A geological structure mapping method and system

Abstract

The present invention relates to the technical field of geological structure surveying and mapping, and specifically to a geological structure surveying and mapping method and system. In the system, a grid task package dynamic allocation module dynamically allocates grid task packages corresponding to each slave drone based on the real-time status data of the slave drones bound to the master drone. The present invention employs a surveying and mapping approach that combines a master drone with multiple slave drones (the slave drones are equipped with sensors). During the surveying and mapping process, the method not only considers the impact of surveying difficulty caused by geological differences at different locations within the surveying and mapping area on the division of the drone surveying and mapping area, but also derives adaptive grid partitioning of the surveying and mapping area based on geological risk parameters. Furthermore, the method also considers the coordination of multiple drones, enabling task migration of pending grid task packages for slave drones with abnormal operating states and dynamic coordination of grid task packages among the slave drones, thereby ensuring surveying accuracy and efficiency for the surveying and mapping area.

Description

Technical Field

[0001] The present invention relates to the technical field of geological structure mapping, and in particular to a geological structure mapping method and system. Background Art

[0002] Geological structural mapping is a fundamental and critical task in geological exploration, mineral resource assessment, engineering construction (such as tunnel, bridge, dam, and nuclear power plant site selection), geological hazard assessment and prevention (such as landslides, earthquakes, and ground subsidence), hydrogeological surveys, and environmental geology assessments. Accurately acquiring information on the distribution, structure (such as faults and folds), lithology, and physical properties of underground rock strata is crucial for scientific decision-making, engineering safety, efficient resource utilization, and disaster warning.

[0003] Existing geological structure surveying and mapping systems usually use manual or drilling methods to collect geological structures in the surveying area; this method is time-consuming and labor-intensive; and with the development of drone technology, the method of using drones equipped with sensors to survey the surveying area has gradually become popular. However, the coordination problem of multiple drones in the surveying process has not been effectively solved, and the impact of the surveying difficulty caused by geological differences at different locations in the surveying area on the division of drone mapping areas is not considered in the surveying process. At the same time, the impact of areas with low 4G / 5G base station coverage on the return of drone mapping data is not considered; therefore, the existing technology has major defects. Summary of the Invention

[0004] The purpose of the present invention is to provide a geological structure mapping method and system to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a geological structure mapping method, the method comprising the following steps:

[0006] S1. Receive, through the master control drone, the boundary coordinates of the surveying and mapping area and the geological risk parameters of each surface coordinate point in the surveying and mapping area that were most recently obtained in historical data, and generate adaptive grid partitions based on the geological risk parameters;

[0007] S2. Dynamically assign grid task packages to each slave drone based on the real-time status data of the slave drone bound to the master drone.

[0008] S3. Each slave UAV synchronously executes partition mapping according to preset acquisition parameters, and completes the grid task package of the corresponding slave UAV in sequence. When a slave UAV is in an abnormal working state, the grid task package to be executed by the slave UAV with the abnormal working state is migrated and dynamically coordinated to the grid task package of the remaining slave UAVs. During the partition mapping process, a data transmission link corresponding to the current time is established based on the position coordinates between the slave UAV and the master UAV. The mapping data of the slave UAV is transmitted back to the master UAV in real time through the established data transmission link.

[0009] S4: The master drone performs spatiotemporal alignment on the surveying and mapping data sent back by the slave drones, packages the resulting data, and transmits it back to the cloud via 5G communication to assist the cloud in building a geological structure model of the surveying and mapping area.

[0010] In the process of the master-controlled drone of the present invention transmitting the packaged data back to the cloud through 5G communication, if the master-controlled drone is located within the coverage of the 5G base station around the surveying and mapping area when allocating grid task packages and receiving data transmitted back by the slave drones, the packaged data will be directly transmitted back to the cloud through 5G communication; if the master-controlled drone is not located within the coverage of the 5G base station around the surveying and mapping area when allocating grid task packages and receiving data transmitted back by the slave drones, the master-controlled drone will save the packaged data, and after the master-controlled drone completes the surveying and mapping task of the surveying and mapping area and moves to the 5G communication coverage area, the master-controlled drone will transmit the packaged data back to the cloud through 5G communication.

[0011] Furthermore, the master drone receives the surface coordinates within the surveying area in the WGS84 coordinate system, and the axis corresponding to the first element of the coordinate point in the WGS84 coordinate system is recorded as the X axis, the axis corresponding to the second element of the coordinate point in the WGS84 coordinate system is recorded as the Y axis, and the axis corresponding to the third element of the coordinate point in the WGS84 coordinate system is recorded as the Z axis;

[0012] The geological risk parameters include the slope corresponding to each surface coordinate point, the InSAR deformation rate, and the drilling behavior state; the drilling behavior state includes a drilling behavior state and a non-drilling behavior state; the slope corresponding to the surface coordinate point position is obtained by calling the digital elevation model DEM calculation;

[0013] The method of generating adaptive grid partitions according to geological risk parameters in step S1 comprises the following steps:

[0014] S11. Generate a uniform initial grid based on the circumscribed rectangle of the survey area. The side length of the initial grid is denoted as SL.

