Deviation measurement method for AGV cooperative motion and storage medium

Abstract

The invention discloses a deviation measurement method for AGV cooperative motion, and the method comprises the following steps: transmitting a laser beam through a single-line laser radar disposed at the center line of the head of a rear vehicle, enabling the laser beam to irradiate a reflective film which is pasted at the tail of a front vehicle and is as wide as a vehicle body, then carrying out the reflection and returning, collecting the coordinate information of boundary points of the reflective film, and obtaining the coordinate information of the boundary points of the reflective film; the relative distance and angle between the two vehicles are calculated based on conversion of the polar coordinate system and the rectangular coordinate system; the horizontal deviation in laser radar measurement is dynamically corrected according to the vehicle motion state data; reflecting film signal reflection and error calculation: calculating the relative position deviation and attitude deviation between the two vehicles in real time by analyzing the intensity and time difference of reflected signals; detecting and correcting formation keeping errors, and when the deviation exceeds a preset threshold value, adjusting motion parameters of the rear vehicle so as to keep the formation stable; motion parameters of all the vehicles are adjusted in real time through multi-vehicle cooperative control, and error correction response is optimized based on a dynamic trajectory prediction module.

Description

Technical Field

[0001] The present invention relates to the field of AGVs, and in particular to a deviation measurement method for coordinated motion of AGVs. Background Art

[0002] With the continuous advancement of industrial automation, AGVs (Automated Guided Vehicles) are playing an increasingly important role in logistics, production line handling, and large-scale equipment transportation. In the in-factory transportation of large equipment such as spacecraft, rockets, missiles, rail vehicles, and wind turbine blades, collaborative AGV operation is key to improving efficiency and reducing costs. However, traditional AGV collaborative motion methods often rely on tooling brackets or measuring devices, which pose challenges such as high system complexity and limited control.

[0003] Given these requirements, AGVs must maintain precise relative positions and postures to ensure safe and smooth equipment transportation. Traditional collaborative handling methods primarily rely on the following: Hard-connected tooling brackets and AGVs: Multiple AGVs are hard-connected to a single tooling bracket to jointly transport large equipment. This method ensures the relative positional relationship between AGVs, but it also presents the following issues: Reliance on bracket accuracy: Structural errors or inaccurate positioning of the bracket itself will affect the relative positioning accuracy between AGVs. Poor system flexibility: Transporting equipment of varying shapes or sizes often requires bracket redesign or adjustment, increasing system complexity and reducing flexibility. Inability to effectively address dynamic deviations: During operation, AGVs may be affected by external factors (such as uneven road surfaces), resulting in dynamic deviations. Traditional methods struggle to correct these deviations in real time, impacting overall system accuracy. Monitoring with relative position measurement devices: Another common collaborative method involves installing relative position measurement devices (such as optical sensors or laser displacement sensors) between the AGV and bracket to monitor deviations between the AGV and bracket in real time. However, this approach also has some limitations: Limitations: These measurement devices typically only monitor the relative position between each AGV and the bracket, and cannot accurately measure the position changes between AGVs, making it difficult to provide global precision control. Error propagation: Because the deviation of each AGV can only be indirectly inferred from another AGV, errors can gradually accumulate, affecting the overall coordination accuracy. Insufficient real-time performance: In complex environments, the system's real-time response to large deviations between AGVs is slow, making it difficult to achieve precise correction control. Summary of the Invention

[0004] To achieve the above and other related purposes, the present invention discloses a deviation measurement method for AGV coordinated motion, comprising the following steps: Step S1: LiDAR measurement data acquisition: A single-line LiDAR installed on the centerline of the rear vehicle emits a laser beam. The laser beam hits a reflective sheeting with the same width as the vehicle body and is reflected back. The coordinate information of the boundary points of the reflective sheeting is collected, and the relative distance and angle between the two vehicles are calculated based on the conversion between the polar coordinate system and the rectangular coordinate system. Step S2: Horizontal distortion correction, dynamically correcting the horizontal deviation in the lidar measurement based on the vehicle motion state data; Step S3: Reflection and error calculation of reflective film signals. By analyzing the intensity and time difference of the reflected signals, the relative position deviation and posture deviation between the two vehicles are calculated in real time. Step S4: Formation keeping error detection and correction. When the deviation exceeds a preset threshold, the motion parameters of the following vehicle are adjusted to keep the formation stable. Step S5: Dynamic collaborative correction and feedback: adjust the motion parameters of each vehicle in real time through multi-vehicle collaborative control, and optimize the error correction response based on the dynamic trajectory prediction module.

