Movable magnetic field data acquisition system and data acquisition method thereof

Abstract

The invention provides a movable magnetic field data acquisition system and a data acquisition method thereof, the system comprises an optical positioning platform and an intelligent unmanned vehicle platform, the intelligent unmanned vehicle platform is provided with an optical positioning ball, an unmanned vehicle moving unit, an edge computer unit and a data acquisition unit, and the optical positioning platform is provided with an infrared camera and an industrial personal computer; the infrared camera is used for detecting real-time position information and attitude information of the unmanned vehicle moving unit, and the industrial personal computer is used for storing the real-time position information and attitude information of the unmanned vehicle moving unit and sending the real-time position information and attitude information to the edge computer unit; the optical positioning ball is used for collecting real-time position information and attitude information of the unmanned vehicle moving unit; the data acquisition unit is used for acquiring magnetic field data and inertial information of the unmanned vehicle moving unit in a target magnetic field scene with millimeter-level precision. The invention further provides a data acquisition method of the system. According to the invention, magnetic field data can be accurately acquired, and millimeter-level magnetic field data acquisition is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of magnetic field data acquisition, in particular to a movable magnetic field data acquisition system and a data acquisition method thereof. BACKGROUND

[0002] Magnetic field data acquisition can be used to draw a magnetic field map, therefore, the accuracy of magnetic field data acquisition has a great influence on the drawing accuracy of the magnetic field map. Traditional magnetic field data acquisition mainly relies on handheld magnetometers or fixed sensor networks, which has problems of low efficiency, limited coverage, insufficient spatial resolution, etc., resulting in long data acquisition period, difficulty in realizing large-scale high-density magnetic field distribution measurement, difficulty in synchronously acquiring magnetic field data and accurate spatial position information, and inability to establish a high-precision magnetic field-space mapping relationship.

[0003] Some existing magnetic field data acquisition methods use movable trolleys to collect magnetic field data, for example, a Chinese patent application for invention with publication number CN105547301A discloses an indoor map construction method and device based on geomagnetism. The device is installed with a device for collecting magnetic field data on a movable vehicle, and needs to record the position data of the vehicle, and draws a magnetic map according to the detected magnetic field data and position data. However, the above-mentioned scheme is mainly based on indoor map construction of geomagnetism, and uses a mobile robot to collect geomagnetic sequences along a preset path, and generates a map in combination with a geometric topology graph, but the positioning relies on an electronic compass and a gyroscope. Since the existing magnetic field data acquisition method has the problem of low accuracy due to the influence of magnetic field interference on the electronic compass. SUMMARY

[0004] The first object of the present application is to provide a movable magnetic field data acquisition system with high magnetic field data acquisition accuracy.

[0005] The second object of the present application is to provide a magnetic field data acquisition method for realizing the movable magnetic field data acquisition system.

[0006] To achieve the above-mentioned first object, the movable magnetic field data acquisition system provided by the present application comprises an optical positioning platform and an intelligent unmanned vehicle platform, and the intelligent unmanned vehicle platform has an optical positioning ball, an unmanned vehicle moving unit, an edge computer unit and a data acquisition unit. The optical positioning platform has an infrared camera and an industrial computer, the infrared camera is used to detect real-time position information and attitude information of the unmanned vehicle moving unit, the industrial computer is used to store the real-time position information and attitude information of the unmanned vehicle moving unit, and send the real-time position information and attitude information to the edge computer unit; the optical positioning ball is used to collect real-time position information and attitude information of the unmanned vehicle moving unit; and the data acquisition unit is used to collect magnetic field data and inertial information of the target magnetic field scene of the unmanned vehicle moving unit at millimeter level accuracy.

[0007] From the above scheme, the application can obtain accurate position information of the intelligent unmanned vehicle platform by combining the optical positioning platform and the intelligent unmanned vehicle platform, improve the positioning accuracy of the magnetic field sensor, and obtain an accurate scalar magnetic field map. In addition, the application can obtain accurate attitude information of the intelligent unmanned vehicle platform, improve the vector magnetic field data accuracy of the magnetic field sensor through coordinate system conversion, and obtain an accurate vector magnetic field map.

[0008] A preferred scheme is that the edge computer unit is used to analyze and store the magnetic field sensor data and inertial sensor data from the data acquisition unit, and analyze and store the real-time position information and attitude information from the optical positioning platform, and plan the travel trajectory of the unmanned vehicle moving unit.

