Design method of wheel type card reading robot system for urban road parking spaces

Abstract

The invention provides a wheel type card reading robot system design method for urban road parking spaces, which realizes regulation violation monitoring and charging management of urban roadside parking vehicles based on a wheel type card reading robot. Comprising a card reading robot and geomagnetic sensor collaborative interaction subsystem, a subsystem for controlling the card reading robot to arrive at a parking space with an appointed number, a card reading detection subsystem based on a holder, a rule violation judgment subsystem based on the card reading robot, a parking charging subsystem based on the card reading robot and a card reading robot task planning subsystem. A collaborative interaction subsystem is established, and the use condition of the parking space is managed in real time; according to the mapping relation between the position of the robot and the number of the parking space, the robot moves to the parking space; the peccancy judgment subsystem analyzes the vehicle position feature data and identifies peccancy vehicles; the parking charging subsystem designs a vehicle charging standard and feeds back the vehicle charging standard to the user terminal; the task planning system optimizes the card reading sequence and the parking position, and improves the system efficiency and the response speed.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of service robots, in particular to a wheeled license plate copying robot system design method for urban road parking spaces. BACKGROUND

[0003] The introduction of wheeled license plate copying robot technology has become a potential solution. These robots can autonomously patrol urban roads, accurately perceive the surrounding environment, including road conditions and vehicle parking situations, using advanced perception technologies such as laser radar, cameras and infrared sensors. Through autonomous navigation technology, they can plan the optimal path, avoid obstacles and quickly reach the target area. For pre-charged sections, license plate recognition of target vehicles can be achieved. Once a violation is found, the robot can automatically take evidence and generate a violation notice or report according to pre-set rules.

[0004] In contemporary society, the idea of replacing humans with machines to perform repetitive work is advocated. This not only ensures the safety and comfort of the work environment, but also significantly improves work efficiency and reduces costs. In terms of handling violation vehicles and issuing fines, there is also the prospect of using machines to replace traffic law enforcement personnel. Although there is currently no device that can completely replace traffic police officers in terms of operational effectiveness, this is undoubtedly a trend for future development. In summary, the introduction of wheeled license plate copying robot technology brings a new solution to urban parking management, improves law enforcement efficiency, reduces labor costs and provides a sustainable development path for urban traffic management. SUMMARY

[0005] The purpose of the present application is to provide a wheeled license plate copying robot design scheme for urban road parking spaces to solve the problems raised in the background technology.

[0006] To solve the problems raised in the background technology, the technical solution adopted by the present application is as follows:

[0007] A wheeled license plate copying robot system design scheme for urban road parking spaces, which is designed for specific urban road scenarios and includes the following steps:

[0008] (1) The present application requires the installation of sensor equipment on specific urban parking space sections, and a geomagnetic sensor needs to be laid for each parking space to detect the parking situation of vehicles in real time. According to the length of the robot license plate copying path, charging piles need to be arranged at appropriate intervals. Each charging pile can serve as a charging station and waiting area for the robot when it is idle, to ensure that the robot has enough power when performing tasks and can return to charging in time after completing the task;

[0009] (2) Construct a high-definition city parking data map, and provide the information of the current road elements to the mobile robot to realize the numbering and management of the parking spaces in the information interaction center unit, which can be realized by two parts: 1) in the high-definition city parking data map, the parking spaces on both sides of the road are divided according to the environmental map and the width PARK_WTH and the length PARK_LEG of the roadside parking spaces in the city, and are numbered in sequence, and the corresponding numbered information is saved in the free list of the information center; 2) a geomagnetic induction device is installed in each parking space in the high-definition city parking data map, which monitors the vehicle entry and exit state in real time, and when the vehicle sensing unit receives the vehicle entry signal Enter_Signal, the signal is encoded into the corresponding parking space number and sent to other subsystems;

[0010] (3) Control the license plate copying robot to arrive at the specified numbered parking space, and the wheeled robot starts from the current parking space area to establish a global inspection route parallel to the road marking line in the drivable area of the robot to reach the target pre-parking space; the navigation mobile unit determines the number Park_LID of the roadside parking space in the current high-definition city parking data map Wheel_Robot_Map during the movement of the wheeled robot according to the real-time global GPS positioning information Wheel_Robot_POS of the wheeled robot, the movement speed Wheel_Robot_VEL of the wheeled robot and the distance Wheel_Robot_DIS that the wheeled robot has traveled;

