Intelligent positioning and navigation surveying and mapping system based on unmanned driving

Abstract

The invention discloses an intelligent positioning navigation surveying and mapping system based on unmanned driving, which belongs to the technical field of surveying and mapping and comprises a surveying and mapping analysis module, an action module and a surveying and mapping module. The surveying and mapping analysis module is used for analyzing the surveying and mapping area and determining a target surveying and mapping area; the action module is used for determining unmanned equipment according to the target surveying and mapping area, controlling the unmanned equipment to reach the target surveying and mapping area, and performing data acquisition on the target surveying and mapping area through surveying and mapping equipment equipped on the unmanned equipment to obtain corresponding surveying and mapping data; the surveying and mapping module is used for analyzing the surveying and mapping data to obtain check data of the target surveying and mapping area; receiving surveying and mapping data, and performing abnormal surveying and mapping characteristic data processing on the surveying and mapping data to obtain corresponding surveying and mapping standard data; comparing the check data with the surveying and mapping standard data, determining corresponding surveying and mapping update data, and performing security processing on the surveying and mapping update data; and adjusting the check data according to the surveying and mapping update data.

Description

Technical Field

[0001] The present invention belongs to the field of surveying and mapping technology, and in particular to an unmanned intelligent positioning, navigation and surveying system. Background Art

[0002] With the rapid development of science and technology, positioning and navigation technology is increasingly used in the field of surveying and mapping. Traditional surveying and mapping methods usually rely on manual operation and complex equipment, which is not only inefficient, but also easily affected by human factors, resulting in inaccurate surveying and mapping results. In recent years, with the development of high-precision sensor technology, intelligent positioning, navigation and surveying systems have gradually emerged. Existing intelligent positioning, navigation and surveying systems mainly rely on a variety of sensors and positioning technologies to achieve high-precision surveying and mapping. For example, laser radar can obtain terrain information by measuring the distance between the laser beam and the target object; optical cameras and depth cameras can obtain high-resolution image data for identifying and measuring target objects; and global positioning systems (GPS) and inertial navigation systems (INS) can provide accurate navigation and positioning information for unmanned equipment. The common method is to load surveying and mapping equipment on the vehicle and conduct surveying and mapping in the surveying and mapping area by manually driving the vehicle; however, this method has certain limitations. For example, it will be difficult to conduct surveying and mapping in some special areas where vehicles cannot be driven; and the efficiency is low when surveying and mapping updates are required later. Therefore, the development of a more advanced, efficient and stable intelligent positioning, navigation and surveying system still has important practical significance and market demand. Based on this, the present invention provides an intelligent positioning, navigation and mapping system based on unmanned driving. Summary of the invention

[0003] In order to solve the problems existing in the above-mentioned solutions, the present invention provides an intelligent positioning, navigation and mapping system based on unmanned driving.

[0004] The purpose of the present invention can be achieved by the following technical solutions:

[0005] An intelligent positioning, navigation and mapping system based on unmanned driving, including a mapping analysis module, an action module and a mapping module;

[0006] The surveying and mapping analysis module is used to analyze the surveying and mapping area and determine the target surveying and mapping area.

[0007] Furthermore, the method for determining the target surveying and mapping area includes:

[0008] Identify the surveying and mapping area, and obtain the surveying and mapping map corresponding to the surveying and mapping area; obtain the surveying and mapping related data corresponding to each area in the surveying and mapping map in real time, mark each of the surveying and mapping related data in the surveying and mapping map, and form a related data set corresponding to each area;

[0009] According to the surveying and mapping map, the associated data sets corresponding to each area are identified in real time, and the associated data sets are analyzed to determine the target surveying and mapping area.

[0010] Furthermore, the method for obtaining surveying and mapping related data includes:

[0011] Establishing an information retrieval model, performing real-time information retrieval through the information retrieval model, and obtaining regional retrieval information corresponding to the surveying and mapping area;

[0012] The regional retrieval information is evaluated in real time through the preset information evaluation model to obtain the corresponding surveying and mapping related data;

[0013] The expression of the information evaluation model is: Wherein: x is the regional retrieval information; when XL(x)=1, the corresponding regional retrieval information is the surveying and mapping associated data.

