Geological surveying and mapping collaborative operation method and system based on unmanned aerial vehicle

Abstract

The invention relates to the technical field of unmanned aerial vehicle control, and particularly discloses a geological surveying and mapping collaborative operation method and system based on an unmanned aerial vehicle, and the method comprises the following steps: delimiting a grid region, determining a surveying and mapping point, and determining a target unmanned aerial vehicle; acquiring a flight route, and determining a signal transmission score of the target unmanned aerial vehicle i entering a next grid region; determining whether the surveying and mapping point of the next grid region is an abnormal point, and determining a target unmanned aerial vehicle j after the unmanned aerial vehicle i collects geographic surveying and mapping data on the abnormal point; and controlling the movement of the target unmanned aerial vehicle i and the target unmanned aerial vehicle j, and after the movement is finished, transmitting geographic surveying and mapping data to a ground center by the target unmanned aerial vehicle j. According to the invention, the stability of geographic surveying and mapping data transmission is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle control, and in particular to a geological surveying and mapping collaborative operation method and system based on unmanned aerial vehicle. Background Art

[0002] Geological surveying is a scientific work that systematically investigates and records surface and underground geological features through field observation, remote sensing detection and data analysis. In modern geological surveying projects, drones are equipped with high-precision sensors (such as multispectral cameras, lidar, etc.) to quickly obtain three-dimensional surface data and generate geological maps. Through autonomous route planning, low-altitude aerial photography and real-time data transmission, it can efficiently cover complex terrain areas and overcome the limitations of low efficiency and high risk of traditional manual surveying.

[0003] At present, in the technical research of multi-UAV collaborative mapping, the core goal of the path planning algorithm generally focuses on the anti-collision mechanism between aircraft. By introducing methods such as cluster obstacle avoidance models, dynamic priority scheduling, and three-dimensional space trajectory optimization, the collision risk of UAVs in complex airspace is significantly reduced, ensuring the basic operation safety of multi-machine systems in scenarios such as mine monitoring and large-scale terrain scanning.

[0004] However, this design approach, which is dominated by physical security, often overlooks a key constraint: whether the mapping data (such as laser point clouds, hyperspectral images, etc.) collected by drones during collaborative operations can be stably transmitted to ground stations or edge computing nodes. In complex environments such as hills and canyons, the communication link between drones and ground base stations is easily affected by terrain obstruction, atmospheric turbulence or electromagnetic interference, resulting in signal strength fluctuations or even interruptions. For example, when a drone formation performs a landslide monitoring mission, some flight units may completely lose direct communication with the command center due to entering the backslope area, affecting data transmission. Summary of the invention

[0005] The purpose of the present invention is to provide a geological surveying and mapping collaborative operation method based on unmanned aerial vehicles to solve the following technical problems: Design ideas dominated by physical security often overlook a key constraint: whether the mapping data (such as laser point clouds, hyperspectral images, etc.) collected by drones during collaborative operations can be stably transmitted to ground stations or edge computing nodes. In complex environments such as hills and canyons, the communication link between drones and ground base stations is easily affected by terrain obstruction, atmospheric turbulence or electromagnetic interference, resulting in signal strength fluctuations or even interruptions. For example, when a drone formation performs a landslide monitoring mission, some flight units may completely lose direct communication with the command center due to entering the back slope area, affecting data transmission.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A geological surveying and mapping collaborative operation method based on unmanned aerial vehicle comprises the following steps: Divide the area to be surveyed into grids to obtain a number of grid areas, take the center points of the grid areas as survey points, and mark any m drones in the drone hive as target drones, where m is a preset number; Obtain a flight route of a single target UAV, and the target UAV goes to the mapping point along the flight route for geographic mapping; when the target UAV i enters the next grid area a on the corresponding flight route, collect the environmental conditions at the mapping point A corresponding to the grid area a, input the environmental conditions into the pre-trained scoring model to output the signal transmission score; When the signal transmission score is less than a preset signal transmission score threshold, the mapping point A is recorded as an abnormal point. After the target drone i collects geographic mapping data at the abnormal point, the target drone closest to the target drone i is obtained and recorded as the target drone j. Obtain the distance D between the target UAV i and the target UAV j, and control the movement of the target UAV i and the target UAV j according to the distance D. After the movement is completed, the target UAV i transmits the collected geographic mapping data to the target UAV j, and moves from the current position to the next mapping point on the corresponding flight route after the transmission is completed; the target UAV j transmits the received geographic mapping data to the ground center, and moves from the current position to the next mapping point on the corresponding flight route after the transmission is completed.

[0007] As a further solution of the present invention: controlling the movement of the target UAV i and the target UAV j according to the distance D includes: When the distance D≤Dys, the target UAV i and the target UAV j do not move, and Dys represents the preset optimal transmission distance; When the distance D>Dys, the following steps are performed: The route corresponding to the distance D is obtained and recorded as the standard line. The target UAV i is controlled to move along the standard line toward the target UAV j by a target distance d=(D-Dys) / 2; the target UAV j is controlled to move along the standard line toward the target UAV i by a target distance d.

[0008] As a further solution of the present invention: when the target UAV j is at an abnormal point, the target UAV j transmits the received geographic mapping data of the target UAV i to the remaining target UAVs, and the remaining target UAVs transmit it to the ground center.

