spray head position, Represents the current spray head position; Monitor the deviation between the spray position adjustment result and the ideal position, using the formula: Calculate the percentage of position deviation , generate positioning accuracy verification records.

4. An intelligent positioning method applied to a spraying robot, characterized in that: The intelligent positioning system for a spraying robot according to any one of claims 1 to 3 comprises the following steps: Deploy cameras around the car body spraying area to continuously monitor the light direction and intensity, analyze the light changes under different reflection angles, calculate the total intensity of the light field, and generate the car body light field information; Arrange sensors around the vehicle body to capture the reflection and scattering data of paint particles, combine them with the light field information of the vehicle body, refine the light field environment of each data point, calculate the average interaction intensity, simulate the interaction process between particles and light, and obtain the time reverse flow analysis result; Utilizing the time backflow analysis results, analyzing the particle velocity vector and direction changes, reconstructing the particle flight path, measuring and recording the terminal position of each paint particle, performing spatial positioning analysis of particle interaction, and generating particle interaction positioning results; Install acoustic wave sensors at key points in the spraying area, synchronously emit acoustic waves and record the time and intensity of acoustic wave signals reflected from the vehicle surface, calculate the acoustic wave propagation delay, and generate acoustic wave signal time delay data; Collect the time delay data of the acoustic wave signal, synchronize the time of each data point, combine it with the acoustic wave velocity, calculate the one-way distance of the acoustic wave from the spray head to the vehicle body surface, verify and adjust the data, and output the acoustic wave distance data; The particle interaction positioning result and the acoustic wave distance data are used to determine the ideal position that the spray head should reach, the spray head position is adjusted and matched in real time, the deviation between the adjustment result and the ideal position is calculated, and a positioning accuracy verification record is generated.

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