[0014] Furthermore, the method for analyzing the associated data set includes:

[0015] Identify each surveying and mapping related data in the related data set, and identify the candidate time and information source corresponding to the surveying and mapping related data;

[0016] Match the corresponding initial trust value according to the information source of each surveying and mapping related data; mark each surveying and mapping related data with the same initial trust value and candidate time as related classification data; determine the corresponding representative trust value and target time according to each related classification data;

[0017] A time evaluation model is established, and the expression of the time evaluation model is: Where: a is the target time;

[0018] Calculate the corresponding surveying and mapping assessment value according to the formula PGL = ST (a) × XW;

[0019] Where: PGL is the surveying and mapping evaluation value; ST(a) is the time evaluation model; a is the target time; XW is the representative trust value;

[0020] The area where the surveying and mapping evaluation value is greater than the threshold X1 is marked as the target surveying and mapping area.

[0021] Furthermore, the method for determining the corresponding representative trust value and target time according to each associated classification data includes:

[0022] Identify the number of mapping related data in the related classification data and mark them as common quantities;

[0023] According to the formula XW = XA × 1.08 LG Calculate the classification trust value corresponding to each associated classification data; where: XW is the classification trust value; XA is the initial trust value; LG is the common number;

[0024] Select the highest classification trust value as the representative trust value, and mark the candidate time corresponding to the representative trust value as the target time.

[0025] The action module is used to determine an unmanned device according to the target survey area, control the unmanned device to reach the target survey area, and collect data of the target survey area through the survey equipment equipped on the unmanned device to obtain corresponding survey data.

[0026] Further, the method for determining the unmanned device includes:

[0027] Establish an equipment information database, which is used to store various unmanned device information and the equipment survey characteristics corresponding to each unmanned device;

[0028] Collect the area information of the target survey area, generate corresponding target area characteristics according to the area information; compare the equipment survey characteristics in the equipment information database according to the obtained target area characteristics to obtain each candidate device that meets the survey requirements;

[0029] Evaluate each candidate device to obtain the applied unmanned device.

[0030] Further, the method for evaluating the candidate device includes:

[0031] Estimate the required time for surveying the target survey area according to the unmanned device information of the candidate device, and mark it as the survey duration; and set the corresponding survey accuracy value according to the unmanned device information of the candidate device, and the value range of the survey accuracy value is [60, 100];

[0032] Compare each pair of candidate devices, and the comparison formula is:

[0033]

[0034] Where: QU1 and QU2 are the comparison values of two compared candidate devices; b1 and b2 are both proportionality coefficients, and the value range is 0 < b1 ≤ 1, 0 < b2 ≤ 1; CL1 and CL2 are the survey durations of two compared candidate devices respectively; CP1 and CP2 are the survey accuracy values of two compared candidate devices respectively;

[0035] Compare QU1 and QU2, and the one with the larger comparison value has a higher priority; retain the candidate device with a higher priority, and eliminate the other compared candidate device, and so on until there is only one candidate device left, and regard the remaining single selected device as the applied unmanned device.

[0036] The surveying and mapping module is used to analyze the surveying and mapping data, and includes a front-end unit and a back-end unit, wherein the front-end unit is arranged on the unmanned driving device; obtains the verification data of the target surveying and mapping area, and stores the verification data in the front-end unit after security processing;

[0037] The front-end unit receives the surveying and mapping data, performs abnormal surveying and mapping feature data processing on the surveying and mapping data, and obtains corresponding surveying and mapping standard data;

[0038] Comparing the verification data with the surveying and mapping standard data, determining corresponding surveying and mapping update data, and performing security processing on the surveying and mapping update data;

[0039] The surveying and mapping update data after security processing is transmitted to the back-end unit according to the preset transmission method, and the back-end unit adjusts the verification data according to the received surveying and mapping update data.

[0040] Furthermore, the method for processing abnormal surveying and mapping feature data of surveying and mapping data includes:

[0041] Abnormal surveying and mapping feature data are defined, and a corresponding abnormal surveying and mapping recognition model is established according to the defined abnormal surveying and mapping feature data. The surveying and mapping data are analyzed by the abnormal surveying and mapping recognition model to identify each abnormal surveying and mapping feature data, and the identified abnormal surveying and mapping feature data are removed from the surveying and mapping data.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] Through the cooperation between the mapping analysis module, action module and mapping module, intelligent positioning, navigation and mapping based on unmanned driving is realized; it can complete mapping tasks autonomously without human intervention, greatly improving work efficiency; it can adapt to different environments and application scenarios, such as land, water, air, etc., and has a wide range of applicability; and it can accurately locate detailed mapping update data, perform corresponding security processing, and avoid data leakage. Through the setting of the mapping analysis module, intelligent analysis of the mapping area is realized, and which areas are the target mapping areas are automatically determined, which greatly reduces the manual burden. At the same time, it has extremely high positioning efficiency, which is convenient for timely updating of mapping information and ensuring the accuracy of positioning and navigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0046] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] like Figure 1 As shown, the unmanned intelligent positioning, navigation and mapping system includes a mapping analysis module, an action module and a mapping module;