[0005] Furthermore, the step S1 specifically includes: Step S11: obtaining the coordinates of the boundary points of the reflective film in the polar coordinate system, converting them into rectangular coordinates, calculating the length of the line segment, and comparing and verifying the length with the actual length of the reflective film; Step S12: calibrating the reference position of the reflective film in the AGV alignment state; Step S13: determining the relative position deviation of the center points of the two vehicles by calculating the longitudinal and lateral deviations of the coordinates of the midpoints of the line segments; Step S14: Calculate the attitude angle deviation of the two vehicles through the line segment angle difference.

[0006] Furthermore, in step S2, the vehicle motion state data is obtained using a gyroscope and an accelerometer, and dynamic horizontal distortion correction is performed in combination with the real-time measurement data of the laser radar.

[0007] Furthermore, the step S4 further includes: The relative position deviation of the two vehicle center points is corrected based on the mechanical size parameters, which include the vehicle length and the laser radar installation position.

[0008] Furthermore, in step S5, the dynamic trajectory prediction module predicts the motion trend of the leading vehicle through historical trajectory data and current deviation data, and adjusts the motion parameters of the following vehicle in advance.

[0009] Furthermore, a plurality of calibration points are provided on the reflective film, and the positions of the calibration points are precisely designed to improve positioning accuracy.

[0010] Furthermore, it also includes environmental interference detection and correction steps: monitoring signal quality through the interference detection module, and switching to fault-tolerant mode when the interference exceeds the threshold, and performing error compensation in combination with the preceding vehicle trajectory data.

[0011] Furthermore, the measurement accuracy of the laser radar is at the millimeter level, and the scanning range covers the entire area required for the coordinated movement of the two vehicles.

[0012] In another aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the above method when executed by a processor.

[0013] By adopting the above technical solution, by directly measuring the relative posture between AGVs, the dependence on tooling brackets and multiple measuring devices in traditional methods is avoided. The data measured by the laser radar can provide information such as the distance, angle, relative displacement, etc. between the two AGVs. These data are fed back to the control system in real time, and the control system can perform precise trajectory adjustment and collaborative control based on this information. Compared with traditional methods, the AGV collaborative motion deviation measurement method of the present invention greatly simplifies the system structure and avoids the need for complex tooling brackets and local measuring equipment. It is only necessary to obtain accurate relative position data through laser radar scanning and perform motion correction through control algorithms. This not only improves the accuracy of the system, but also greatly reduces the complexity and maintenance cost of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. The accompanying drawings are provided for a better understanding of the present disclosure and do not constitute a limitation of the present disclosure. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, among which: Figure 1 is a flow chart of the present invention; Figure 2 Schematic diagram of the deviation measurement of adjacent AGVs; Figure 3 Schematic diagram of the polar coordinate system and rectangular coordinate system of the radar measuring the rear vehicle. DETAILED DESCRIPTION

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0016] Reference Figure 1The embodiment of the present invention provides a deviation measurement method for AGV coordinated motion, which is characterized by comprising the following steps: Step S1: LiDAR measurement data acquisition: A single-line LiDAR installed on the centerline of the rear vehicle emits a laser beam. The laser beam hits a reflective sheeting with the same width as the vehicle body and is reflected back. The coordinate information of the boundary points of the reflective sheeting is collected, and the relative distance and angle between the two vehicles are calculated based on the conversion between the polar coordinate system and the rectangular coordinate system. Specifically include: Step S11: obtaining the coordinates of the boundary points of the reflective film in the polar coordinate system, converting them into rectangular coordinates, calculating the length of the line segment, and comparing and verifying the length with the actual length of the reflective film; Step S12: calibrating the reference position of the reflective film in the AGV alignment state.

[0017] There are multiple calibration points on the reflective film, and the positions of the calibration points are precisely designed to improve positioning accuracy.

