Man-machine cloud collaborative road marking method and system

Abstract

The invention discloses a man-machine cloud collaborative road marking method and system, and belongs to the technical field of robot construction. Sampling interval parameters are set, and three coordinate points of different curve radiuses of a road are determined; determining a quadratic curve equation as a regular equation according to the three coordinate points; according to the rule equation, coordinates of first three initial route points are collected; forming a circle according to the coordinates of the previous three historical nearest route points, substituting the radius of the circle as the curve radius of the next route point into the rule equation, calculating the distance from the next route point to the current route point, and so on until the distance from the last route point to the previous route point is calculated; according to the distance from the next route point to the current route point, determining an annular area range of the next route point by setting annular area range parameters; acquiring coordinates of the route points by judging whether the positioning device moves to the annular area range of the next route point or not, acquiring coordinate data of the route points until the last route point when the positioning device moves to the annular area range, acquiring coordinate data of all the route points, and generating a reference path for marking the road marking; and according to the reference path marked by the road marking, tracking and driving along the reference path, and marking the road marking on the road. Through the method, the reference path can be accurately generated, the accuracy of road marking is improved, and the labor intensity of constructors is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of robot construction, and more particularly to a method and system for automatically painting road markings based on human-machine-cloud collaboration. Background Art

[0002] Road traffic markings, such as lane lines and lane boundary lines, are mainly painted on the road surface to indicate lane boundaries and road boundaries. In China, the annual newly built highway mileage reaches 30,000 kilometers, and correspondingly, these traffic markings also need to be painted. At the same time, the total mileage of expressways in China is as high as 300,000 kilometers. Subject to sun exposure, rain, snow, ice, and the impact and abrasion of vehicles, these markings need to be repainted regularly.

[0003] Currently, road marking painting is mainly manual work, which not only has the problem of painting errors, but also brings heavy workload and low work efficiency. An automatic marking robot can paint markings with high precision and high efficiency. By importing a target route as a reference path and starting the automatic marking robot, the robot automatically drives along the reference path and paints the markings.

[0004] Currently, Chinese Patent No. CN112779845A discloses an automatic pre-painting device and working method for road markings. Although this method discloses that before the robot walks and paints, it needs to receive or import a reference path, and then start the robot to drive along the reference path while spraying and painting, it requires construction workers to hold a positioning device and walk to each route point for coordinate collection, and then perform fitting or interpolation processing to generate a reference path.

[0005] That is, the above method still has the problems of large manual sampling workload, and construction workers cannot determine where it is most reasonable to collect route points, and there are problems with the rationality of sample point selection, resulting in human errors in the generation of the reference path and large errors when the robot paints the markings. Summary of the Invention

[0006] In view of the problems existing in the above field, the present invention proposes a method and system for painting road markings with human-machine-cloud collaboration, which can solve the technical problems that the rationality of sample point selection is problematic, resulting in human errors in the generation of the reference path and large errors when the robot paints the markings.

[0007] To solve the above technical problems, the present invention discloses a method for painting road markings with human-machine-cloud collaboration, including the following steps:

[0008] Set the sampling interval parameter, and determine three coordinate points with different curve radii on the road according to it; according to the three coordinate points, determine the quadratic curve equation as the regular equation; according to the regular equation, collect the coordinates of the first three initial route points;

[0009] Construct a circle based on the coordinates of the three most recent historical waypoints, and use the radius of the circle as the turning radius at the next waypoint; substitute the turning radius at the next waypoint into the rule equation to calculate the distance from the next waypoint to the current waypoint, and so on until the distance from the last waypoint to the previous waypoint is calculated;

[0010] Based on the distance from the next waypoint to the current waypoint, determine the annular area range of the next waypoint by setting the annular area range parameter; collect the waypoint coordinate by judging whether the positioning device moves into the annular area range of the next waypoint. When the positioning device moves into the annular area range of the next waypoint, collect the coordinate data of this waypoint until the last waypoint to obtain all the waypoint coordinate data;

[0011] Generate a reference path for road marking application based on all the waypoint coordinate data; drive along the reference path according to the reference path for road marking application to apply road markings to the road.