[0048] The surveying and mapping analysis module is used to determine the target surveying and mapping area, and the process is as follows:

[0049] Identify the surveying and mapping area, the surveying and mapping area such as a city, town, custom marked area, etc., which needs to be positioned, navigated and mapped; that is, an overall area; the target surveying and mapping area is the area marked in the surveying and mapping area that needs to be surveyed this time; the present invention is mainly aimed at the subsequent update and maintenance after the overall surveying and mapping of the surveying and mapping area has been carried out, but it can also be applied to the early overall surveying, directly marking the surveying and mapping area as the target surveying and mapping area, and then conducting a comprehensive survey, which is not described in detail in the present invention; it is mainly aimed at the implementation example of the subsequent update and maintenance after the overall surveying and mapping of the surveying and mapping area.

[0050] An information retrieval model is established. The information retrieval model is used to retrieve various relevant data within the surveying and mapping area. It is established using existing retrieval technology. The main retrieval direction is whether there are changes in surveying and mapping information within the surveying and mapping area, such as buildings, roads and other related information. Therefore, corresponding retrieval keywords will be set according to surveying and mapping needs to narrow the retrieval scope and improve retrieval efficiency. Real-time information retrieval is performed through the information retrieval model to obtain corresponding regional retrieval information.

[0051] A large amount of retrieval simulation information is simulated and set. The retrieval simulation information is the regional retrieval information set in the simulation. The corresponding information evaluation model is established according to the retrieval simulation information. The retrieval simulation information that meets the requirements of surveying and mapping changes is regarded as abnormal data, and other data is regarded as normal data. Therefore, the information evaluation model is established based on the existing isolation forest algorithm, and the expression is: Where: x is the input data, that is, the regional retrieval information.

[0052] Through the information evaluation model, the regional retrieval information is evaluated in real time to obtain the corresponding abnormal data, and the abnormal data is marked as surveying and mapping related data; the location area corresponding to the surveying and mapping related data is identified; the surveying and mapping map of the surveying and mapping area is obtained, and the corresponding surveying and mapping related data is marked in the surveying and mapping map according to the location area corresponding to the surveying and mapping related data, so as to form the related data sets corresponding to each area; generally, codes and other related features are used to represent it, and the corresponding access links are associated; the corresponding marking method is set according to the actual needs.

[0053] According to the surveying and mapping map, the associated data sets corresponding to each area are identified in real time, and the associated data sets are analyzed to determine whether the area needs to be updated for surveying and mapping. If it is determined that a surveying and mapping update is required, the corresponding area is marked as the target surveying and mapping area; otherwise, no corresponding operation is performed.

[0054] The analysis of the associated data set is mainly based on the corresponding time and information credibility; the specific process is as follows:

[0055] Identify each surveying and mapping related data in the related data set, and identify the candidate time and information source corresponding to the surveying and mapping related data; the candidate time is the time of surveying and mapping changes reflected in the surveying and mapping related data, mainly including changes on a certain day in the future, changes that have already been made, etc. If the time is not indicated in the published data, but the construction has already started, it is considered to have been changed;

[0056] The corresponding initial trust value is matched according to the information source of each surveying and mapping related data; that is, the platform party aggregates various possible information sources, such as individuals, platforms, websites, official websites, etc., and the platform party sets corresponding initial trust values ​​for various information sources according to the credibility of various information sources. The value range of the initial trust value is [0, 100];

[0057] Identify each surveying and mapping related data with the same initial trust value and candidate time, mark them as related classification data, identify the number of surveying and mapping related data in the related classification data, and mark them as common number;

[0058] According to the formula XW = XA × 1.08 LG Calculate the classification trust value corresponding to each associated classification data; where: XW is the classification trust value; XA is the initial trust value; LG is the common number;

[0059] The highest classification trust value is selected and marked as the representative trust value, and the candidate time corresponding to the representative trust value is marked as the target time.