[0011] (4) Based on the extracted parking space laser point cloud information and the parking space edge line information of the high-definition city parking data map, the illegal situation is judged. The wheeled license plate copying robot divides the laser radar point cloud information in the CAR_LEN*CAR_WTH rectangular range according to the vehicle length CAR_LEN and the width CAR_WTH in the laser radar coordinate system, converts the extracted laser radar point cloud information to the high-definition city parking data map coordinate system, and calculates the relative position of the real-time point cloud and the target parking line of the map;

[0012] (5) Based on the vehicle detection algorithm, the vehicle tail bounding box is identified, a method for automatically calculating the pan-tilt rotation data based on the vehicle box is designed, the image data of the whole vehicle area is obtained through the camera, the image reaches the highest resolution effect, the parking space number, the parking time point of the toll road section are established, and the mapping relationship between the parking duration and the charging standard is established, and the robot realizes autonomous license plate copying and charging.

[0013] As a further technical scheme of the present application, in step (1), the specific roadside parking space layout of the city section can be developed in three steps:

[0014] The arrangement position of the selected geomagnetic sensor is selected, and the range of the urban roadside parking space is 6m*2.5m, and the geomagnetic induction intensity within the range can be regarded as basically unchanged. When a vehicle enters the detection range of the geomagnetic sensor, the magnetic field distribution above the parking space is disturbed. In the design scheme, the geomagnetic vehicle detector is placed in the center of the parking space, and the geomagnetic sensor is about 15-20cm away from the vehicle chassis.

[0015] In the process of identifying the parking space in the point high-definition city parking space data map, the parking space is first numbered according to the predetermined rule, so that it has a unique identification in the map. Then, two linked lists are constructed to manage these parking spaces: one is the occupied linked list, which is used to record the current occupied parking space number; the other is the idle linked list, which is used to record the idle parking space number. When the system receives the geomagnetic induction information, corresponding operations will be performed in the two linked lists according to the specific situation: the corresponding parking space number in the idle linked list is popped out, and the number is added to the occupied linked list. The management system based on this design facilitates the query of idle parking space information for parking vehicles.

[0016] The design and arrangement of the charging pile involve two main aspects: first, the main part of the charging pile must be able to effectively dock the robot charging port, considering the shape, size and connection method of the charging socket, to ensure the convenience and stability of the charging operation. Second, the design of the distance measuring docking plate needs to ensure accurate distance measurement during the robot docking process, focusing on ensuring that the distance between the distance measuring docking plate and the laser radar is greater than the blind distance of the laser radar. In terms of arrangement, the charging area can be planned according to the needs to ensure that the robot can find the charging point in time for charging or waiting.

[0017] As a further technical solution of the present application, in step (2), the construction of the high-definition city parking space data map can be carried out through the following two parts:

[0018] The high-definition city parking space data map fuses the city road boundary line information, robot drivable area marking line, road sign information and parking space boundary line information as semantic elements into the point cloud data map. This process is based on the environmental point cloud map. First, according to the distribution of the parking space beside the city road, the starting point, ending point and section point of the road section are determined in the environmental map, and the section points are divided at equal intervals to convert them into point cloud semantic data, which are finally added to the map. Second, the divided parking space boundary is processed by using straight line fitting to generate continuous boundary line information, and the robot drivable area is set to within 1.5 meters of the parking space boundary line, so as to obtain the marking line of the robot drivable area. Finally, the road sign information on the roadside is identified, so that the entire map has more semantic information, providing more reference for the navigation and decision-making of the robot.