[0009] A further scheme is that the unmanned vehicle moving unit has a single-chip microcomputer, a motor driver, a direct current motor and an encoder; the single-chip microcomputer receives the command sent by the edge computer unit and sends the command to the motor driver, and the motor driver drives the direct current motor to work; the encoder is used to feed back the rotation speed and rotation information of the direct current motor to the single-chip microcomputer in real time.

[0010] A further scheme is that a Mecanum wheel is installed on the unmanned vehicle moving unit, and the direct current motor drives the Mecanum wheel to rotate.

[0011] Since the Mecanum wheel can realize the rotation of the unmanned vehicle moving unit in place, it can realize the steering of the unmanned vehicle moving unit in a very narrow space, and improve the accuracy of magnetic field data acquisition.

[0012] A further scheme is that the number of Mecanum wheels is four, and the number of direct current motors is equal to the number of Mecanum wheels, and one direct current motor drives one Mecanum wheel to rotate.

[0013] A further scheme is that the data acquisition unit has a magnetic field sensor, an accelerometer and an angular velocity meter; the magnetic field sensor is used to collect magnetic field data in a target magnetic field scene; the accelerometer is used to measure and collect data of the linear motion state of the intelligent unmanned vehicle platform in real time; and the angular velocity meter is used to monitor and collect data of the rotation motion state of the intelligent unmanned vehicle platform in real time.

[0014] A further scheme is that the number of infrared cameras is four or more, and the number of optical positioning balls is three or more, and the plurality of infrared cameras monitor the positions of the plurality of optical positioning balls integrated on the intelligent unmanned vehicle platform in sequence.

[0015] To achieve the above-mentioned second purpose, the data acquisition method of the movable magnetic field data acquisition system provided by the application comprises: using an infrared camera to detect real-time position information and attitude information of the unmanned vehicle moving unit and storing them in an industrial computer, and sending the real-time position information and attitude information to an edge computer unit; using an optical positioning ball to collect real-time position information and attitude information of the unmanned vehicle moving unit; using a data acquisition unit to collect magnetic field data and inertial information of the target magnetic field scene of the unmanned vehicle moving unit at millimeter level precision; analyzing and storing the magnetic field sensor data and inertial sensor data from the data acquisition unit by the edge computer unit, and analyzing and storing the real-time position information and attitude information from the optical positioning platform to plan the travel trajectory of the unmanned vehicle moving unit.

[0016] A preferred scheme is that when planning the travel trajectory of the unmanned vehicle moving unit, target trajectory parameters for trajectory planning are obtained, and the target trajectory parameters include a measurement range, a measurement line interval, a measurement direction and a moving speed.

[0017] A further scheme is that after obtaining the target trajectory parameters for trajectory planning, a plurality of target points of the unmanned vehicle moving unit are calculated, the speed is calculated in combination with the plurality of target points and the real-time position information and attitude information to obtain the travel direction and distance of the unmanned vehicle moving unit in a global coordinate system; the global coordinate system speed and the target points are converted into the speed and target points of the coordinate system of the unmanned vehicle moving unit through a coordinate system conversion algorithm; the vector trajectory speed and attitude data of the unmanned vehicle moving unit are obtained in combination with the moving speed, the speed of the unmanned vehicle moving unit and the target points through a vector normalization algorithm, and are stored in the edge computer unit. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is a structural block diagram of an embodiment of the movable magnetic field data acquisition system of the application.

[0019] Figure 2 is a flow block diagram of an embodiment of the data acquisition method of the movable magnetic field data acquisition system of the application.

[0020] The application will be further described below in combination with the drawings and embodiments. DETAILED DESCRIPTION

[0021] The movable magnetic field data acquisition system of the application has an intelligent unmanned vehicle platform, and the data acquisition unit is carried by the unmanned vehicle moving unit to realize the collection of magnetic field data in a specific space.

[0022] Embodiment of the movable magnetic field data acquisition system: Referring to Figure 1The movable magnetic field data acquisition system of the embodiment includes an optical positioning platform 10 and an intelligent unmanned vehicle platform 20. The optical positioning platform 10 is provided with an infrared camera 11 and an industrial computer 12. The intelligent unmanned vehicle platform 20 includes an optical positioning ball 21, an edge computer unit 22, an unmanned vehicle moving unit 30, and a data acquisition unit 40. The unmanned vehicle moving unit 30 includes a single-chip microcomputer 31, a motor driver 32, an encoder 33, a direct current motor 34, and a Mecanum wheel 35. The data acquisition unit 40 includes a magnetic field sensor 41, an accelerometer 42, and an angular velocity meter 43.