[0015] ,

[0016] Among them, SLmin represents the minimum grid side length threshold preset in the database; β represents the weight coefficient; L represents the maximum side length of the circumscribed rectangle of the surveying area; N represents the number of slave drones;

[0017] S12. Calculate the encryption weight coefficient of each grid, and record the encryption weight coefficient of the i-th grid as W i ;

[0018] ,

[0019] Among them, R i represents the InSAR deformation rate corresponding to the i-th grid center point; SP i Indicates the arc corresponding to the average slope value of each surface coordinate point in the i-th grid; B i represents the number of drill holes corresponding to the i-th grid; r1, r2 and r3 represent the first normalization coefficient, the second normalization coefficient and the third normalization coefficient respectively;

[0020] S13, query the first constraint weight coefficient and the second constraint weight coefficient preset in the database, and use W i Comparing with the first constraint weight coefficient and the second constraint weight coefficient respectively, and the first constraint weight coefficient is greater than the second constraint weight coefficient;

[0021] When W i Greater than or equal to the first constraint weight coefficient and the minimum edge length in the i-th grid is greater than or equal to 2 SL min When , the encryption operation is performed on the i-th grid, half of the minimum side length of the i-th grid is used as the new grid side length to evenly divide the i-th grid, the new grid is used to replace the original i-th grid, and jump to S12;

[0022] When W i When the encryption weight coefficient of the grid adjacent to the i-th grid is less than the second constraint weight coefficient and the corresponding encryption weight coefficient of the grid adjacent to the i-th grid is also less than the second constraint weight coefficient, the i-th grid and the adjacent grids whose corresponding encryption weight coefficients are less than the second constraint weight coefficient are merged into a new grid, and the newly obtained grid replaces the grids before the merger, and jumps to S12;

[0023] Otherwise, the i-th grid remains unchanged;

[0024] S14. Summarize the areas corresponding to the grids that cannot continue to perform grid encryption and grid merging operations to obtain adaptive grid partitions.

[0025] The present invention performs adaptive grid partitioning, which takes into account the differences in surveying difficulty at different locations within the surveying area, and performs encryption and merging operations on the grid to facilitate the reasonable division of the grid task packages corresponding to each slave UAV in the subsequent process.

[0026] Furthermore, in the process of dynamically allocating the grid task package corresponding to each slave UAV, the adaptive grid partition is dynamically divided into each slave UAV according to the allocation method of allocating each grid to one slave UAV, and a grid task package planning scheme is constructed, and each grid task package planning scheme includes all grids in the adaptive grid partition;

[0027] Calculate the predicted value of surveying and mapping acquisition time corresponding to each grid task package planning scheme. The calculation formula involved is as follows: ,

[0028] Among them, T k→sum represents the predicted value of surveying and mapping acquisition time corresponding to the k-th grid task package planning scheme;

[0029] N represents the number of slave drones;

[0030] represents the maximum value function;

[0031] T （k，j） It represents the predicted value of the operation time required for the j-th slave UAV to complete the grid area mapping task assigned in the k-th grid task package planning scheme; ,

[0032] The encryption weight coefficient corresponding to the d-th grid area assigned to the j-th slave UAV in the k-th grid task package planning scheme is recorded as W （j，k，d） PR （j，k，d） PR represents the area corresponding to the dth grid area assigned to the kth grid task package planning scheme completed by the jth slave UAV; （j，k，KJ） V represents the area corresponding to the KJ-th grid area assigned by the j-th slave UAV to complete the k-th grid task package planning scheme; （j，k，d） Indicates that the corresponding encryption weight coefficient of the jth slave UAV in the historical data is PR （j，k，d） The average surveying speed of each grid area; V （j，k，KJ） Indicates that the corresponding encryption weight coefficient of the jth slave UAV in the historical data is PR （j，k，KJ） The average surveying speed of each grid area; TY （j，k，d）represents the quotient of the shortest distance between the dth grid area and the d+1th grid area assigned to the jth slave UAV in the kth grid task package planning scheme divided by the preset movement speed of the jth slave UAV; KJ represents the number of grid areas assigned to the jth slave UAV in the kth grid task package planning scheme;

[0033] The grid task package planning scheme with the smallest corresponding mapping acquisition time prediction value is taken as the optimal grid task package planning scheme; the grid summary set divided by each slave UAV in the optimal grid task package planning scheme is the grid task package of the corresponding slave UAV.

[0034] Furthermore, when the working state of the slave UAV is abnormal, S3 migrates the grid task package to be executed by the slave UAV with abnormal working state, and dynamically coordinates it to the grid task packages of other slave UAVs. In the process, the grid task package to be executed by the slave UAV with abnormal working state is obtained, which is recorded as the task package to be coordinated. The slave UAV task packages of the adjacent grids of each grid area in the task package to be coordinated are obtained respectively, and the set consisting of all slave UAVs with grids adjacent to the e-th grid area in the task package to be coordinated in the corresponding grid task package is used as the collaborative object set corresponding to the e-th grid area in the task package to be coordinated; each grid in the task package to be coordinated is inserted into the back end of the adjacent grid in the grid task package of any slave UAV in the corresponding collaborative object set to obtain different task migration schemes, and the task migration scheme with the smallest difference between the maximum and minimum values ​​of the predicted operating time required for the grid area mapping task assigned to each slave UAV in the planning schemes of each grid task package after task migration is used as the optimal task migration scheme, and the update of the corresponding grid task package of the slave UAV is executed according to the optimal task migration scheme.