[0019] As a further technical solution of the present application, in step (3), the mapping relationship between the real-time position of the robot and the number of the roadside parking space in the high-definition city parking space data map can be established by the following method:

[0020] According to the real-time global GPS positioning information Robot POS of the wheeled robot, the moving speed Robot VEL of the wheeled robot and the distance Robot DIS that the wheeled robot has traveled, the number Park LID of the roadside parking space in the current high-definition city parking space data map Robot Map is determined during the movement of the wheeled robot:

[0021] Robot Map POSX = Robot X + δ·Robot θ·(Robot VEL·t + Robot DIS)

[0022] Robot Map POSY = Robot Y + δ·Robot θ·(Robot VEL·t + Robot DIS)

[0023] Robot Map POS = α·Robot GPS + β·Conv(Robot Map POSX, Robot Map POSY)

[0024] Park LID = map(Robot Map, Robot Map POS)

[0025] Wherein, Robot Map POSX and Robot Map POSY represent the lateral and longitudinal coordinates of the wheeled robot in the high-definition city parking space data map coordinate system, Robot X and Robot Y are the GPS longitude and latitude of the wheeled robot at the starting time, Robot θ is the yaw angle of the wheeled robot in the GPS coordinate system, δ is the correction coefficient of the heading angle, t is the walking time of the robot, the function Conv represents the coordinate conversion relationship between the GPS coordinate system of the wheeled robot and the global map, α and β are the correction coefficients of the GPS coordinate and the map coordinate, Robot Map POS is the position coordinate in the map coordinate system of the mobile robot, the function map is the mapping relationship between the real-time map position of the wheeled robot and the number of the parking space in the map.

[0026] As a further technical solution of the present application, in step (4), based on the geometric features of the vehicle, the corresponding parking space vehicle laser point cloud information is determined, the relative position between the vehicle laser point cloud and the boundary line of the roadside parking space in the city is calculated, and the illegal situation is judged according to the following steps:

[0027] The wheeled license plate copying robot divides the laser radar point cloud information in a CAR_LEN*CAR_WTH rectangular range according to the vehicle length CAR_LEN and the vehicle width CAR_WTH in a laser radar coordinate system;

[0028] The extracted laser radar point cloud information is converted to a high-definition city parking space data map coordinate system, and the relative position of the real-time point cloud and the target parking line on the map is calculated;

[0029] The vehicle whose relative position exceeds the parking area is judged as a vehicle in violation of the parking regulations, the corresponding license plate information is queried from the license plate list License_INFO according to the parking space number Cur_Parking_NUM, and a parking violation notice is sent to the corresponding vehicle owner user terminal.

[0030] As a further technical solution of the application, in the step (5), the autonomous license plate copying detection based on the pan-tilt and the parking fee collection based on the license plate copying robot, the steps include:

[0031] The method for autonomously calculating the pan-tilt data based on the vehicle identification frame is as follows: the coordinates of the top left vertex of the vehicle tail identification frame are (x1, y1), the coordinates of the bottom right vertex of the vehicle tail identification frame are (x2, y2), the vehicle pose angle deviation is α, the vehicle width is d (the average width of small cars is 1.7m), the distance from the license plate copying position to the vehicle tail is l, and the license plate copying position of the robot can be represented as p: x3=x2+(l-d / 2cot(α))cos(α), y3=y2+(l-d / 2cot(α))sin(α); the license plate copying position of the robot is calculated through the above process, the angle of the pan-tilt is calculated based on the current position, the height of the robot pan-tilt is h, the height of the license plate from the ground is m, and the width of the license plate is n, and the pan-tilt angle is calculated as: β=tan^(-1)(((n / 2+m)-h) / l); the license plate information License_INFO is detected by using the real-time image of the pan-tilt, and the license plate information is transmitted to other systems.

[0032] The license plate copying robot parking fee collection subsystem establishes a pre-charge vehicle information list Pre_Charge_LIST, which includes the pre-charge parking space number information Cur_Parking_NUM from the license plate copying robot cooperative geomagnetic interaction subsystem, the vehicle entry time point TIME_IN and the exit time point TIME_OUT, and the license plate information License_INFO from the wheeled license plate copying detection subsystem;

[0033] Extract the time information of the parking space Cur_Parking_NUM from the pre-charged vehicle information list Pre_Charge_LIST, the vehicle entry time point TIME_IN, the vehicle exit time point TIME_OUT, and the parking time is CAR_STOP_TIME=TIME_OUT-TIME_IN;