[0012] Preferably, the defining rule equation includes the following steps:

[0013] Set the sampling interval parameters d1, d2, and d3; where d1 represents the preset sampling interval for a road with a turning radius of 50 meters, d2 represents the preset sampling interval for a road with a turning radius of 200 meters, and d3 represents the preset sampling interval for a road with a turning radius greater than or equal to 500 meters;

[0014] According to the sampling interval parameters, solve the quadratic curve equation passing through the coordinate points (50, d1), (250, d2), and (500, d3) by the analytical method:

[0015] S = f(r) = ar 2 + br + c

[0016] where r is the turning radius, and a, b, and c are the coefficients of the curve equation respectively;

[0017] Define the rule equation as:

[0018]

[0019] And when S < 1, take S = 1.

[0020] Preferably, the collecting of the coordinates of the first three waypoints includes the following steps:

[0021] Determine the reference object according to the roadside curb / central isolation belt / original lane lines of the road;

[0022] Place the positioning device at the reference object at the starting point of the road section to be marked, read and collect the coordinates (x1, y1) of the first route point, and use it as the first route point.

[0023] Estimate the road curve radius r1 at the position of the first route point (x1, y1), calculate S1 according to the rule equation, continue to drive forward a distance of S1 by controlling the positioning device, place the positioning device at the reference object and obtain the coordinates at the reference object, and use this coordinate as the coordinates of the second route point (x2, y2).

[0024] Estimate the road curve radius r2 at the position of the second route point (x2, y2), calculate S2 according to the rule equation, continue to drive forward a distance of S2 by controlling the positioning device, place the positioning device at the reference object and obtain the coordinates at the reference object, and use this coordinate as the coordinates of the third route point (x3, y3).

[0025] Preferably, the solution process of the curve radius at the next route point includes the following steps:

[0026] For the i-th route point, i = 4, 5, 6, 7, …, N, obtain the three closest historical previous route points (x i-3 , y i-3 ), (x i-2 , y i-2 ), (x i-1 , y i-1 ), where N represents the last route point.

[0027] According to the three closest historical previous route points (x i-3 , y i-3 ), (x i-2 , y i-2 ), (x i-1 , y i-1 ), solve for the radius r i-1 of the circle formed by these three coordinate points, and use it as the curve radius at the i-th route point. The solution formula is:

[0028]

[0029] where p i-1 = (d i-3,i-2 + d i-3,i-1 + d i-2,i-1 ) / 2, d i-3,i-2 represents the straight-line distance between the (i - 3)-th route point and the (i - 2)-th route point, d i-3,i-1 represents the straight-line distance between the (i - 3)-th route point and the (i - 1)-th route point, and d i-2,i-1 represents the straight-line distance between the (i - 2)-th route point and the (i - 1)-th route point.

[0030] Preferably, the method for determining the range of the circular area of the next route point includes the following steps:

[0031] Substitute the calculated curve radius r of the position of the next route point i-1 into the rule equation to obtain the distance from the next route point to the current route point as:

[0032]

[0033] And when S i-1 < 1, take S i-1 = 1;

[0034] With the (i - 1)-th route point as the center, respectively use S i-1 - D as the inner circle radius and S i-1 + D as the outer circle radius to determine the range of the circular area of the next route point, where D represents the parameter of the circular area range.

[0035] Preferably, the method for obtaining all the route point coordinate data includes the following steps:

[0036] Control the positioning device to continue moving forward along the reference object, and obtain the positioning data in real time through the positioning device;

[0037] According to the positioning data obtained in real time, by judging whether the positioning coordinates are within the circular area, if not, control the positioning device to continue moving forward along the reference object; if within the circular area, through the emitted sound, light, and vibration reminders, immediately control the positioning device to stop moving and place it at the reference object at the parking point, and collect the route point coordinates of the reference object at this point;

[0038] By judging whether the last route point has been reached, if so, stop moving along the reference object, if not, continue moving forward along the reference object.