[0035] Furthermore, the method of constructing the data transmission link corresponding to the current time in S3 includes the following steps:

[0036] S31. Using the master drone as the data receiving terminal node, all slave drones within the area with the master drone as the center and within the effective communication signal reception radius are marked as first-level transfer nodes, and each first-level transfer node is topologically connected to the master drone. The effective communication signal reception radius is a constant preset in the database.

[0037] S32. Obtain the level of the currently marked transfer node, denoted as b, and denote any currently marked b-level transfer node as DSb; all unmarked slave drones within the area with DSb as the center point and the effective communication signal reception radius are used as the next-level transfer nodes of DSb, and all the next-level transfer nodes of DSb are marked and each next-level transfer node of DSb is topologically connected to DSb respectively; until there are no unmarked slave drones within the area with the effective communication signal reception radius of each currently marked transfer node or all slave drones are marked;

[0038] S33, obtaining different data receiving topology schemes with the master control drone as the data receiving terminal node; using the data receiving topology scheme corresponding to the union of the lines between the transfer nodes in each data receiving topology scheme as the data transmission link corresponding to the current time;

[0039] The transmission data received by each transfer node from the remaining transfer nodes includes the distance and position direction of each transfer node among the remaining transfer nodes based on the corresponding transfer node of the received data, the surveying and mapping data corresponding to each transfer node among the remaining transfer nodes at the corresponding position, the corresponding surveying and mapping data acquisition time, and the multi-hop relay return data received by each transfer node among the remaining transfer nodes; the multi-hop relay return data received by each transfer node includes the surveying and mapping data to be returned, and the sum of the position vectors corresponding to the transfer nodes passed through each time in the process of the corresponding surveying and mapping data being returned from the surveying point to the corresponding transfer node; the modulus of the position vector corresponding to the transfer node passed through each time is equal to the distance between the position of the transfer node of the return data and the position of the transfer node receiving the corresponding return data; the vector direction of the position vector corresponding to the transfer node passed through each time is equal to the direction from the position of the transfer node of the return data to the position of the transfer node receiving the corresponding return data.

[0040] Based on the corresponding position coordinates of the corresponding transfer nodes receiving the data, the present invention can accurately calculate the specific position coordinates of each transfer node that transmits data to the transfer node receiving the data, bind the surveying and mapping data corresponding to each transfer node at the corresponding position with the corresponding position coordinates, and obtain the spatiotemporal alignment results of the surveying and mapping data.

[0041] Furthermore, in the process of the S4 master UAV performing spatiotemporal alignment on the surveying and mapping data sent back by the slave UAV, the coordinates of the surveying and mapping points corresponding to each surveying and mapping data are calculated based on the data transmission link corresponding to the current time; each surveying and mapping data is respectively bound to the coordinates of the surveying and mapping points corresponding to the corresponding surveying and mapping data and the corresponding surveying and mapping data acquisition time, to obtain the spatiotemporal alignment result of the surveying and mapping data sent back by the master UAV to the slave UAV.

[0042] A geological structure mapping system, comprising an adaptive grid partitioning module, a grid task package dynamic allocation module, a task coordination and transmission module, and a mapping data return control module;

[0043] The adaptive grid partitioning module receives the boundary coordinates of the surveying area and the geological risk parameters of each surface coordinate point in the surveying area obtained most recently in historical data through the master control drone, and generates adaptive grid partitions according to the geological risk parameters;

[0044] The grid task package dynamic allocation module dynamically allocates the grid task package corresponding to each slave drone according to the real-time status data of the slave drone bound to the master drone;

[0045] The task coordination and transmission module controls each slave UAV to synchronously execute partition mapping according to preset acquisition parameters, and completes the grid task packages of the corresponding slave UAVs in sequence. When the working status of a slave UAV is abnormal, the grid task package to be executed by the slave UAV with abnormal working status is migrated and dynamically coordinated to the grid task packages of the remaining slave UAVs. During the partition mapping process, a data transmission link corresponding to the current time is established based on the position coordinates between the slave UAV and the master UAV, and the mapping data of the slave UAV is transmitted back to the master UAV in real time through the established data transmission link.

[0046] The surveying and mapping data return control module controls the master UAV to perform spatiotemporal alignment on the surveying and mapping data returned by the slave UAV, packages the obtained data, and returns it to the cloud via 5G communication to assist the cloud in building a geological structure model of the surveying and mapping area.

[0047] Furthermore, the task coordination and transmission module includes a grid task execution management unit, a task migration coordination unit and a data transmission link construction unit;

[0048] The grid task execution management unit controls each slave UAV to synchronously perform partition mapping according to preset acquisition parameters, and completes the grid task package of the corresponding slave UAV in sequence;

[0049] When the working state of the slave UAV is abnormal, the task migration coordination unit migrates the grid task package to be executed by the slave UAV with abnormal working state and dynamically coordinates it to the grid task packages of other slave UAVs;

[0050] During the partition mapping process, the data transmission link construction unit constructs a data transmission link corresponding to the current time according to the position coordinates between the slave UAV and the master UAV, and transmits the mapping data of the slave UAV to the master UAV in real time through the constructed data transmission link.