[0034] The parking fee subsystem of the parking ticket-collecting robot constructs a mapping relationship between parking time and charging standard: Actual_Charge=charge(CAR_STOP_TIME), and sends parking information and actual fees to the user terminal. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic diagram of the subsystem composition and information interaction of a design method for a wheeled parking ticket-collecting robot system for urban road parking spaces according to the present invention;

[0036] Figure 2 This is a schematic diagram of the overall structure of a roadside parking space on a specific urban road section according to the present invention;

[0037] Figure 3 This is a schematic diagram of the pan-tilt pitch angle conversion in the pan-tilt-based ticket-checking detection subsystem of the present invention. DETAILED DESCRIPTION

[0038] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0039] like Figure 1 As shown, this embodiment provides a design solution for a wheeled parking ticket collection robot system for urban road parking spaces in specific road scenarios.

[0040] S101, design of the cooperative interaction subsystem between the ticket collection robot and the geomagnetic sensor;

[0041] S102, design of the subsystem that controls the parking robot to reach the designated numbered parking space;

[0042] S103, design of a ticket-checking detection subsystem based on a PTZ;

[0043] S104, design of the violation judgment subsystem based on the ticket-checking robot;

[0044] S105, Design of parking fee collection subsystem based on ticket collection robot;

[0045] S106, Design of the task planning subsystem of the license plate copying robot;

[0046] described Figure 1The S101 in the S100, the design of the interaction subsystem of the license plate copying robot and the geomagnetic sensor can be developed in three steps in turn.

[0047] The specific urban road section roadside parking space layout, such as Figure 2 It includes the parking space (C21) set on the side of the urban road, the geomagnetic vehicle sensor (C22) set in the parking space (C21), the parking space management terminal (C23) connected with the vehicle sensor, the information management center (C24), the wheeled robot (C25) set on one side of the parking space, the autonomous docking charging pile (C26) set in the fixed section, and the data acquisition, processing and control system installed in the wheeled robot (C25).

[0048] The selected geomagnetic sensor is arranged in the range of 6m*2.5m of the urban roadside parking space, and the geomagnetic induction intensity in this range is considered to be basically unchanged. When a vehicle enters the detection range of the geomagnetic sensor, the magnetic field distribution above the parking space is disturbed. In this design, the geomagnetic vehicle detector is placed in the center of the parking space, and the geomagnetic sensor is about 15-20cm away from the vehicle chassis. The design and arrangement of the charging pile involve two main aspects. First, the main part of the charging pile must be able to effectively dock the robot charging port, considering the shape, size and connection method of the charging socket, to ensure the convenience and stability of the charging operation. Second, the design of the distance measuring docking plate needs to ensure accurate distance measurement during the robot docking process, focusing on ensuring that the distance between the distance measuring docking plate and the laser radar after docking is greater than the blind distance of the laser radar. In terms of arrangement, the charging area can be planned according to the needs to ensure that the robot can find the charging point in time for charging or waiting.

[0049] In the high-definition urban parking space data map, according to the environment map and the urban road roadside parking space width PARK_WTH and the parking space length PARK_LEG, the parking spaces on both sides of the road are divided and numbered according to the preset rules, and the corresponding number is saved to the map parking space number list Map_LIST; using the geomagnetic sensor to monitor the vehicle entry and exit state in real time, when the system receives the geomagnetic driving-in and driving-out signal, the corresponding Map_LIST parking space number Cur_Parking_NUM is extracted, the license plate chain table Pre_License_LIST is established, and is sent to all other subsystems. At the same time, when the geomagnetic sensing device receives the vehicle driving-in signal, the driving-in time point TIME_IN is added to the Pre_License_LIST of the corresponding parking space, and when the vehicle driving-out signal is received, the driving-out time point TIME_OUT is added to the Pre_License_LIST of the corresponding parking space.