[0060] Establish a time evaluation model. The time evaluation model is used to evaluate whether the target time meets the standard for updating the surveying and mapping timing. For example, if the target time changes on a certain day in the future, it has not changed yet and does not need to be updated, which does not meet the standard; the changed time is before the last re-measurement and update, because it has been re-measured and updated, it does not meet the requirements. And so on. According to the evaluation common sense, the time evaluation model is established, and the corresponding time evaluation standard is set manually; the expression is Where: a is the input data, i.e. the target time;

[0061] The corresponding surveying and mapping evaluation value is calculated according to the formula PGL=ST(a)×XW; where: PGL is the surveying and mapping evaluation value; ST(a) is the time evaluation model; a is the target time; XW is the representative trust value, that is, the corresponding classification trust value.

[0062] When the surveying and mapping evaluation value is greater than the threshold value X1, it is determined that a surveying and mapping update is required, that is, the area where the surveying and mapping evaluation value is greater than the threshold value X1 is marked as a target surveying and mapping area; otherwise, no surveying and mapping update is performed.

[0063] Through the setting of the surveying and mapping analysis module, intelligent analysis of the surveying and mapping area can be achieved, and areas that are the target surveying and mapping areas can be automatically determined, which greatly reduces the manual burden. At the same time, it has extremely high positioning efficiency, facilitates timely updating of surveying and mapping information, and ensures the accuracy of positioning and navigation.

[0064] The action module is used to intelligently determine the unmanned driving equipment according to the target surveying and mapping area, and control the unmanned driving equipment to reach the target surveying and mapping area, collect data through the surveying and mapping equipment equipped by the unmanned driving equipment, and obtain corresponding surveying and mapping data.

[0065] Among them, the control of unmanned driving equipment and the data collection of surveying and mapping equipment are all realized by using existing technologies. Unmanned driving equipment includes various equipment such as drones, unmanned vehicles, and unmanned ships.

[0066] Methods for determining unmanned equipment include:

[0067] The platform determines the unmanned driving equipment it has, obtains the information of each unmanned driving equipment, and sets the equipment mapping characteristics of each unmanned driving equipment, such as which mapping environment it is suitable for, mapping accuracy, equipment performance and other relevant data; after making the corresponding summary, establishes the corresponding equipment information library, that is, the equipment information library is used to store various unmanned driving equipment information and corresponding equipment mapping characteristics; the platform establishes, maintains and updates the equipment information library.

[0068] Identify the corresponding regional information of the target survey area, such as data on target information to be surveyed, road conditions, various influencing factors, etc.; specifically, the platform party presets a corresponding data collection template to collect information on the target survey area, and subsequently extracts features according to each collection item in the data collection template to form the target area features corresponding to the target survey area; mainly various data related to the use of unmanned devices; such as whether the surveying ability can meet the surveying requirements and whether the surveying work can be carried out normally;

[0069] Compare the surveying features of each device in the device information library with the obtained target area features to obtain each unmanned device that can meet the surveying requirements, and mark them as candidate devices;

[0070] Evaluate each candidate device to obtain the applied unmanned device.

[0071] Among them, various methods can be used to evaluate each candidate device, such as random assignment, manual assignment, assignment according to a preset schedule, etc. It can also be evaluated in the following way. The method includes:

[0072] Estimate the time required to survey the target survey area based on the unmanned device information corresponding to the candidate device, and mark it as the surveying duration; and set the corresponding surveying accuracy value according to the unmanned device information of the candidate device. The surveying accuracy value is evaluated according to the surveying accuracy of this candidate device and the comprehensiveness of the surveying target; it can be achieved by the platform party summarizing the surveying accuracy values of various unmanned devices for different surveying targets and then performing matching later; it can also be based on neural networks such as CNN network or DNN network to establish a corresponding surveying analysis model, and a corresponding training set is established through artificial means for training. The training set includes input data and output data. The input data includes target area features and unmanned device information, and the output data is the surveying accuracy value. The value range of the surveying accuracy value is [60, 100]; through the trained surveying analysis model for analysis, the corresponding surveying accuracy value is obtained.

[0073] Compare each pair of candidate devices, and retain the candidate device with a higher priority, and eliminate the other compared candidate device. By analogy, until there is only one candidate device left, regard the remaining single selected device as the applied unmanned device.