[0018] Step S13: determining the relative position deviation of the center points of the two vehicles by calculating the longitudinal and lateral deviations of the coordinates of the midpoints of the line segments; Step S14: Calculate the attitude angle deviation of the two vehicles through the line segment angle difference.

[0019] Step S2: Horizontal distortion correction, dynamically correcting the horizontal deviation in the lidar measurement based on the vehicle motion state data.

[0020] Among them, the gyroscope and accelerometer are used to obtain the vehicle motion state data, and the dynamic horizontal distortion correction is performed in combination with the real-time measurement data of the lidar.

[0021] Step S3: Reflection and error calculation of reflective film signals. By analyzing the intensity and time difference of the reflected signals, the relative position deviation and posture deviation between the two vehicles are calculated in real time. Step S4: Formation keeping error detection and correction. When the deviation exceeds a preset threshold, the motion parameters of the following vehicle are adjusted to keep the formation stable. The relative posture deviation at the center of the two vehicle models is corrected according to the mechanical size parameters, which include the vehicle body length and the laser radar installation position.

[0022] Step S5: Dynamic collaborative correction and feedback: adjust the motion parameters of each vehicle in real time through multi-vehicle collaborative control, and optimize the error correction response based on the dynamic trajectory prediction module.

[0023] The dynamic trajectory prediction module predicts the motion trend of the leading vehicle through historical trajectory data and current deviation data, and adjusts the motion parameters of the following vehicle in advance.

[0024] It also includes environmental interference detection and correction steps: monitoring signal quality through the interference detection module, switching to fault-tolerant mode when the interference exceeds the threshold, and performing error compensation based on the preceding vehicle trajectory data.

[0025] The specific implementation of this embodiment is as follows: Step S1: LiDAR measurement data acquisition: LiDAR Transmission and Reception: A single-line LiDAR mounted on one vehicle emits a laser beam, which strikes another vehicle equipped with reflective film and returns to the LiDAR's receiver. Measuring Distance and Angle: The LiDAR accurately measures the laser beam's travel distance by calculating the time difference between its transmission and return. Combined with the LiDAR's angular data (achieved through rotational scanning), the relative distance and angle between the reflective film and the LiDAR can be determined.

[0026] The specific implementation method of this step is as follows: A continuous laser reflective film is pasted on the rear of the front vehicle, and a lidar sensor is installed at the corresponding position on the front of the rear vehicle. At the same time, a computer for processing lidar feedback data is installed on the rear vehicle, and the computer includes a method for processing lidar feedback data.

[0027] Among them, the reflective film pasted on the rear of the front vehicle should be the same width as the vehicle body.

[0028] Among them, the laser radar sensor installed on the front of the rear vehicle should be located on the center line of the vehicle body, and when the two vehicles are aligned, the laser radar is located in the center of the laser reflective film.

[0029] The following vehicle uses a computer to process the laser radar feedback data in the following way: Step S11: Obtain the boundary point coordinate information of the reflective film in the polar coordinate system through the reflection intensity data fed back by the laser radar, and set it as , , converted to rectangular coordinates , And calculate the length of line segment AB; compare the calculated result with the known actual length of the laser reflective film. When the deviation between the two is less than the preset threshold, the measurement result is considered correct.

[0030] Step S12: Figure 2 As shown in the figure, when the rear vehicle is at the theoretical target position, the two AGVs are considered to be in alignment. At this time, the position and posture deviation values are both 0. The line segment obtained by measuring the front vehicle's reflective film in the rear vehicle's laser radar is marked as A'B', and the coordinates of its center point are marked as like Figure 3 shown.

[0031] Step S13: Calculate the coordinates of the midpoint C of line segment AB, set as , then the difference between C and C' is the longitudinal deviation and lateral deviation of the center point of the reflective film relative to the center point of the laser radar measurement.

[0032] Step S14: Calculate the angle of line segment AB relative to A'B' to obtain the deflection angle of the laser reflective film.

[0033] Step S15: Combining the vehicle length parameter in the AGV mechanical dimensions and the actual installation position of the laser radar on the vehicle head, the relative posture deviation of the two vehicle center points can be calculated.