[0051] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention adopts a surveying and mapping method of a master UAV + multiple slave UAVs (slave UAVs equipped with sensors). During the surveying and mapping process, it not only considers the impact of the surveying and mapping difficulty caused by geological differences at different locations in the surveying and mapping area on the division of the UAV surveying and mapping area, but also obtains the adaptive grid partitioning of the surveying and mapping area according to the geological risk parameters; at the same time, it also takes into account the coordination problem of multiple UAVs, realizes the task migration of the grid task packages to be executed by slave UAVs with abnormal working status and the dynamic coordination of the grid task packages of slave UAVs, and ensures the surveying and mapping accuracy and efficiency of the surveying and mapping area; at the same time, the present invention adopts 5G communication + construction of a data transmission link between the master UAV and the slave UAV to realize the spatiotemporal alignment and efficient return of the surveying and mapping data. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0053] Figure 1 It is a structural schematic diagram of a geological structure mapping system of the present invention;

[0054] Figure 2 It is a flow chart of a geological structure mapping method of the present invention. DETAILED DESCRIPTION

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0056] See also Figure 1-Figure 2 , the present invention provides a technical solution: Figure 1 As shown, this embodiment provides a geological structure mapping system, which includes an adaptive grid partitioning module, a grid task package dynamic allocation module, a task coordination and transmission module, and a mapping data return control module;

[0057] The adaptive grid partitioning module receives the boundary coordinates of the surveying area and the geological risk parameters of each surface coordinate point in the surveying area obtained most recently in historical data through the master control drone, and generates adaptive grid partitions according to the geological risk parameters;

[0058] The grid task package dynamic allocation module dynamically allocates the grid task package corresponding to each slave drone according to the real-time status data of the slave drone bound to the master drone;

[0059] The task coordination and transmission module includes a grid task execution management unit, a task migration coordination unit and a data transmission link construction unit;

[0060] The grid task execution management unit controls each slave UAV to synchronously perform partition mapping according to preset acquisition parameters, and completes the grid task package of the corresponding slave UAV in sequence;

[0061] When the working state of the slave UAV is abnormal, the task migration coordination unit migrates the grid task package to be executed by the slave UAV with abnormal working state and dynamically coordinates it to the grid task packages of other slave UAVs;

[0062] During the partition mapping process, the data transmission link construction unit constructs a data transmission link corresponding to the current time according to the position coordinates between the slave UAV and the master UAV, and transmits the mapping data of the slave UAV to the master UAV in real time through the constructed data transmission link.

[0063] The surveying and mapping data return control module controls the master UAV to perform spatiotemporal alignment on the surveying and mapping data returned by the slave UAV, packages the obtained data, and returns it to the cloud via 5G communication to assist the cloud in building a geological structure model of the surveying and mapping area.

[0064] like Figure 2 As shown, this embodiment provides a geological structure mapping method, which includes the following steps:

[0065] S1. Receive, through the master control drone, the boundary coordinates of the surveying and mapping area and the geological risk parameters of each surface coordinate point in the surveying and mapping area that were most recently obtained in historical data, and generate adaptive grid partitions based on the geological risk parameters;

[0066] The master drone receives the surface coordinates within the surveying area in the WGS84 coordinate system. The axis corresponding to the first element of the coordinate point in the WGS84 coordinate system is recorded as the X axis, the axis corresponding to the second element of the coordinate point in the WGS84 coordinate system is recorded as the Y axis, and the axis corresponding to the third element of the coordinate point in the WGS84 coordinate system is recorded as the Z axis.

[0067] The geological risk parameters include the slope corresponding to each surface coordinate point, the InSAR deformation rate, and the drilling behavior state; the drilling behavior state includes a drilling behavior state and a non-drilling behavior state; the slope corresponding to the surface coordinate point position is obtained by calling the digital elevation model DEM calculation;

[0068] The method of generating adaptive grid partitions according to geological risk parameters in step S1 comprises the following steps:

[0069] S11. Generate a uniform initial grid based on the circumscribed rectangle of the survey area. The side length of the initial grid is denoted as SL. ,

[0070] Among them, SL min represents the minimum grid side length threshold preset in the database; β represents the weight coefficient; L represents the maximum side length of the circumscribed rectangle of the surveying area; N represents the number of slave drones;

[0071] S12. Calculate the encryption weight coefficient of each grid, and record the encryption weight coefficient of the i-th grid as W i ;

[0072] ,

[0073] Among them, R i represents the InSAR deformation rate corresponding to the i-th grid center point; SP i Indicates the arc corresponding to the average slope value of each surface coordinate point in the i-th grid; B i represents the number of drill holes corresponding to the i-th grid; r1, r2 and r3 represent the first normalization coefficient, the second normalization coefficient and the third normalization coefficient respectively;

[0074] S13, query the first constraint weight coefficient and the second constraint weight coefficient preset in the database, and use W i Comparing with the first constraint weight coefficient and the second constraint weight coefficient respectively, and the first constraint weight coefficient is greater than the second constraint weight coefficient;