[0050] The Figure 1In S102, the subsystem for controlling the ticket-collecting robot to reach a designated parking space is designed. The wheeled robot starts from the current parking space area and establishes a global inspection route parallel to the road markings within the robot's drivable area to accurately reach the target pre-parking space Pre_Parking_NUM = Cur_Parking_NUM - 1. Based on the wheeled robot's real-time global GPS positioning information Robot_POS, the wheeled robot's movement speed Robot_VEL, and the distance the wheeled robot has currently traveled Robot_DIS, the number of the roadside parking space in the current high-definition urban parking space data map Robot_Map is determined during the wheeled robot's movement: Park_LID:

[0051] Robot_Map_POSX=Robot_X+δ·Robotθ·(Robot_VEL·t+Robot_DIS)

[0052] Robot_Map_POSY=Robot_Y+δ·Robotθ·(Robot_VEL·t+Robot_DIS)

[0053] Robot_Map_POS=α·Robot_GPS+β·Conv(Robot_Map_POSX,Robot_Map_POSY)

[0054] Park_LID=map(Robot_Map, Robot_Map_POS

[0055] described Figure 1 In S103, the design of the PTZ-based ticket detection subsystem is mainly carried out through the following steps:

[0056] The PTZ-based parking detection subsystem receives the actual parking space number Cur_Parking_NUM from the parking robot and geomagnetic sensor cooperative interaction subsystem, determines the position of the license plate relative to the rear of the vehicle, and converts it into the PTZ pitch angle to achieve license plate recognition. The vehicle detection algorithm is used to identify the bounding box of the rear of the vehicle, such as Figure 3 , let the coordinates of the upper left vertex of the vehicle tail identification box be (x1, y1), the coordinates of the lower right vertex of the vehicle tail identification box be (x2, y2), the attitude angle deviation between the vehicle and the robot be α, the vehicle width be d, and the distance between the ticket-collecting position and the vehicle tail be r. The robot's ticket-collecting position can be expressed as p: x3 = x2 + (rd / 2cot(α)) cos(α), y3 = y2 + (rd / 2cot(α)) sin(α);

[0057] The robot license plate copying position calculated by the above process, the angle of the gimbal pitch, the robot gimbal height is h, the height of the license plate from the ground is m, the width of the license plate is n, and the gimbal pitch angle β is calculated as follows:

[0058] β=tan^(-1)(((n / 2+m)-h) / r)

[0059] The license plate information is transmitted to the illegal parking judgment subsystem based on the license plate copying robot and the parking fee subsystem based on the license plate copying robot.

[0060] The Figure 1 S104 in the above, the design of the illegal parking judgment subsystem based on the license plate copying robot is carried out according to the following three steps:

[0061] The wheeled license plate copying robot divides the laser radar point cloud information in the CAR_LEN*CAR_WTH rectangular range according to the vehicle length CAR_LEN and the width CAR_WTH in the laser radar coordinate system;

[0062] The extracted laser radar point cloud information is converted to the high-definition city parking space data map coordinate system, and the relative position of the real-time point cloud and the target parking line is calculated.

[0063] The vehicle whose relative position exceeds the parking area is judged as a vehicle in violation of the law, the corresponding license plate information is queried from the license plate list License_INFO according to the parking number Cur_Parking_NUM, and a notice of illegal parking is sent to the corresponding vehicle owner terminal.

[0064] The Figure 1 S105 in the above, the design of the parking fee subsystem based on the license plate copying robot is carried out according to the following two steps:

[0065] The license plate copying robot parking fee subsystem establishes a pre-charge vehicle information list Pre_Charge_LIST, including the pre-charge parking space number information Cur_Parking_NUM from the license plate copying robot cooperative geomagnetic interaction subsystem, the vehicle entry time point TIME_IN and the exit time point TIME_OUT, and the license plate information License_INFO from the wheeled robot license plate detection subsystem, extracts the time information of the parking space Cur_Parking_NUM, the vehicle entry time point TIME_IN, the vehicle exit time point TIME_OUT, and the parking time CAR_STOP_TIME=TIME_OUT-TIME_IN from the pre-charge vehicle information list Pre_Charge_LIST;

[0066] The license copying robot parking fee subsystem constructs a mapping relationship between parking time and charging standard Actual_Charge=charge(CAR_STOP_TIME), and sends the parking information and actual fee to the user terminal.