[0034] Step S2: Horizontal distortion correction: Sources of distortion: In practical applications, LiDAR may be affected by factors such as vehicle motion, radar offset, or vibration, resulting in horizontal distortion in the measured data (e.g., lateral errors caused by vehicle movement). Correcting for distortion: The vehicle's motion state (e.g., speed and direction) is determined based on LiDAR sensor data (e.g., gyroscope and accelerometer). Dynamic adjustments are made to correct for horizontal distortion in LiDAR measurements, ensuring more accurate LiDAR data.

[0035] Step S3: Reflective film signal reflection and error calculation: The function of reflective film: After receiving the LiDAR signal, the vehicle equipped with reflective film reflects it back and returns it to the LiDAR. These reflected signals carry information about the relative position (including position and angle) between the two vehicles. Error estimation: By analyzing the reflected signal of the reflective film (such as reflection time, signal strength, etc.), the relative position and attitude between the two vehicles are calculated. When there is a deviation between the vehicles (for example, changes in position or angle), these errors will be captured through the interaction between the LiDAR and the reflective film. Error detection: Based on the distance and angle information collected by the LiDAR, the error is calculated in real time and tracked. For example, if there is a large deviation between the LiDAR measurement value and the expected value, it means that there may be an error in the vehicle's position and attitude.

[0036] Step S4: Formation keeping error detection and correction: Formation maintenance goal: In multi-vehicle collaborative operations, all vehicles need to maintain a stable formation. To ensure the accuracy of the formation, the relative position error between each vehicle and the others needs to be detected. Error correction mechanism: When the error exceeds the set tolerance range, the system will automatically correct it. Based on the error data between the reflective film and the lidar, the vehicle's motion parameters such as speed, acceleration, and steering angle are adjusted in real time. Specifically: If a vehicle deviates from the formation, the system will issue a control command based on the error size to adjust the vehicle's position; other vehicles will make synchronous adjustments based on this correction information to maintain the stability of the overall formation.

[0037] Step S5: Dynamic collaborative correction and feedback: Multi-vehicle collaborative control: In multi-vehicle collaborative operations, not only does each vehicle need to independently correct errors, but the system also coordinates their movements. Each vehicle continuously receives data feedback from lidar and reflective film, adjusting its position in real time to ensure the formation is accurately maintained. Feedback mechanism: By continuously monitoring the relative errors between vehicles, the system can dynamically adjust the vehicle's path and speed. For example, if a vehicle has a large deviation, the system will automatically calculate and feedback the error information, adjusting the vehicle's movement. Other vehicles will then adjust their speed, direction, and other parameters based on this real-time data to ensure formation consistency.

[0038] Reflective Film Feature Point Calibration: Multiple calibration points (such as laser reflection points or markers of varying brightness) are added to the laser reflective film of the preceding vehicle. These points are precisely positioned. The following vehicle's LiDAR can measure the relative positions of these calibration points to further determine the position of the preceding vehicle's reflective film within the coordinate system. Advantage: Measuring multiple feature points effectively reduces errors caused by single-point measurement and improves overall positioning accuracy.

[0039] Environmental Interference Detection and Correction: Interference Detection: During LiDAR measurements, the system may be affected by external factors (such as light interference and obstructions). By adding an interference detection module, signal quality can be monitored in real time. Interference Correction: If interference is detected, the system switches to a preset fault-tolerant mode, combining the preceding vehicle's trajectory data to compensate for errors and ensure measurement stability. Advantages: Enhanced system robustness ensures accurate measurements even in complex environments.

[0040] Calculate the deviation: Position deviation: By calculating the relative position deviation between line segment A'B' and line segment AB in the rectangular coordinate system, the horizontal and vertical distance differences between the two vehicles can be obtained.

[0041] Attitude angle deviation: In addition, the attitude deviation between the two vehicles can be obtained by calculating the relative attitude angle of A'B' and AB (that is, the angle difference between the two segments). These two error terms (position deviation and attitude deviation) together determine the relative error of the AGV.

[0042] Dynamic trajectory prediction: A dynamic trajectory prediction module is added to the following vehicle's computer system. This module uses real-time measurement data and the preceding vehicle's historical trajectory data to predict the preceding vehicle's future motion trends. Combining current deviation data with the preceding vehicle's motion trends, it proactively adjusts the following vehicle's motion parameters (such as speed, acceleration, and direction). Advantages: Improves system response speed and coordination accuracy, while reducing error correction lag.