[0075] When W i Greater than or equal to the first constraint weight coefficient and the minimum edge length in the i-th grid is greater than or equal to 2 SL min When , the encryption operation is performed on the i-th grid, half of the minimum side length of the i-th grid is used as the new grid side length to evenly divide the i-th grid, the new grid is used to replace the original i-th grid, and jump to S12;

[0076] When W i When the encryption weight coefficient of the grid adjacent to the i-th grid is less than the second constraint weight coefficient and the corresponding encryption weight coefficient of the grid adjacent to the i-th grid is also less than the second constraint weight coefficient, the i-th grid and the adjacent grids whose corresponding encryption weight coefficients are less than the second constraint weight coefficient are merged into a new grid, and the newly obtained grid replaces the grids before the merger, and jumps to S12;

[0077] Otherwise, the i-th grid remains unchanged;

[0078] S14. Summarize the areas corresponding to the grids that cannot continue to perform grid encryption and grid merging operations to obtain adaptive grid partitions.

[0079] S2. Dynamically assign grid task packages to each slave drone based on the real-time status data of the slave drone bound to the master drone.

[0080] In the process of dynamically allocating the grid task package corresponding to each slave UAV, the adaptive grid partition is dynamically divided into each slave UAV according to the allocation method of each grid to a slave UAV, and a grid task package planning scheme is constructed, and each grid task package planning scheme includes all grids in the adaptive grid partition;

[0081] Calculate the predicted value of surveying and mapping acquisition time corresponding to each grid task package planning scheme. The calculation formula involved is as follows: ,

[0082] Among them, T k→sum represents the predicted value of surveying and mapping acquisition time corresponding to the k-th grid task package planning scheme;

[0083] N represents the number of slave drones;

[0084] represents the maximum value function;

[0085] T （k，j） It represents the predicted value of the operation time required for the j-th slave UAV to complete the grid area mapping task assigned in the k-th grid task package planning scheme;

[0086] ,

[0087] The encryption weight coefficient corresponding to the d-th grid area assigned to the j-th slave UAV in the k-th grid task package planning scheme is recorded as W （j，k，d） PR （j，k，d） PR represents the area corresponding to the dth grid area assigned to the kth grid task package planning scheme completed by the jth slave UAV; （j，k，KJ） V represents the area corresponding to the KJ-th grid area assigned by the j-th slave UAV to complete the k-th grid task package planning scheme; （j，k，d） Indicates that the corresponding encryption weight coefficient of the jth slave UAV in the historical data is PR （j，k，d） The average surveying speed of each grid area; V （j，k，KJ） Indicates that the corresponding encryption weight coefficient of the jth slave UAV in the historical data is PR （j，k，KJ） The average surveying speed of each grid area; TY （j，k，d）represents the quotient of the shortest distance between the dth grid area and the d+1th grid area assigned to the jth slave UAV in the kth grid task package planning scheme divided by the preset movement speed of the jth slave UAV; KJ represents the number of grid areas assigned to the jth slave UAV in the kth grid task package planning scheme;

[0088] The grid task package planning scheme with the smallest corresponding mapping acquisition time prediction value is taken as the optimal grid task package planning scheme; the grid summary set divided by each slave UAV in the optimal grid task package planning scheme is the grid task package of the corresponding slave UAV.

[0089] S3. Each slave UAV synchronously executes partition mapping according to preset acquisition parameters, and completes the grid task package of the corresponding slave UAV in sequence. When a slave UAV is in an abnormal working state, the grid task package to be executed by the slave UAV with the abnormal working state is migrated and dynamically coordinated to the grid task package of the remaining slave UAVs. During the partition mapping process, a data transmission link corresponding to the current time is established based on the position coordinates between the slave UAV and the master UAV. The mapping data of the slave UAV is transmitted back to the master UAV in real time through the established data transmission link.

[0090] When the working state of the slave UAV is abnormal, the S3 migrates the grid task package to be executed by the slave UAV with abnormal working state, and dynamically coordinates it with the grid task packages of other slave UAVs. The grid task package to be executed by the slave UAV with abnormal working state is obtained, recorded as the task package to be coordinated, and the slave UAV task packages belonging to the adjacent grids of each grid area in the task package to be coordinated are obtained respectively. The set consisting of all slave UAVs with grids adjacent to the e-th grid area in the task package to be coordinated in the corresponding grid task package is used as the collaborative object set corresponding to the e-th grid area in the task package to be coordinated; each grid in the task package to be coordinated is inserted into the back end of the adjacent grid in the grid task package of any slave UAV in the corresponding collaborative object set to obtain different task migration schemes, and the task migration scheme with the smallest difference between the maximum and minimum values ​​of the predicted operating time required for the grid area mapping task assigned to each slave UAV in the planning schemes of each grid task package after task migration is used as the optimal task migration scheme, and the update of the corresponding grid task package of the slave UAV is executed according to the optimal task migration scheme.

[0091] The method S3 for constructing a data transmission link corresponding to the current time includes the following steps:

[0092] S31. Using the master drone as the data receiving terminal node, all slave drones within the area with the master drone as the center and within the effective communication signal reception radius are marked as first-level transfer nodes, and each first-level transfer node is topologically connected to the master drone. The effective communication signal reception radius is a constant preset in the database.