[0074] The comparison formula is: In the formula: QU1 and QU2 are the comparison values of the two compared candidate devices respectively; b1 and b2 are both proportionality coefficients, and the value range is 0 < b1 ≤ 1, 0 < b2 ≤ 1; CL1 and CL2 are the surveying durations of the two compared candidate devices respectively; CP1 and CP2 are the surveying accuracy values of the two compared candidate devices respectively;

[0075] Compare QU1 and QU2, and the one with the larger comparison value has higher priority.

[0076] The surveying and mapping module is used to analyze the surveying and mapping data, and includes a front-end unit and a back-end unit, wherein the front-end unit is arranged on the unmanned driving device; obtaining the verification data of the target surveying and mapping area, that is, the surveying and mapping data of the current target surveying and mapping area is regarded as the verification data; storing the verification data in the front-end unit after security processing, that is, applying the existing data encryption security measures for processing;

[0077] The front-end unit acquires surveying and mapping data, processes the surveying and mapping data for abnormal surveying and mapping feature data, and obtains corresponding surveying and mapping standard data; that is, the unsurveyed related data is identified and marked, such as the collected data of surrounding pedestrians, passing vehicles, etc., and defined as abnormal surveying and mapping feature data; specifically, a corresponding abnormal surveying and mapping recognition model is established based on the existing technology, so as to facilitate the recognition according to the preset abnormal surveying and mapping feature data, and the recognized abnormal surveying and mapping feature data is eliminated; the common method is to establish an abnormal surveying and mapping recognition model based on a neural network, and other technologies can also be applied to establish it;

[0078] Compare the obtained verification data with the surveying and mapping standard data, determine the corresponding surveying and mapping update data, and perform security processing on the surveying and mapping update data, including data encryption and other measures; because there is only surveying and mapping update data, the amount of data is greatly reduced, which is convenient for encryption processing, and more adaptive methods can be used to delete non-surveying and mapping update data; that is, the above steps are all loaded on the unmanned driving equipment;

[0079] The surveying and mapping update data is transmitted to the back-end unit according to the preset transmission mode, and the back-end unit adjusts the verification data according to the received surveying and mapping update data. The preset transmission mode is set by the platform.

[0080] Among them, the obtained verification data and surveying and mapping standard data are compared, that is, the corresponding data are compared one by one to identify the updated surveying and mapping parts; and extracted as surveying and mapping update data.

[0081] Through the mutual cooperation between the surveying and mapping analysis module, the action module and the surveying and mapping module, intelligent positioning, navigation and surveying based on unmanned driving is realized; it can complete surveying and mapping tasks independently without human intervention, greatly improving work efficiency; it can adapt to different environments and application scenarios, such as land, water, air, etc., and has a wide range of applicability; and it can accurately locate detailed surveying and mapping update data, perform corresponding security processing, and avoid data leakage.

[0082] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0083] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. Unmanned driving-based intelligent positioning, navigation and mapping system, characterized by: It includes surveying and mapping analysis module, action module and surveying and mapping module; The surveying and mapping analysis module is used to analyze the surveying and mapping area and determine the target surveying and mapping area; The action module is used to determine the unmanned driving device according to the target surveying and mapping area, and control the unmanned driving device to reach the target surveying and mapping area, collect data of the target surveying and mapping area through the surveying and mapping equipment equipped by the unmanned driving device, and obtain corresponding surveying and mapping data; The surveying and mapping module is used to analyze the surveying and mapping data, and includes a front-end unit and a back-end unit, wherein the front-end unit is arranged on the unmanned driving device; obtains the verification data of the target surveying and mapping area, and stores the verification data in the front-end unit after security processing; The front-end unit receives the surveying and mapping data, performs abnormal surveying and mapping feature data processing on the surveying and mapping data, and obtains corresponding surveying and mapping standard data; Comparing the verification data with the surveying and mapping standard data, determining corresponding surveying and mapping update data, and performing security processing on the surveying and mapping update data; The surveying and mapping update data after security processing is transmitted to the back-end unit according to the preset transmission method, and the back-end unit adjusts the verification data according to the received surveying and mapping update data.

2. The unmanned intelligent positioning, navigation and mapping system according to claim 1 is characterized in that: Methods for determining the target surveying and mapping area include: Identify the surveying and mapping area, and obtain the surveying and mapping map corresponding to the surveying and mapping area; obtain the surveying and mapping related data corresponding to each area in the surveying and mapping map in real time, mark each of the surveying and mapping related data in the surveying and mapping map, and form a related data set corresponding to each area; According to the surveying and mapping map, the associated data sets corresponding to each area are identified in real time, and the associated data sets are analyzed to determine the target surveying and mapping area.