[0039] Preferably, the method for applying road markings to the road to be marked includes the following steps:

[0040] According to all the obtained route point coordinate data, process them through translation and interpolation methods to generate a reference path for road marking application; drive along the reference path in a tracing manner and apply road markings.

[0041] Preferably, it further includes a marking system for a road marking application method with human - machine cloud collaboration, including:

[0042] The acquisition system includes construction workers, a tablet, a segway, an acoustic-light-vibration module, and a positioning device; the segway is used to carry construction workers, the tablet, the acoustic-light-vibration module, and the positioning device; the construction workers set the sampling interval parameters through the tablet and determine three coordinate points with different curve radii on the road according to them; substitute the determined three coordinate points into the quadratic curve equation and define the rule equation by solving the quadratic curve equation; according to the rule equation, collect the coordinates of the first three route points and use them to control the segway to move to the circular area range of the next route point, collect the coordinates of the next route point until the last route point, and send it to the cloud system; the positioning device is placed on the segway and obtains positioning data in real time as the segway moves, and is used to be taken off by the construction worker and placed at the reference object to obtain positioning data in real time, and send the positioning data to the tablet wirelessly; the tablet is used to set construction parameters and display the positioning data of the positioning device, and send the construction parameters and positioning data to the cloud system wirelessly; the acoustic-light-vibration module is used to give reminders of sound / light / vibration to the construction workers;

[0043] The cloud system is used to form a circle based on the coordinates of the first three route points closest to the history obtained by the acquisition system, and use the radius of the circle as the curve radius at the next route point; substitute the curve radius at the next route point into the rule equation, calculate the distance from the next route point to the current route point, and so on until calculating the distance from the last route point to the previous route point; according to the distance from the next route point to the current route point, determine the circular area range of the next route point by setting the circular area range parameters; by judging whether the segway moves to the circular area range of the next route point, collect the route point coordinate data. When the segway moves into the circular area range of the next route point, send a stop movement instruction to the acquisition system, and the positioning device collects the route point coordinate data in real time until the last route point to obtain all the route point coordinate data; generate a reference path for road marking application according to all the received route point data and send it to the robot system;

[0044] The robot system is used to receive the reference path sent by the cloud system, track and drive along the reference path, and apply road markings.

[0045] Preferably, the cloud system judges whether the positioning coordinates are within the circular area according to the real-time obtained positioning data. If not, send a continue movement instruction to the acquisition system. If within the circular area, send a stop driving instruction to the acquisition system.

[0046] Preferably, the acquisition system is also used to receive instructions from the cloud system in real time. When a continue movement instruction is received, the sound, light and vibration module does not make sound, light and vibration reminders. When a stop movement instruction is received, the acquisition system sends sound, light and vibration reminders to the construction personnel through the sound, light and vibration modules. After the construction personnel feel the sound, light and vibration reminders, they immediately control the movement of the balance car, remove the positioning device and place it on the reference object of the parking point, read and collect the route point coordinates of the point through the tablet, and send the coordinate data to the cloud system through the tablet.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] The automatic road marking method proposed by the present invention can overcome the problem of rationality of sample point selection in the prior art, which makes the reference path generation have human errors and leads to the technical defects of large errors when the robot marks the road. The method pre-sets the collection rules according to the set sampling interval parameters, collects the coordinates of the first three route points according to the collection rules, and uses them as the basic data for the subsequent collection of route points to support the automatic calculation of the subsequent route point area; calculates the area range of the next route point according to the coordinates of the first three route points acquired in history, and can automatically calculate the location area of the next route point collection based on the degree of road curvature; collects the route point coordinates by judging whether the positioning device moves to the annular area range of the next route point, and collects the route point coordinates when it moves to the next route point area, so as to realize the reasonable collection of route points, thereby reducing labor intensity and improving construction efficiency. According to the collected coordinates of all route points, the reference path can be accurately generated, which improves the accuracy of road marking. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A flow chart of the method for automatically marking road lines proposed by the present invention;