[0093] S32. Obtain the level of the currently marked transfer node, denoted as b, and denote any currently marked b-level transfer node as DSb; all unmarked slave drones within the area with DSb as the center point and the effective communication signal reception radius are used as the next-level transfer nodes of DSb, and all the next-level transfer nodes of DSb are marked and each next-level transfer node of DSb is topologically connected to DSb respectively; until there are no unmarked slave drones within the area with the effective communication signal reception radius of each currently marked transfer node or all slave drones are marked;

[0094] S33, obtaining different data receiving topology schemes with the master control drone as the data receiving terminal node; using the data receiving topology scheme corresponding to the union of the lines between the transfer nodes in each data receiving topology scheme as the data transmission link corresponding to the current time;

[0095] The transmission data received by each transfer node from the remaining transfer nodes includes the distance and position direction of each transfer node among the remaining transfer nodes based on the corresponding transfer node of the received data, the surveying and mapping data corresponding to each transfer node among the remaining transfer nodes at the corresponding position, the corresponding surveying and mapping data acquisition time, and the multi-hop relay return data received by each transfer node among the remaining transfer nodes; the multi-hop relay return data received by each transfer node includes the surveying and mapping data to be returned, and the sum of the position vectors corresponding to the transfer nodes passed through each time in the process of the corresponding surveying and mapping data being returned from the surveying point to the corresponding transfer node; the modulus of the position vector corresponding to the transfer node passed through each time is equal to the distance between the position of the transfer node of the return data and the position of the transfer node receiving the corresponding return data; the vector direction of the position vector corresponding to the transfer node passed through each time is equal to the direction from the position of the transfer node of the return data to the position of the transfer node receiving the corresponding return data.

[0096] In this embodiment, the distance and position direction of each of the remaining transit nodes based on the corresponding transit node receiving the data are obtained in order to calculate the relative position vector of the remaining transit nodes relative to the corresponding transit node receiving the data when transmitting data, wherein the distance of each of the remaining transit nodes based on the corresponding transit node receiving the data corresponds to the module length in the relative position vector of the remaining transit nodes relative to the corresponding transit node receiving the data when transmitting data, and the corresponding position direction corresponds to the vector direction of the corresponding position vector; based on the corresponding position coordinates of the corresponding transit node receiving the data, the specific position coordinates of each transit node transmitting data to the transit node receiving the data can be accurately calculated, and the surveying and mapping data corresponding to each transit node at the corresponding position is bound to the corresponding position coordinates, so as to obtain the spatiotemporal alignment result of the surveying and mapping data.

[0097] S4: The master drone performs spatiotemporal alignment on the surveying and mapping data sent back by the slave drones, packages the resulting data, and transmits it back to the cloud via 5G communication to assist the cloud in building a geological structure model of the surveying and mapping area.

[0098] During the process of the S4 master UAV performing spatiotemporal alignment on the surveying and mapping data sent back by the slave UAV, the coordinates of the surveying and mapping points corresponding to each surveying and mapping data are calculated based on the data transmission link corresponding to the current time; each surveying and mapping data is respectively bound to the coordinates of the surveying and mapping points corresponding to the corresponding surveying and mapping data and the corresponding surveying and mapping data acquisition time, to obtain the spatiotemporal alignment result of the surveying and mapping data sent back by the master UAV to the slave UAV.

[0099] In this embodiment, if the master drone is located within the coverage of the 5G base station around the surveying and mapping area when allocating grid task packages and receiving data returned by the slave drones, the master drone will directly transmit the packaged data back to the cloud via 5G communication; if the master drone is not located within the coverage of the 5G base station around the surveying and mapping area when allocating grid task packages and receiving data returned by the slave drones, the master drone will save the packaged data, and after the master drone completes the surveying and mapping task of the surveying and mapping area and moves to the 5G communication coverage area, the master drone will then transmit the packaged data back to the cloud via 5G communication.