3. The unmanned intelligent positioning, navigation and mapping system according to claim 2 is characterized in that: Methods for obtaining surveying and mapping related data include: Establishing an information retrieval model, performing real-time information retrieval through the information retrieval model, and obtaining regional retrieval information corresponding to the surveying and mapping area; The regional retrieval information is evaluated in real time through the preset information evaluation model to obtain the corresponding surveying and mapping related data; The expression of the information evaluation model is: Wherein: x is the regional retrieval information; when XL(x)=1, the corresponding regional retrieval information is the surveying and mapping associated data.

4. The unmanned intelligent positioning, navigation and mapping system according to claim 3 is characterized in that: Methods for analyzing linked datasets include: Identify each surveying and mapping related data in the related data set, and identify the candidate time and information source corresponding to the surveying and mapping related data; Match the corresponding initial trust value according to the information source of each surveying and mapping related data; mark each surveying and mapping related data with the same initial trust value and candidate time as related classification data; determine the corresponding representative trust value and target time according to each related classification data; A time evaluation model is established, and the expression of the time evaluation model is: Where: a is the target time; Calculate the corresponding surveying and mapping assessment value according to the formula PGL = ST (a) × XW; Where: PGL is the surveying and mapping evaluation value; ST(a) is the time evaluation model; a is the target time; XW is the representative trust value; The area where the surveying and mapping evaluation value is greater than the threshold X1 is marked as the target surveying and mapping area.

5. The unmanned intelligent positioning, navigation and mapping system according to claim 4 is characterized in that: The method for determining the corresponding representative trust value and target time according to each associated classification data includes: Identify the number of mapping related data in the related classification data and mark them as common quantities; According to the formula XW = XA × 1.08 LG Calculate the classification trust value corresponding to each associated classification data; where: XW is the classification trust value; XA is the initial trust value; LG is the common number; The highest classification trust value is selected and marked as the representative trust value, and the candidate time corresponding to the representative trust value is marked as the target time.

6. The unmanned intelligent positioning, navigation and mapping system according to claim 1, characterized in that: Methods for determining unmanned equipment include: Establishing an equipment information database, wherein the equipment information database is used to store various unmanned driving equipment information and equipment mapping features corresponding to each unmanned driving equipment; Collect the regional information of the target surveying and mapping area, and generate corresponding target area features according to the regional information; compare the device surveying and mapping features in the device information library according to the obtained target area features to obtain each candidate device that meets the surveying and mapping requirements; Evaluate each candidate device to obtain the applied unmanned driving device.

7. The unmanned intelligent positioning, navigation and mapping system according to claim 6, characterized in that: The method for evaluating candidate devices includes: Estimate the required time for surveying and mapping the target surveying and mapping area according to the unmanned driving device information of the candidate device, and mark it as the surveying and mapping duration; and set the corresponding surveying and mapping accuracy value according to the unmanned driving device information of the candidate device, and the value range of the surveying and mapping accuracy value is [60, 100]; Compare each pair of candidate devices, and the comparison formula is: and Where: QU1 and QU2 are the comparison values of two compared candidate devices; b1 and b2 are both proportionality coefficients, and the value range is 0 < b1 ≤ 1, 0 < b2 ≤ 1; CL1 and CL2 are the surveying and mapping durations of two compared candidate devices respectively; CP1 and CP2 are the surveying and mapping accuracy values of two compared candidate devices respectively; Compare QU1 and QU2, and the one with the larger comparison value has a higher priority; retain the candidate device with the higher priority, and eliminate the other compared candidate device, and so on until there is only one candidate device left, and regard the remaining single selected device as the applied unmanned driving device.

8. The unmanned intelligent positioning, navigation and mapping system according to claim 1, characterized in that: The method for processing abnormal surveying and mapping feature data of surveying and mapping data includes: Define abnormal surveying and mapping feature data, establish a corresponding abnormal surveying and mapping recognition model according to the defined abnormal surveying and mapping feature data, analyze the surveying and mapping data through the abnormal surveying and mapping recognition model, identify each abnormal surveying and mapping feature data, and remove the identified abnormal surveying and mapping feature data from the surveying and mapping data.

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