[0050] Figure 2 A schematic diagram of the range of the annular area for calculating the next path point of the present invention;

[0051] Figure 3 Generate a reference path diagram for the present invention;

[0052] Figure 4 The figure is a diagram of the automatic road marking system of the present invention. DETAILED DESCRIPTION

[0053] The following will be combined with the attached embodiment of the present invention Figures 1-4 , the technical solutions in the embodiments of the present invention are clearly and completely described. It should be understood that the terms described in the present invention are only used to describe specific implementation methods and are not used to limit the present invention.

[0054] Traditional manual road marking requires construction workers to operate the line drawing machine to draw the markings along the marked line, resulting in low efficiency and high labor costs. Existing automatic marking techniques rely on construction workers to individually collect the coordinates of route points on foot to generate the reference path for the line drawing robot. As a result, the labor intensity of construction workers is high, and the collection of route points is not standardized, causing driving route errors.

[0055] To solve the problems of low efficiency and heavy workload in manual road marking, as well as the problem of inaccurate reference paths in the existing technology resulting in robot marking errors, the present invention discloses a method and system for human-machine cloud collaboration in road marking. This method can achieve automatic road marking, reduce the labor intensity of construction workers, improve the accuracy of reference path generation, and significantly enhance the efficiency of road construction operations.

[0056] Embodiment

[0057] As Figure 1 shown, an embodiment of the present invention provides a method for human-machine cloud collaboration in road marking, including the following steps:

[0058] S1: Preset the route collection rules in advance;

[0059] S2: According to the collection rules, collect the coordinates of the first 3 route points;

[0060] S3: Starting from the 4th route point, the cloud system predicts the range of the next route point area based on the historical route points;

[0061] S4: The construction worker controls the positioning device, i.e., the self-balancing scooter, to move to the next route point area to collect the route point coordinates until the last route point;

[0062] S5: The cloud system generates a reference path and sends it to the robot system, and the robot system marks the road markings according to the reference path sent by the cloud system.

[0063] Specifically, in step S1, presetting the route collection rules includes the following steps:

[0064] (1) The construction worker sets the sampling interval parameters through the tablet. The specific setting method is: set the sampling interval parameters d1, d2, and d3, where d1 represents the preset sampling interval for roads with a bend radius of 50 meters, d2 represents the preset sampling interval for roads with a bend radius of 200 meters, and d3 represents the preset sampling interval for roads with a bend radius greater than or equal to 500 meters, and send the set parameters to the cloud system;

[0065] (2) The cloud system solves the quadratic curve equation passing through the 3 coordinate points (50, d1), (250, d2), and (500, d3) by the analytical method according to the received sampling interval parameters:

[0066] S = f(r) = ar 2 + br + c

[0067] where r is the radius of the curve, and a, b, and c are the coefficients of the curve equation respectively;

[0068] Define the rule equation as:

[0069]

[0070] And when S < 1, take S = 1.

[0071] (3) Store the rule equation of the cloud system and send the rule equation to the tablet of the acquisition system.

[0072] Specifically, in step S2, the acquisition system acquires the coordinates of the first 3 route points according to the acquisition rule, including the following steps:

[0073] (1) The construction worker rides a balance bike to the reference object at the starting point of the road section to be marked. The reference object can be the road curb / median strip / original lane line, etc., a marker that can represent the trend of the to-be-marked marking. The construction worker holds the positioning device and places it at the first route point, and reads and acquires the coordinates (x1, y1) of the first route point through the tablet;

[0074] (2) The construction worker estimates the road curve radius r1 at the position of the first route point, calculates S1 according to the rule equation displayed on the tablet, controls the balance bike to drive forward a distance of S1, and acquires the coordinates of the reference object here through the positioning device and the tablet as the coordinates (x2, y2) of the second route point;

[0075] (3) The construction worker estimates the road curve radius r2 at the position of the second route point, calculates S2 according to the rule equation displayed on the tablet, controls the balance bike to continue driving forward a distance of S2, and acquires the coordinates of the reference object here through the positioning device and the tablet as the coordinates (x3, y3) of the third route point;

[0076] (4) The construction worker sends the coordinates (x1, y1), (x2, y2), (x3, y3) of the first 3 acquired route points to the cloud system through the tablet.