[0067] The Figure 1 S106 in the above formula, based on the design of the license copying robot task planning subsystem, is performed in the following three aspects:

[0068] When multiple vehicle entry signals are simultaneously received in the license copying robot and geomagnetic sensor cooperative interaction subsystem, a distance and entry time priority mechanism is added to the license copying vehicle position number in the license copying license list Pre_License_LIST based on the real-time position of the robot, and the license copying vehicle position numbers are arranged in order according to the scores in the mechanism;

[0069] The license copying robot and geomagnetic sensor cooperative interaction subsystem feedbacks the vehicle position number information, and dynamically adjusts the position of the wheeled robot when it is idle by counting the parking space occupancy in different time periods and different road sections.

[0070] The size of the vehicle tail identification frame and the resolution score of license plate recognition in the pan-tilt-based license copying detection subsystem are fed back to determine the vehicle type and the selection of the pre-license copying position, and to optimize the path of the license copying robot to the license copying vehicle position.

[0071] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and are not limited thereto; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope defined by the claims of the present application.

Claims

1. A design method for a wheeled parking ticket collection robot system for urban road parking spaces, characterized by: The application discloses a wheel-type license plate copying robot for realizing illegal parking monitoring and charging management of urban roadside parking vehicles. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The control license plate copying robot to reach the specified number parking space subsystem establishes the mapping relationship between the real-time position of the robot and the number of the roadside parking space in the high-definition urban parking space data map through the real-time positioning information of the wheel robot, controls the robot to accurately reach the specified parking space along the drivable area, and realizes the autonomous movement control of the license plate copying robot. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information.

2. The method of claim 1, wherein: The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in and driving-out signals from the geomagnetic induction device, converting the vehicle geomagnetic induction signals into the coding of the parking space in the high-definition urban parking space data map, and realizing the interaction of multi-system information. The license plate copying robot and the geomagnetic sensor cooperative interaction subsystem is used for managing vehicle driving-in The geomagnetic induction device receives a vehicle entry signal, adds an entry time point TIME_IN to a Pre_License_LIST corresponding to a parking space, receives a vehicle exit signal, and adds an exit time point TIME_OUT to the Pre_License_LIST corresponding to the parking space.

3. The method of claim 1, wherein: In the subsystem for controlling the license plate copying robot to reach a specified number parking space, the wheeled license plate copying robot obtains the current parking space number through real-time positioning information, and controls the robot to reach the specified parking space along the drivable area, that is, the wheeled robot starts from the current parking space area, establishes a global inspection route parallel to the road marking line in the robot drivable area to reach the target pre-parking space Pre_Parking_NUM=Cur_Parking_NUM-1; according to the real-time global GPS positioning information Robot_POS of the wheeled robot, the moving speed Robot_VEL of the wheeled robot, and the distance Robot_DIS that the current wheeled robot has traveled, the number Park_LID of the roadside parking space in the current high-definition urban parking space data map Robot_Map is determined during the movement of the wheeled robot: Robot_Map_POSX=Robot_X+δ·Robotθ·(Robot_VEL·t+Robot_DIS) Robot_Map_POSY=Robot_Y+δ·Robotθ·(Robot_VEL·t+Robot_DIS) Robot_Map_POS=α·Robot_GPS+β·Conv(Robot_Map_POSX,Robot_Map_POSY) Park_LID=map(Robot_Map,Robot_Map_POS) Wherein, Robot_Map_POSX and Robot_Map_POSY represent the lateral and longitudinal coordinates of the wheeled robot in the high-definition urban parking space data map coordinate system, Robot_X and Robot_Y are the GPS longitude and latitude of the wheeled robot at the starting time, Robotθ is the yaw angle of the wheeled robot in the GPS coordinate system, δ is the correction coefficient of the heading angle, t is the walking time of the robot, the function Conv represents the coordinate conversion relationship between the GPS coordinate system of the wheeled robot and the global map, α and β are the correction coefficients of the GPS coordinates and the map coordinates, Robot_Map_POS is the position coordinates in the mobile robot map coordinate system, and the function map is the mapping relationship between the real-time map position of the wheeled robot and the parking space number in the map.