[0100] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0101] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A geological structure mapping method, characterized in that: The method comprises the following steps: S1. Receive, through the master control drone, the boundary coordinates of the surveying and mapping area and the geological risk parameters of each surface coordinate point in the surveying and mapping area that were most recently obtained in historical data, and generate adaptive grid partitions based on the geological risk parameters; The master drone receives the surface coordinates within the surveying area in the WGS84 coordinate system. The axis corresponding to the first element of the coordinate point in the WGS84 coordinate system is recorded as the X axis, the axis corresponding to the second element of the coordinate point in the WGS84 coordinate system is recorded as the Y axis, and the axis corresponding to the third element of the coordinate point in the WGS84 coordinate system is recorded as the Z axis. The geological risk parameters include the slope corresponding to each surface coordinate point, the InSAR deformation rate, and the drilling behavior state; the drilling behavior state includes a drilling behavior state and a non-drilling behavior state; the slope corresponding to the surface coordinate point position is obtained by calling the digital elevation model DEM calculation; The method of generating adaptive grid partitions according to geological risk parameters in step S1 comprises the following steps: S11. Generate a uniform initial grid based on the circumscribed rectangle of the survey area. The side length of the initial grid is denoted as SL. ， Among them, SL min represents the minimum grid side length threshold preset in the database; β represents the weight coefficient; L represents the maximum side length of the circumscribed rectangle of the surveying area; N represents the number of slave drones; S12. Calculate the encryption weight coefficient of each grid, and record the encryption weight coefficient of the i-th grid as W i ; ， Among them, R i represents the InSAR deformation rate corresponding to the i-th grid center point; SP i Indicates the arc corresponding to the average slope value of each surface coordinate point in the i-th grid; B i represents the number of drill holes corresponding to the i-th grid; r1, r2 and r3 represent the first normalization coefficient, the second normalization coefficient and the third normalization coefficient respectively; S13, query the first constraint weight coefficient and the second constraint weight coefficient preset in the database, and use W i Comparing with the first constraint weight coefficient and the second constraint weight coefficient respectively, and the first constraint weight coefficient is greater than the second constraint weight coefficient; When W i Greater than or equal to the first constraint weight coefficient and the minimum edge length in the i-th grid is greater than or equal to 2 SL min When , the encryption operation is performed on the i-th grid, half of the minimum side length of the i-th grid is used as the new grid side length to evenly divide the i-th grid, the new grid is used to replace the original i-th grid, and jump to S12; W i When the encryption weight coefficient of the grid adjacent to the i-th grid is less than the second constraint weight coefficient and the corresponding encryption weight coefficient of the grid adjacent to the i-th grid is also less than the second constraint weight coefficient, the i-th grid and the adjacent grids whose corresponding encryption weight coefficients are less than the second constraint weight coefficient are merged into a new grid, and the newly obtained grid replaces the grids before the merger, and jumps to S12; Otherwise, the i-th grid remains unchanged; S14, summarizing the areas corresponding to the grids that cannot continue to perform grid refinement and grid merging operations to obtain adaptive grid partitions; S2. Dynamically assign grid task packages to each slave drone based on the real-time status data of the slave drone bound to the master drone. S3. Each slave UAV synchronously executes partition mapping according to preset acquisition parameters, and completes the grid task package of the corresponding slave UAV in sequence. When a slave UAV is in an abnormal working state, the grid task package to be executed by the slave UAV with the abnormal working state is migrated and dynamically coordinated to the grid task package of the remaining slave UAVs. During the partition mapping process, a data transmission link corresponding to the current time is established based on the position coordinates between the slave UAV and the master UAV. The mapping data of the slave UAV is transmitted back to the master UAV in real time through the established data transmission link. S4. The master drone performs spatiotemporal alignment on the surveying and mapping data sent back by the slave drones, packages the obtained data, and transmits it back to the cloud via 5G communication to assist the cloud in building a geological structure model of the surveying and mapping area.

2. A geological structure mapping method according to claim 1, characterized in that: In the process of dynamically allocating the grid task package corresponding to each slave UAV, the adaptive grid partition is dynamically divided into each slave UAV according to the allocation method of each grid to a slave UAV, and a grid task package planning scheme is constructed, and each grid task package planning scheme includes all grids in the adaptive grid partition; Calculate the predicted value of surveying and mapping acquisition time corresponding to each grid task package planning scheme. The calculation formula involved is as follows: , Among them, T k→sum represents the predicted value of surveying and mapping acquisition time corresponding to the k-th grid task package planning scheme; N represents the number of slave drones; represents the maximum value function; T （k，j） It represents the predicted value of the operation time required for the j-th slave UAV to complete the grid area mapping task assigned in the k-th grid task package planning scheme; ， The encryption weight coefficient corresponding to the d-th grid area assigned to the j-th slave UAV in the k-th grid task package planning scheme is recorded as W （j，k，d） PR （j，k，d） PR represents the area corresponding to the dth grid area assigned to the kth grid task package planning scheme completed by the jth slave UAV; （j，k，KJ） V represents the area corresponding to the KJ-th grid area assigned by the j-th slave UAV to complete the k-th grid task package planning scheme; （j，k，d） Indicates that the corresponding encryption weight coefficient of the jth slave UAV in the historical data is PR （j，k，d） The average surveying speed of each grid area; V （j，k，KJ） Indicates that the corresponding encryption weight coefficient of the jth slave UAV in the historical data is PR （j，k，KJ） The average surveying speed of each grid area; TY （j，k，d） represents the quotient of the shortest distance between the dth grid area and the d+1th grid area assigned to the jth slave UAV in the kth grid task package planning scheme divided by the preset movement speed of the jth slave UAV; KJ represents the number of grid areas assigned to the jth slave UAV in the kth grid task package planning scheme; The grid task package planning scheme with the smallest corresponding mapping acquisition time prediction value is taken as the optimal grid task package planning scheme; the grid summary set divided by each slave UAV in the optimal grid task package planning scheme is the grid task package of the corresponding slave UAV.

3. A geological structure mapping method according to claim 1, characterized in that: When the working state of the slave UAV is abnormal, the S3 migrates the grid task package to be executed by the slave UAV with abnormal working state, and dynamically coordinates it with the grid task packages of other slave UAVs. The grid task package to be executed by the slave UAV with abnormal working state is obtained, recorded as the task package to be coordinated, and the slave UAV task packages belonging to the adjacent grids of each grid area in the task package to be coordinated are obtained respectively. The set consisting of all slave UAVs with grids adjacent to the e-th grid area in the task package to be coordinated in the corresponding grid task package is used as the collaborative object set corresponding to the e-th grid area in the task package to be coordinated; each grid in the task package to be coordinated is inserted into the back end of the adjacent grid in the grid task package of any slave UAV in the corresponding collaborative object set to obtain different task migration schemes, and the task migration scheme with the smallest difference between the maximum and minimum values ​​of the predicted operating time required for the grid area mapping task assigned to each slave UAV in the planning schemes of each grid task package after task migration is used as the optimal task migration scheme, and the update of the corresponding grid task package of the slave UAV is executed according to the optimal task migration scheme.