[0077] Specifically, in step S3, starting from the fourth route point, the cloud system predicts the range of the next route point area based on the historical route points, including the following steps:

[0078] (1) The cloud system background obtains the coordinates of the historical nearest 3 route points and calculates the curve radius of the next route point position. The specific method is: for the i-th route point (i = 4, 5, 6, 7,..., N), obtain the historical nearest 3 route points (x i-3 , yi-3 ), (x i-2 , y i-2 ), (x i-1 , y i-1 ), where N represents the last waypoint; based on 3 historical waypoints (x i-3 , y i-3 ), (x i-2 , y i-2 ), (x i-1 , y i-1 ), solve for the radius r of the circle formed by these 3 coordinate points i-1 and use it as the turning radius at the next waypoint. The solution formula is:

[0079]

[0080] where:

[0081] p i-1 = (d i-3,i-2 + d i-3,i-1 + d i-2,i-1 ) / 2

[0082] (2) The background calculates the distance from the next waypoint to the current waypoint according to the rule equation. The specific method is: Substitute the turning radius r i-1 of the predicted next waypoint position into the rule equation to obtain the distance of the next waypoint as:

[0083]

[0084] and when S i-1 < 1, take S i-1 = 1;

[0085] where the cloud system calculates the circular area range of the next waypoint. The specific method is: As Figure 2 shown, with the (i - 1)th waypoint as the center, and with S i-1 - D as the inner circle radius and S i-1 + D as the outer circle radius, determine the circular area range of the next waypoint. Among them, D represents the circular area range parameter, and D can take the value of D = 1 meter.

[0086] Specifically, in step S4, the construction personnel control the balance car to move to the next waypoint area and collect waypoint coordinates until the last waypoint, including the following steps:

[0087] (1) The acquisition system continues to move along the reference object and reports the positioning data in real time. Specifically, the construction personnel control the balance car to continue moving forward along the reference object. During the driving process, the positioning device obtains the positioning data of the acquisition system in real time and sends it to the cloud system through the tablet;

[0088] (2) Based on the acquired positioning data, the cloud system sends a continue moving / stop moving instruction to the acquisition system. Specifically, according to the real-time acquired positioning data, the cloud system determines whether the positioning coordinates are within the circular area. If not, it sends a continue moving instruction to the acquisition system. If within the circular area, it sends a stop moving instruction to the acquisition system;

[0089] (3) According to the instruction of the cloud system, the acquisition system reminds the construction personnel through sound, light and vibration. Specifically, the acquisition system continuously receives the instruction of the cloud system. When receiving the continue moving instruction, it does not give sound, light and vibration reminders. When receiving the stop moving instruction, the acquisition system uses the sound, light and vibration module to send sound, light and vibration reminders to the construction personnel;

[0090] (4) After the construction personnel feel the sound, light and vibration reminders, they control the balance vehicle to stop moving and collect and upload the route point coordinate data. Specifically, after the construction personnel feel the sound, light and vibration reminders, they immediately control the balance vehicle to stop moving. The construction personnel hold the positioning device and place it on the reference object at the parking point, read and collect the route point coordinates of this point through the tablet, and send the coordinate data to the cloud system through the tablet.

[0091] (5) The acquisition system determines whether it has reached the last route point. If so, the acquisition system no longer continues to move along the reference object. If not, it returns to (1) and continues to move forward along the reference object.

[0092] Specifically, in step S5, the robot system draws road markings according to the reference path issued by the cloud system, as Figure 3 shown, including the following steps:

[0093] (1) Based on all the received route point data, the cloud system processes them through translation and interpolation methods to generate a reference path for road marking drawing and issues it to the robot system.