4. The method of claim 1, wherein: The license plate copying detection subsystem based on the holder receives the actual license plate copying parking space number Cur_Parking_NUM from the license plate copying robot and the geomagnetic sensor cooperative interaction subsystem, determines the position of the license plate relative to the tail of the vehicle, and converts it into the pitch angle of the holder to realize license plate recognition, specifically: The vehicle tail bounding box is identified by a vehicle detection algorithm. The coordinates of the top-left corner of the vehicle tail bounding box are (x1, y1), the coordinates of the bottom-right corner of the vehicle tail bounding box are (x2, y2), the vehicle pose angle deviation is α, the vehicle width is d, and the distance from the license plate position to the vehicle tail is r. The license plate position of the robot can be represented as p: x3 = x2 + (r - d / 2cot(α))cos(α), y3 = y2 + (r - d / 2cot(α))sin(α). The gimbal pitch angle β is calculated based on the robot license plate position calculated by the above process. The robot gimbal height is h, the license plate height from the ground is m, and the license plate width is n. The gimbal pitch angle β is calculated as follows: β = tan^(-1)(((n / 2 + m) - h) / r) The vehicle license plate information License_INFO is detected using the gimbal real-time image, and the license plate information is transmitted to the illegal parking judgment subsystem based on the license plate robot and the parking fee subsystem based on the license plate robot.

5. The method of claim 1, wherein: The illegal parking judgment subsystem based on the license plate robot determines the relative position of the vehicle parking position and the parking line, and determines the illegal parking situation. Specifically: The wheeled license plate robot divides the laser radar point cloud information in the CAR_LEN*CAR_WTH rectangular range according to the vehicle length CAR_LEN and width CAR_WTH in the laser radar coordinate system. The extracted laser radar point cloud information is converted to the high-definition city parking data map coordinate system, and the relative position of the real-time point cloud and the map target parking line is calculated. If the relative position exceeds the parking area, the vehicle is determined as an illegal vehicle. The corresponding license plate information is queried from the license plate list License_INFO according to the parking number Cur_Parking_NUM, and a violation notice is sent to the corresponding vehicle owner terminal.

6. The method of claim 1, wherein: The license plate robot parking fee subsystem establishes a corresponding relationship between time and cost based on the charging standard according to the vehicle entry and exit time and parking space number fed back by the license plate robot cooperative geomagnetic interaction subsystem. Specifically: The license plate robot parking fee subsystem establishes a pre-charge vehicle information list Pre_Charge_LIST, which includes the pre-charge parking space number information Cur_Parking_NUM from the license plate robot cooperative geomagnetic interaction subsystem, the vehicle entry time point TIME_IN and exit time point TIME_OUT, and the license plate information License_INFO from the wheeled license plate detection subsystem; The time information of the parking space Cur_Parking_NUM is extracted from the pre-charge vehicle information list Pre_Charge_LIST, the vehicle entry time point TIME_IN, the vehicle exit time point TIME_OUT, and the parking time CAR_STOP_TIME = TIME_OUT - TIME_IN. The license copying robot parking fee subsystem constructs a mapping relationship between parking time and charging standard Actual_Charge=charge(CAR_STOP_TIME), and sends parking information and actual fee to the user terminal.

7. The method of claim 1, wherein: The license copying robot task planning subsystem is arranged in the wheeled license copying robot background management center, analyzes and counts the parking information fed back by other subsystems in time and space, and realizes management and optimization of the license copying sequence of the license copying robot for multiple parked vehicles, and the parking position of the robot in the idle state. Specifically: When the license copying robot and the geomagnetic sensor cooperative interaction subsystem simultaneously receives multiple vehicle entry signals, a distance and entry time priority mechanism is added to the license copying parking space number in the license copying linked list Pre_License_LIST based on the real-time position of the robot, and the license copying parking space number sequence is arranged according to the score in the mechanism. The license copying robot and the geomagnetic sensor cooperative interaction subsystem feed back the parking space number information, count the parking space occupation in different time periods and different road sections, and dynamically adjust the position of the wheeled robot in the idle state. The size of the vehicle tail identification frame and the resolution score of the license plate recognition in the pan-tilt-based license copying detection subsystem are fed back to judge the vehicle type and the selection of the pre-license copying position, and to optimize the path of the license copying robot to the license copying parking space.

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