[0023] In the embodiment, the optical positioning platform 10 is provided with 26 infrared cameras 11 and one industrial computer 12. The 26 infrared cameras 11 monitor the positions of the five optical positioning balls 21 integrated on the intelligent unmanned vehicle platform 20 in sequence, so as to determine the real-time position information and attitude information of the unmanned vehicle moving platform 30. In actual application, the number of infrared cameras needs to be more than four, and the number of optical positioning balls needs to be more than three. The industrial computer 21 is used to receive and store the position information and attitude information from all the infrared cameras 11, and publish the received position information and attitude information to the edge computer unit 22 through a VRPN interface.

[0024] The intelligent unmanned vehicle platform 20 is provided with one unmanned vehicle moving unit 30, five optical positioning balls 21, one edge computer unit 22, and one data acquisition unit 40. The data acquisition unit 40 is used to acquire data information in the environment, and transmit the acquired data information to the edge computer unit 22. The edge computer unit 22 combines the information of the unmanned vehicle moving unit 30 from the optical positioning platform 10 and the information acquired by the data acquisition unit 40, and transmits a control instruction to the unmanned vehicle moving unit 30. The optical positioning ball 21 is carried on the unmanned vehicle moving unit 30, moves with the movement of the unmanned vehicle moving unit 30, and is used to acquire real-time position information and attitude information of the unmanned vehicle moving unit 30.

[0025] The unmanned vehicle moving unit 30 includes one single-chip microcomputer 31, two motor drivers 32, four encoders 33, four direct current motors 34 and four Mecanum wheels 35. The single-chip microcomputer 31 is configured to receive the control instructions sent by the edge computer unit 22 and transmit the control instructions to the motor drivers 32. The motor drivers 32 receive the instructions from the single-chip microcomputer 31 and send control signals to the direct current motors 34. In the embodiment, the number of the direct current motors 34 is equal to the number of the Mecanum wheels 35, and each direct current motor 34 controls the rotation of one Mecanum wheel 35. When the direct current motor 34 receives the control signal, the corresponding Mecanum wheel 35 rotates according to the received control signal, thereby realizing the movement of the unmanned vehicle moving unit 30. The direct current motor 34 also transmits the control instructions to the encoder 33, and the encoder 33 transmits the received data to the single-chip microcomputer 31, thereby realizing the closed-loop stable control of the unmanned vehicle moving unit 30.

[0026] The data acquisition unit 40 is configured to acquire the magnetic field data and inertial information of the unmanned vehicle moving unit 30 in the target magnetic field scene with millimeter-level precision. The data acquisition unit 40 includes one magnetic field sensor 41, one accelerometer 42 and one angular velocity sensor 43. The magnetic field sensor 41 is configured to acquire the surrounding magnetic field data in the environment and transmit the magnetic field data to the edge computer unit 22, that is, to acquire the magnetic field data in the target magnetic field scene. The accelerometer 42 is configured to acquire the acceleration information of the unmanned vehicle moving unit 30 and transmit the acceleration information to the edge computer unit 22, that is, to acquire the data of the linear motion state of the intelligent unmanned vehicle platform 20. The angular velocity sensor 43 is configured to acquire the angular velocity information of the unmanned vehicle moving unit 30 and transmit the angular velocity information to the edge computer unit 22, that is, to monitor and acquire the data of the rotational motion state of the intelligent unmanned vehicle platform 20 in real time.

[0027] The edge computer unit 22 is configured to receive the data transmitted by the optical positioning platform 10 and the data acquisition unit 40 and transmit the generated control instructions to the unmanned vehicle moving unit 30 for controlling the movement of the unmanned vehicle moving unit 30. Specifically, the edge computer unit 22 is configured to analyze and store the magnetic field sensor data and inertial sensor data from the data acquisition unit 40 and analyze and store the real-time position information and attitude information from the optical positioning platform 10, thereby planning the travel trajectory of the unmanned vehicle moving unit 30.