[0094] (2) After receiving the reference path from the cloud system, the robot system follows the reference path and draws road markings.

[0095] This application also proposes a drawing system for a human-machine-cloud collaborative road marking drawing method, as Figure 4 shown, including:

[0096] The acquisition system includes construction workers, a tablet, a segway, an acoustic-optic-vibration module, and a positioning device; the segway is used to carry construction workers, the tablet, the acoustic-optic-vibration module, and the positioning device; the construction workers set sampling interval parameters through the tablet and determine three coordinate points with different curve radii on the road according to them; according to the three coordinate points, a quadratic curve equation is determined as the rule equation; according to the rule equation, the coordinates of the first three route points are collected and used to control the segway to move to the circular area range of the next route point to collect the coordinates of the next route point until the last route point, and the data is sent to the cloud system; the positioning device is placed on the segway to obtain positioning data in real time as the segway moves, and is used to be taken off by the construction workers and placed at a reference object to obtain positioning data in real time, and the positioning data is sent to the tablet wirelessly; the tablet is used to set construction parameters and display the positioning data of the positioning device, and send the construction parameters and positioning data to the cloud system wirelessly; the acoustic-optic-vibration module is used to give reminders of sound, light, and vibration to construction workers;

[0097] The cloud system is used to form a circle based on the coordinates of the first three route points obtained by the acquisition system recently, and take the radius of the circle as the curve radius at the next route point; substitute the curve radius at the next route point into the rule equation to calculate the distance from the next route point to the current route point, and so on until the distance from the last route point to the previous route point is calculated; according to the distance from the next route point to the current route point, determine the circular area range of the next route point by setting the circular area range parameters; by judging whether the segway moves to the circular area range of the next route point, route point coordinate collection is performed. When the segway moves into the circular area range of the next route point, a stop movement instruction is sent to the acquisition system, and the positioning device collects route point coordinate data in real time until the last route point to obtain all route point coordinate data; according to all the received route point data, a reference path for road marking is generated and sent to the robot system;

[0098] The robot system is used to receive the reference path sent by the cloud system, drive along the reference path in a tracking manner, and apply road markings.

[0099] Among them, the cloud system judges whether the positioning coordinates are within the circular area according to the real-time obtained positioning data. If they are not within the circular area, a continue movement instruction is sent to the acquisition system. If they are within the circular area, a stop driving instruction is sent to the acquisition system.

[0100] The acquisition system is also used to receive the instructions of the cloud system in real time. When the instruction to continue moving is received, the acousto-optic-vibration module does not give acousto-optic-vibration reminders. When the instruction to stop moving is received, the acquisition system uses the acousto-optic-vibration module to send acousto-optic-vibration reminders to the construction workers. After the construction workers feel the acousto-optic-vibration reminders, they immediately control the balance vehicle to stop moving. The construction workers hold the positioning device and place it on the reference object at the parking point, read and collect the route point coordinates of this point through the tablet, and send the coordinate data to the cloud system through the tablet.

[0101] The present invention can provide an automated construction method for road marking, reduce manual operation errors, significantly improve the efficiency of road marking, and reduce the work intensity of construction workers.

[0102] The above is only the preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent replacements or changes, and all should be covered within the protection scope of the present invention.

[0103] In addition, unless otherwise specified, all technical and scientific terms used in the present invention have the same meanings as those commonly understood by those of ordinary skill in the art to which the present invention belongs. All documents mentioned in this specification are incorporated by reference to disclose and describe the methods related to the documents. In case of conflict with any incorporated document, the content of this specification shall prevail.