[0043] Error feedback and adjustment: The calculated deviation data will be transmitted to the control system of the following vehicle through the computer, and the motion state of the following vehicle will be adjusted in time through the feedback mechanism (such as adjusting speed, steering, etc.) to ensure that the following vehicle can maintain the predetermined relative position and posture with the leading vehicle, thereby achieving high-precision AGV coordinated movement.

[0044] Combined with AGV mechanical dimension correction: Using known AGV mechanical dimensions (such as body length and width), the calculated deviation can be further corrected to determine the deviation between the centroids of two adjacent AGVs. The centroid is typically the geometric center of the AGV, a location that is crucial for precise coordinated motion and trajectory control.

[0045] Those skilled in the art will understand that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by those skilled in the art in the art to which the present invention pertains. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with those in the context of the prior art and, unless specifically defined, will not be interpreted in an idealized or overly formal sense.

[0046] For simplicity of description, the method embodiments are described as a series of actions. However, those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because certain steps can be performed in other orders or simultaneously according to the embodiments of the present invention. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0047] Through the description of the above embodiments, it can be seen that those skilled in the art can clearly understand that the present application can be implemented by means of software plus the necessary general hardware platform. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present application or certain parts of the embodiments.

[0048] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A deviation measurement method for AGV coordinated motion, characterized in that: The following steps are involved: Step S1: LiDAR measurement data acquisition: A single-line LiDAR installed on the centerline of the rear vehicle emits a laser beam. The laser beam hits a reflective sheeting with the same width as the vehicle body and is reflected back. The coordinate information of the boundary points of the reflective sheeting is collected, and the relative distance and angle between the two vehicles are calculated based on the conversion between the polar coordinate system and the rectangular coordinate system. Step S2: Horizontal distortion correction, dynamically correcting the horizontal deviation in the lidar measurement based on the vehicle motion state data; Step S3: Reflection and error calculation of reflective film signals. By analyzing the intensity and time difference of the reflected signals, the relative position deviation and posture deviation between the two vehicles are calculated in real time. Step S4: Formation keeping error detection and correction. When the deviation exceeds a preset threshold, the motion parameters of the following vehicle are adjusted to keep the formation stable. Step S5: Dynamic collaborative correction and feedback: adjust the motion parameters of each vehicle in real time through multi-vehicle collaborative control, and optimize the error correction response based on the dynamic trajectory prediction module.

2. The deviation measurement method according to claim 1, characterized in that: The step S1 specifically includes: Step S11: obtaining the coordinates of the boundary points of the reflective film in the polar coordinate system, converting them into rectangular coordinates, calculating the length of the line segment, and comparing and verifying the length with the actual length of the reflective film; Step S12: calibrating the reference position of the reflective film in the AGV alignment state; Step S13: determining the relative position deviation of the center points of the two vehicles by calculating the longitudinal and lateral deviations of the coordinates of the midpoints of the line segments; Step S14: Calculate the attitude angle deviation of the two vehicles through the line segment angle difference.

3. The deviation measurement method according to claim 1, characterized in that: In step S2, the vehicle motion state data is acquired using a gyroscope and an accelerometer, and dynamic horizontal distortion correction is performed in combination with the real-time measurement data of the laser radar.

4. The deviation measurement method according to claim 1, characterized in that: The step S4 further includes: The relative position deviation of the two vehicle center points is corrected based on the mechanical size parameters, which include the vehicle length and the laser radar installation position.

5. The deviation measurement method according to claim 1, characterized in that: In step S5, the dynamic trajectory prediction module predicts the motion trend of the leading vehicle through historical trajectory data and current deviation data, and adjusts the motion parameters of the following vehicle in advance.

6. The deviation measurement method according to claim 1, characterized in that: A plurality of calibration points are provided on the reflective film, and the positions of the calibration points are precisely designed to improve positioning accuracy.

7. The deviation measurement method according to claim 1, characterized in that: It also includes environmental interference detection and correction steps: monitoring signal quality through the interference detection module, switching to fault-tolerant mode when the interference exceeds the threshold, and performing error compensation based on the preceding vehicle trajectory data.

8. The deviation measurement method according to claim 1, characterized in that: The measurement accuracy of the laser radar is at the millimeter level, and the scanning range covers the entire area required for the coordinated movement of the two vehicles.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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