[0028] The movable magnetic field data acquisition system not only integrates the above-mentioned hardware, but also includes software modules running on the hardware. Referring to Figure 2The software module includes a data analysis module 54, a VRPN analysis module 52, a data recording module 53, a trajectory planning module 51 and a motion execution module 55. Among them, the data analysis module 54 stores magnetic field data, accelerometer data and angular velocity data, and is provided with a data frame matching algorithm for transmitting the magnetic field data, accelerometer data and angular velocity data to the data recording module 53 after data frame matching; the VRPN analysis module 52 stores position information and attitude information, and is provided with a data frame matching algorithm; the data recording module 53 is provided with a periodic sampling algorithm, a data filtering algorithm and a data storage algorithm; the trajectory planning module 51 stores target trajectory parameters, and is provided with a target point calculation algorithm, a speed calculation algorithm, a coordinate system conversion algorithm and a vector normalization algorithm; wherein the target trajectory parameters include measurement range, measurement vector, measurement interval, measurement direction and movement rate. The motion execution module 55 is provided with an adaptive speed constraint algorithm, a PID control algorithm, a control output algorithm and a speed measurement algorithm.

[0029] The embodiment realizes real-time collection of magnetic field data in a target scene with millimeter-level precision, and dynamically constructs a millimeter-level precision magnetic field-space correlation database by deeply integrating magnetic field data collection work with high-precision motion control. In this way, the reliability and accuracy of the collected magnetic field data can be improved, and various target magnetic field application scenarios can be adapted according to specific needs.

[0030] The embodiment realizes high-precision collection of magnetic field data by sequentially connecting the unmanned vehicle moving unit 30, the edge computer unit 22, the data collection unit 40, the optical positioning platform 10, the data analysis module 55, the VRPN analysis module 52, the data recording module 53, the trajectory planning module 51 and the motion execution module 55.

[0031] Specifically, the data acquisition unit 40 transmits the collected magnetic field data and inertial data such as accelerometer data and gyroscope data to the data analysis module 54 for data analysis; the optical positioning platform 10 collects the real-time position information and attitude information of the unmanned vehicle moving unit 30 and transmits them to the VRPN analysis module 52 for data analysis; the data analysis module 54 and the VRPN analysis module 52 transmit the analyzed position information and attitude information of the unmanned vehicle moving unit 30, magnetic field data and inertial data to the data recording module 52, and store them in the edge computer unit 22. The trajectory planning module 51 combines the target trajectory input data and the real position and attitude information of the unmanned vehicle moving unit 30 transmitted by the VRPN analysis module 52 in the edge computer unit 22 to obtain the vector velocity to be executed by the unmanned vehicle moving unit 30; the motion execution module 55 transmits the vector velocity execution instruction from the edge computer unit 22 to the unmanned vehicle moving unit 30; the motion execution module 55 also receives data from the encoder 33 of the unmanned vehicle moving unit 30 to realize closed-loop feedback control.

[0032] The VRPN analysis module 52 stores position information and attitude information, and the data matching algorithm can match the position information and attitude information after data frame matching and transmit them to the data recording module 53 and the trajectory planning module 51.

[0033] The data recording module 53 is provided with a periodic sampling algorithm, a data filtering algorithm and a data storage algorithm. The data sampling algorithm periodically samples the magnetic field data, accelerometer data, gyroscope data, position information and attitude information from the data analysis module 51 and the VRPN analysis module 52 at a frequency of 100Hz to avoid data pressure and feature loss caused by unlimited sampling and sparse sampling; the data filtering algorithm performs Gaussian filtering on the sampled magnetic field data to suppress noise and interference and improve the reliability and effectiveness of the data; the data storage algorithm stores the filtered data in the edge computer unit 22 to realize the extraction of the magnetic field data and the storage of the position information and attitude information of the unmanned vehicle moving unit 30, which is convenient for calling at any time.

[0034] The trajectory planning module 51 stores target trajectory parameters and is provided with a target point calculation algorithm, a speed calculation algorithm, a coordinate system conversion algorithm and a vector normalization algorithm. The target trajectory parameters include a measurement range of magnetic field data, a survey line interval, a measurement direction and a moving speed of the unmanned vehicle moving unit 30, etc. The above parameters can be input by a human being. The target point calculation algorithm calculates target point data of the unmanned vehicle moving unit 30 according to the input measurement range, survey line interval and measurement direction. The speed calculation algorithm performs target speed calculation according to the target point data, real position information and attitude information of the unmanned vehicle moving unit 30 output by the VRPN analysis module 52. The coordinate system conversion algorithm realizes conversion of global coordinate system speed and position into coordinate system speed and position of the unmanned vehicle moving unit 30 according to the target speed data and the real position information and attitude information of the unmanned vehicle moving unit 30 output by the VRPN analysis module 52. The vector normalization algorithm normalizes the input moving speed and the coordinate system speed of the unmanned vehicle moving unit 30 to obtain a vector speed, which is transmitted to the edge computer unit 22.