Claims

1. A method for applying road markings through human-machine cloud collaboration, characterized in that, Including the following steps: Set the sampling interval parameter and determine three coordinate points for different curve radii of the road according to it; according to the three coordinate points, determine the quadratic curve equation as the rule equation; according to the rule equation, collect the coordinates of the first three route points; Form a circle based on the coordinates of the three nearest historical route points obtained, and use the radius of the circle as the curve radius at the next route point; substitute the curve radius at the next route point into the rule equation to calculate the distance from the next route point to the current route point, and so on until the distance from the last route point to the previous route point is calculated; According to the distance from the next route point to the current route point, determine the annular area range of the next route point by setting the annular area range parameter; Collect the route point coordinates by judging whether the positioning device moves to the annular area range of the next route point. When the positioning device moves into the annular area range of the next route point, collect the coordinate data of this route point until the last route point to obtain all the route point coordinate data; Generate a reference path for road marking application according to all the route point coordinate data; follow the reference path along the reference path to apply road markings to the road.

2. The method for applying road markings through human-machine-cloud collaboration according to claim 1, wherein The definition of the rule equation includes the following steps: Set the sampling interval parameters d1, d2, and d3; where d1 represents the preset sampling interval for a road with a curve radius of 50 meters, d2 represents the preset sampling interval for a road with a curve radius of 200 meters, and d3 represents the preset sampling interval for a road with a curve radius greater than or equal to 500 meters; According to the sampling interval parameters, solve the quadratic curve equation passing through the coordinate points (50, d1), (250, d2), and (500, d3) by the analytical method: S = f(r) = ar 2 + br + c where r is the curve radius, and a, b, and c are the coefficients of the curve equation respectively; Define the rule equation as: And when S < 1, take S = 1.

3. The method for applying road markings through human-machine-cloud collaboration according to claim 2, wherein, The collection of the coordinates of the first three route points includes the following steps: Determine the reference object according to the road curb / central isolation belt / original lane line of the road; Place the positioning device at the reference object at the starting point of the section to be marked, read and collect the coordinates (x1, y1) of the first route point as the first route point; Estimate the curve radius r1 of the road at the position of the first route point (x1, y1), calculate S1 according to the rule equation, continue to drive forward S1 distance by controlling the positioning device, place the positioning device at the reference object and obtain the coordinates at the reference object, and use this coordinate as the coordinates of the second route point (x2, y2); Estimate the curve radius r2 of the road at the position of the second route point (x2, y2), calculate S2 according to the rule equation, continue to drive forward S2 distance by controlling the positioning device, place the positioning device at the reference object and obtain the coordinates at the reference object, and use this coordinate as the coordinates of the third route point (x3, y3).

4. The method for applying road markings through human-machine-cloud collaboration according to claim 3, wherein The solution process of the curve radius at the next route point includes the following steps: For the i-th route point, where i = 4, 5, 6, 7, …, N, obtain the three most recent historical route points (x i-3 , y i-3 ), (x i-2 , y i-2 ), (x i-1 , y i-1 ), where N represents the last route point; According to the three most recent historical waypoints (x i-3 , y i-3 ), (x i-2 , y i-2 ), (x i-1 , y i-1 ), solve for the radius r i-1 of the circle formed by these three coordinate points, and use it as the turning radius at the i-th waypoint. The solution formula is: where p i-1 =(d i-3,i-2 +d i-3,i-1 +d i-2,i-1 ) / 2, and d i-3,i-2 represents the straight-line distance between the (i - 3)-th waypoint and the (i - 2)-th waypoint, d i-3,i-1 represents the straight-line distance between the (i - 3)-th waypoint and the (i - 1)-th waypoint, and d i-2,i-1 represents the straight-line distance between the (i - 2)-th waypoint and the (i - 1)-th waypoint.

5. The method for applying road markings through human-machine-cloud collaboration according to claim 4, characterized in that The determination of the annular area range of the next route point includes the following steps: The curve radius r of the calculated next waypoint position i-1 Substitute it into the rule equation, and the distance from the next waypoint to the current waypoint is obtained as follows: And when S i-1 < is less than 1, take S i-1 = 1; With the (i - 1)-th route point as the center, respectively using S i-1 - D as the inner circle radius and S i-1 + D as the outer circle radius, determine the annular region range of the next route point, where D represents the annular region range parameter.