4. A geological structure mapping method according to claim 1, characterized in that: The method S3 for constructing a data transmission link corresponding to the current time includes the following steps: S31. Using the master drone as the data receiving terminal node, all slave drones within the area with the master drone as the center and within the effective communication signal reception radius are marked as first-level transfer nodes, and each first-level transfer node is topologically connected to the master drone. The effective communication signal reception radius is a constant preset in the database. S32. Obtain the level of the currently marked transfer node, denoted as b, and denote any currently marked b-level transfer node as DSb; all unmarked slave drones within the area with DSb as the center point and the effective communication signal reception radius are used as the next-level transfer nodes of DSb, and all the next-level transfer nodes of DSb are marked and each next-level transfer node of DSb is topologically connected to DSb respectively; until there are no unmarked slave drones within the area with the effective communication signal reception radius of each currently marked transfer node or all slave drones are marked; S33, obtaining different data receiving topology schemes with the master control drone as the data receiving terminal node; using the data receiving topology scheme corresponding to the union of the lines between the transfer nodes in each data receiving topology scheme as the data transmission link corresponding to the current time; The transmission data received by each transfer node from the remaining transfer nodes includes the distance and position direction of each transfer node among the remaining transfer nodes based on the corresponding transfer node of the received data, the surveying and mapping data corresponding to each transfer node among the remaining transfer nodes at the corresponding position, the corresponding surveying and mapping data acquisition time, and the multi-hop relay return data received by each transfer node among the remaining transfer nodes; the multi-hop relay return data received by each transfer node includes the surveying and mapping data to be returned, and the sum of the position vectors corresponding to the transfer nodes passed through each time in the process of the corresponding surveying and mapping data being returned from the surveying point to the corresponding transfer node; the modulus of the position vector corresponding to the transfer node passed through each time is equal to the distance between the position of the transfer node of the return data and the position of the transfer node receiving the corresponding return data; the vector direction of the position vector corresponding to the transfer node passed through each time is equal to the direction from the position of the transfer node of the return data to the position of the transfer node receiving the corresponding return data.

5. A geological structure mapping method according to claim 1, characterized in that: During the process of the S4 master UAV performing spatiotemporal alignment on the surveying and mapping data sent back by the slave UAV, the coordinates of the surveying and mapping points corresponding to each surveying and mapping data are calculated based on the data transmission link corresponding to the current time; each surveying and mapping data is respectively bound to the coordinates of the surveying and mapping points corresponding to the corresponding surveying and mapping data and the corresponding surveying and mapping data acquisition time, to obtain the spatiotemporal alignment result of the surveying and mapping data sent back by the master UAV to the slave UAV.

6. A geological structure mapping system, applying a geological structure mapping method according to any one of claims 1 to 5, characterized in that: The system includes an adaptive grid partitioning module, a grid task package dynamic allocation module, a task coordination and transmission module, and a surveying and mapping data return control module; The adaptive grid partitioning module receives the boundary coordinates of the surveying area and the geological risk parameters of each surface coordinate point in the surveying area obtained most recently in historical data through the master control drone, and generates adaptive grid partitions according to the geological risk parameters; The grid task package dynamic allocation module dynamically allocates the grid task package corresponding to each slave drone according to the real-time status data of the slave drone bound to the master drone; The task coordination and transmission module controls each slave UAV to synchronously perform partition mapping according to preset acquisition parameters, and completes the grid task package of the corresponding slave UAV in sequence; when the working status of a slave UAV is abnormal, the grid task package to be executed by the slave UAV with abnormal working status is migrated and dynamically coordinated to the grid task package of the remaining slave UAVs; During the partition mapping process, a data transmission link corresponding to the current time is established based on the position coordinates between the slave UAV and the master UAV. The mapping data of the slave UAV is transmitted back to the master UAV in real time through the established data transmission link. The surveying and mapping data return control module controls the master UAV to perform spatiotemporal alignment on the surveying and mapping data returned by the slave UAV, packages the obtained data, and returns it to the cloud via 5G communication to assist the cloud in building a geological structure model of the surveying and mapping area.

7. A geological structure mapping system according to claim 6, characterized in that: The task coordination and transmission module includes a grid task execution management unit, a task migration coordination unit and a data transmission link construction unit; The grid task execution management unit controls each slave UAV to synchronously perform partition mapping according to preset acquisition parameters, and completes the grid task package of the corresponding slave UAV in sequence; When the working state of the slave UAV is abnormal, the task migration coordination unit migrates the grid task package to be executed by the slave UAV with abnormal working state and dynamically coordinates it to the grid task packages of other slave UAVs; During the partition mapping process, the data transmission link construction unit constructs a data transmission link corresponding to the current time according to the position coordinates between the slave UAV and the master UAV, and transmits the mapping data of the slave UAV to the master UAV in real time through the constructed data transmission link.

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