[0035] The motion execution module 55 is provided with an adaptive speed constraint algorithm, a PID control algorithm, a control output and a speed measurement algorithm. The adaptive speed constraint algorithm performs adaptive planning on the target speed, attitude information and target point information from the trajectory planning module and transmits them to the PID control algorithm. The PID control algorithm realizes stable movement of the unmanned vehicle moving unit 30 according to the vector speed transmitted by the edge computer unit 22. The control output algorithm realizes movement control of the unmanned vehicle moving unit 30 according to the control instruction output by the PID control algorithm. The speed measurement algorithm obtains the actual moving speed of the unmanned vehicle moving unit 30 through physical mapping of the encoder data from the unmanned vehicle moving unit 30 and inputs it to the PID control algorithm to realize closed-loop feedback control.

[0036] The data acquisition method of the movable magnetic field data acquisition system embodiment is as follows: The following introduces the above-described movable magnetic field data acquisition system to collect magnetic field data. First, target trajectory parameter input in the motion planning module is performed, parameters such as the magnetic field measurement range, measurement line interval, measurement direction, and the moving speed of the unmanned vehicle moving unit are input in an artificial input manner, and the target point data of the unmanned vehicle moving unit is calculated according to the input measurement range, measurement line interval, and measurement direction. The target speed is calculated according to the target point data obtained by the above calculation, the real position information and attitude information of the unmanned vehicle moving unit of the VRPN analysis module; and the global coordinate system speed and position are converted into the coordinate system speed and position of the unmanned vehicle moving unit according to the target speed data, the real position information and attitude information of the unmanned vehicle moving unit of the VRPN analysis module. Then, the input moving speed and the coordinate system speed of the unmanned vehicle moving unit are normalized by the vector normalization algorithm to obtain the vector speed, which is transmitted to the edge computer unit.

[0037] The edge computer unit transmits the vector speed instruction to the motion execution module, which constrains the vector speed and position through an adaptive constraint algorithm and then transmits the instruction to the PID control algorithm. The PID control algorithm also receives the encoder data from the speed measurement algorithm of the unmanned vehicle moving unit in real time to realize feedback loop. The instruction after completing the PID control algorithm is transmitted to the control output algorithm and finally to the unmanned vehicle moving unit to realize the movement of the unmanned vehicle moving unit.

[0038] While the unmanned vehicle moving unit is moving, the optical positioning ball carried on the unmanned vehicle moving unit is also moving, and the infrared camera on the optical positioning platform captures the position information and pose information of the optical positioning ball and transmits them to the industrial computer. The industrial computer on the optical positioning platform publishes the position information and pose information through the VRPN interface and sends them to the VRPN analysis module.

[0039] While the unmanned vehicle moving unit is moving, the data acquisition unit integrated on the unmanned vehicle moving unit is also moving. The magnetic field sensor in the data acquisition unit collects magnetic field data, the accelerometer and the angular velocity meter collect accelerometer data and angular velocity meter data respectively, and the three kinds of data are transmitted to the data analysis module.

[0040] The VRPN analysis module receives the position information and pose information from the industrial computer and performs data frame matching calculation. The real-time data of the unmanned vehicle moving unit after data frame matching is transmitted to the data recording module and the trajectory planning module, and the trajectory planning module realizes real-time acquisition of environmental information for dynamic path planning and adjustment through target point calculation, current position information, and attitude information.

[0041] The data analysis module receives real-time magnetic field data and inertial data from the data acquisition unit, and performs a data frame matching algorithm.

[0042] The data recording module receives data from the data analysis module and the VRPN analysis module, and performs periodic sampling and data storage operations within the same time stamp.

[0043] It can be seen that the application can solve the problems of heavy workload and low measurement accuracy of traditional indoor magnetic field map measurement, and can obtain accurate position information by combining an optical positioning platform, improve the positioning accuracy of the magnetic field sensor, and thus obtain an accurate scalar magnetic field map.

[0044] In addition, the application can obtain accurate attitude information by combining an optical positioning platform, improve the accuracy of the vector magnetic field data of the magnetic field sensor through coordinate system conversion, and obtain an accurate vector magnetic field map.

[0045] Finally, it should be emphasized that the above is only a preferred embodiment of the application and is not intended to limit the application. For those skilled in the art, the application can have various changes and modifications, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the application shall be included in the protection scope of the application.