6. The method for applying road markings through human-machine-cloud collaboration according to claim 5, wherein, The acquisition of all the route point coordinate data includes the following steps: Continue to move forward along the reference object by manipulating the positioning device, and obtain positioning data in real time through the positioning device; According to the positioning data obtained in real time, by judging whether the positioning coordinates are within the circular area. If not, manipulate the positioning device to continue moving forward along the reference object; if within the circular area, immediately control the positioning device to stop moving and place it at the reference object at the parking point through audible, visual, and vibration reminders, and collect the route point coordinates of the reference object at this point; By judging whether the last route point has been reached. If so, no longer continue to move along the reference object. If not, continue to move forward along the reference object.

7. The method for applying road markings through human-machine cloud collaboration according to claim 6, characterized in that, The road marking for the road to be marked includes the following steps: According to all the obtained route point coordinate data, process it through translation and interpolation methods to generate a reference path for road marking; drive along the reference path in a tracking manner and mark the road markings.

8. The application system for the road marking application method of human-machine-cloud collaboration according to any one of claims 1 to 7, characterized in that, Including: A collection system, including construction workers, a tablet, a self-balancing scooter, an audible / visual / vibration module, and a positioning device; the self-balancing scooter is used to carry construction workers, a tablet, an audible / visual / vibration module, and a positioning device; the construction workers set the sampling interval parameter through the tablet and determine three coordinate points with different curve radii on the road according to it; according to the three coordinate points, determine the quadratic curve equation as the regular equation; according to the regular equation, collect the coordinates of the first three route points and use them to control the self-balancing scooter to move to the circular area range of the next route point for collecting the coordinates of the next route point until the last route point and send it to the cloud system; the positioning device is placed on the self-balancing scooter to obtain positioning data in real time as it moves, and is used to be taken off by the construction worker and placed at the reference object to obtain positioning data in real time, and send the positioning data to the tablet wirelessly; the tablet is used to set construction parameters and display the positioning data of the positioning device, and send the construction parameters and positioning data to the cloud system wirelessly; the audible / visual / vibration module is used to give reminders of sound / light / vibration to the construction workers; A cloud system, used to form a circle based on the coordinates of the three most recent historical route points obtained by the collection system, and use the radius of the circle as the curve radius at the next route point; substitute the curve radius at the next route point into the regular equation to calculate the distance from the next route point to the current route point, and so on until calculating the distance from the last route point to the previous route point; according to the distance from the next route point to the current route point, determine the circular area range of the next route point by setting the circular area range parameter; by judging whether the self-balancing scooter has moved into the circular area range of the next route point for route point coordinate collection. When the self-balancing scooter moves into the circular area range of the next route point, send a stop movement instruction to the collection system, and the positioning device collects route point coordinate data in real time until the last route point to obtain all the route point coordinate data; generate a reference path for road marking according to all the received route point data and send it to the robot system; A robot system, used to receive the reference path sent by the cloud system, drive along the reference path in a tracking manner, and mark the road markings.

9. The application system for the road marking application method of human-machine-cloud collaboration according to claim 8, wherein The cloud system determines whether the positioning coordinates are within the circular area according to the real-time obtained positioning data. If they are not within the circular area, it sends a continue movement instruction to the acquisition system. If they are within the circular area, it sends a stop driving instruction to the acquisition system.

10. The application system for the road marking application method of human-machine-cloud collaboration according to claim 9, characterized in that The acquisition system is also used to receive the instructions of the cloud system in real time. When receiving the continue movement instruction, the acoustic-optic-vibration module does not give an acoustic-optic-vibration reminder. When receiving the stop movement instruction, the acquisition system uses the acoustic-optic-vibration module to send acoustic, optical, and vibration reminders to the construction personnel. After the construction personnel feel the acoustic-optic-vibration reminder, they immediately control the movement of the balance vehicle. The construction personnel remove the positioning device and place it at the reference object at the parking point, read and collect the route point coordinates of this point through the tablet, and send the coordinate data to the cloud system through the tablet.

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