Claims

1. A portable magnetic field data acquisition system, characterized in that, It includes an optical positioning platform and an intelligent unmanned vehicle platform, wherein the intelligent unmanned vehicle platform has an optical positioning sphere, an unmanned vehicle mobile unit, an edge computing unit, and a data acquisition unit: The optical positioning platform has an infrared camera and an industrial control computer. The infrared camera is used to detect the real-time position information and attitude information of the unmanned vehicle mobile unit. The industrial control computer is used to store the real-time position information and attitude information of the unmanned vehicle mobile unit and send the real-time position information and attitude information to the edge computer unit. The optical positioning ball is used to collect the real-time position and attitude information of the unmanned vehicle's mobile unit; The data acquisition unit is used to collect magnetic field data and inertial information of the unmanned vehicle mobile unit in a target magnetic field scenario with millimeter-level precision.

2. The portable magnetic field data acquisition system according to claim 1, characterized in that: The edge computing unit is used to parse and store magnetic field sensor data and inertial sensor data from the data acquisition unit, and to parse and store real-time position information and attitude information from the optical positioning platform, and to plan the travel trajectory of the unmanned vehicle mobile unit.

3. The portable magnetic field data acquisition system according to claim 1 or 2, characterized in that: The unmanned vehicle mobile unit includes a microcontroller, a motor driver, a DC motor, and an encoder; The microcontroller receives commands from the edge computing unit and sends commands to the motor driver, which in turn drives the DC motor to operate. The encoder is used to provide real-time feedback of the DC motor's speed and rotation information to the microcontroller.

4. The portable magnetic field data acquisition system according to claim 3, characterized in that: The unmanned vehicle mobile unit is equipped with Mecanum wheels, and the DC motor drives the Mecanum wheels to rotate.

5. The portable magnetic field data acquisition system according to claim 4, characterized in that: The number of Mecanum wheels is four, and the number of DC motors is equal to the number of Mecanum wheels, with one DC motor driving one Mecanum wheel to rotate.

6. The portable magnetic field data acquisition system according to claim 1 or 2, characterized in that: The data acquisition unit includes a magnetic field sensor, an accelerometer, and an angular velocity meter; The magnetic field sensor is used to collect magnetic field data in the target magnetic field scene; The accelerometer is used to measure and collect data on the linear motion state of the intelligent unmanned vehicle platform in real time; The angular velocity meter is used to monitor and collect data on the rotational motion state of the intelligent unmanned vehicle platform in real time.

7. The portable magnetic field data acquisition system according to claim 1 or 2, characterized in that: The number of infrared cameras is four or more, and the number of optical positioning balls is three or more. The multiple infrared cameras monitor the positions of the multiple optical positioning balls integrated on the intelligent unmanned vehicle platform in sequence.

8. The data acquisition method of the portable magnetic field data acquisition system as described in any one of claims 2 to 7, characterized in that, include: The infrared camera is used to detect the real-time position and attitude information of the unmanned vehicle's mobile unit and store it in the industrial control computer, and then the real-time position and attitude information are sent to the edge computer unit. The optical positioning ball is used to collect the real-time position and attitude information of the unmanned vehicle's mobile unit; The data acquisition unit is used to collect magnetic field data and inertial information of the unmanned vehicle mobile unit in a target magnetic field scene with millimeter-level precision; The edge computing unit parses and stores the magnetic field sensor data and inertial sensor data from the data acquisition unit, and parses and stores the real-time position information and attitude information from the optical positioning platform to plan the travel trajectory of the unmanned vehicle mobile unit.

9. The data acquisition method of the portable magnetic field data acquisition system according to claim 8, characterized in that: When planning the travel trajectory of the unmanned vehicle mobile unit, the target trajectory parameters for trajectory planning are obtained. The target trajectory parameters include the measurement range, the measurement line interval, the measurement direction, and the movement speed.

10. The data acquisition method of the portable magnetic field data acquisition system according to claim 9, characterized in that: After obtaining the target trajectory parameters for trajectory planning, multiple target points of the unmanned vehicle mobile unit are calculated. The speed is calculated by combining the multiple target points with the real-time position information and attitude information, and the travel direction and distance of the unmanned vehicle mobile unit in the global coordinate system are obtained. The global coordinate system velocity and the target point are converted into the velocity and target point of the unmanned vehicle mobile unit's coordinate system through a coordinate system transformation algorithm. The vector trajectory speed and attitude data of the unmanned vehicle mobile unit are obtained by combining the movement rate, the speed of the unmanned vehicle mobile unit and the target point through a vector normalization algorithm, and stored in the edge computer unit.

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