[0009] As a further solution of the present invention: the process of obtaining the pre-trained scoring model includes: Establishing a data set, wherein the data set stores environmental conditions with labeled signal transmission scores; A scoring model is established based on deep learning, and the scoring model is trained and verified based on the data set to obtain a pre-trained scoring model.

[0010] As a further solution of the present invention: the process of obtaining the quantity m includes: Setting the objective function ,y k represents the target value. When the kth UAV is the target UAV, y k =1, K represents the total number of drones in the drone hive; when the kth drone is not the target drone, y k =0; The objective function is solved by integer linear programming in combination with preset constraints to obtain the quantity m.

[0011] As a further solution of the present invention: the constraints specifically include: A single surveying point is visited by the target UAV at least once; A single target drone only departs from the drone hive once, and a single target drone must return to the drone hive once; The distance that a single UAV takes from the UAV hive to the UAV hive is recorded as the target distance. The single target distance is less than 0.8L, and the target distance corresponds to only one route. L represents the maximum cruising range of the UAV.

[0012] As a further solution of the present invention: marking the route corresponding to the target distance as the corresponding flight route of the target UAV.

[0013] A geological surveying and mapping collaborative operation system based on unmanned aerial vehicles, comprising: Task allocation module: divide the area to be surveyed into grids to obtain several grid areas, take the center point of the grid area as the survey point, and mark any m drones in the drone hive as target drones, where m is a preset number; Initial control module: obtain the flight route of a single target UAV, and the target UAV goes to the mapping point along the flight route for geographic mapping; when the target UAV i enters the next grid area a on the corresponding flight route, collect the environmental conditions at the mapping point A corresponding to the grid area a, input the environmental conditions into the pre-trained scoring model to output the signal transmission score; Selection module: when the signal transmission score is less than a preset signal transmission score threshold, the mapping point A is recorded as an abnormal point, and when the target drone i collects geographic mapping data at the abnormal point, the target drone closest to the target drone i is obtained and recorded as target drone j; Control optimization module: obtain the distance D between the target drone i and the target drone j, control the movement of the target drone i and the target drone j according to the distance D, and after the movement is completed, the target drone i transmits the collected geographic mapping data to the target drone j, and moves from the current position to the next mapping point on the corresponding flight route after the transmission is completed; the target drone j transmits the received geographic mapping data to the ground center, and moves from the current position to the next mapping point on the corresponding flight route after the transmission is completed.

[0014] The beneficial effects of the present invention are as follows: 1) The present invention introduces a signal transmission scoring mechanism into the surveying and mapping tasks, so that the UAV can dynamically evaluate the communication environment and autonomously plan collaborative transmission paths when entering different grid areas, thereby effectively reducing the risk of communication interruption caused by terrain obstruction or electromagnetic interference. Compared with traditional solutions that only focus on obstacle avoidance and flight safety, the present invention significantly enhances the data return stability of multi-UAV systems in complex terrains, and can still maintain a high communication quality in environments such as hills and canyons, avoiding the loss of surveying and mapping information or excessive delays, and providing reliable support for subsequent data analysis and disaster warning. Especially in scenarios that require continuous observation, such as landslide monitoring and open-pit mining surveys, data transmission is completed by autonomously selecting the optimal node, which greatly reduces the number of repeated flights or supplementary surveys caused by unstable communication links, fundamentally improving the overall efficiency and accuracy of surveying and mapping tasks.

[0015] 2) The present invention adopts an abnormal point management strategy. When a drone is at a surveying point where the signal is extremely weak or cannot communicate directly with the ground station, it can quickly find a suitable assisting target based on the real-time distance and communication score of the neighboring drones to achieve secondary transmission of key data. This method not only ensures the accuracy of surveying and mapping, but also provides a new type of protection for information security and integrity: even in complex environments such as back slopes, high altitudes or tunnels, the observation data can be delivered to the ground center as soon as possible through the collaborative relay of other flight platforms to avoid information retention or loss. This multi-drone dynamic networking mode not only significantly improves the system's resilience in extreme scenarios, but also builds a highly fault-tolerant and highly flexible communication system for geological surveying and mapping, so that the surveying and mapping process remains controllable in a changing environment; 3) The present invention incorporates the optimal transmission distance and dynamic scheduling strategy between target UAVs into path planning. After completing the sampling point mapping, each UAV can quickly forward the data to the nearest valid node and flexibly adjust its own route to reduce the invalid flight distance. This not only achieves the dual insurance of anti-collision and data transmission security, but also effectively balances the energy consumption of the UAV, allowing the system to still have a high level of mission continuity capability in complex terrain. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention will be further described below in conjunction with the accompanying drawings.

[0017] Figure 1 It is a flow chart of a geological surveying and mapping collaborative operation method based on unmanned aerial vehicle of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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.

[0019] See also Figure 1 As shown, the present invention is a geological surveying and mapping collaborative operation method based on an unmanned aerial vehicle, comprising the following steps: Divide the area to be surveyed into grids to obtain a number of grid areas, take the center points of the grid areas as survey points, and mark any m drones in the drone hive as target drones, where m is a preset number; It can be understood that according to the geographical boundaries and mission requirements, the target area is divided into regular or irregular grids. By determining the appropriate grid side length, the entire area can be cut into a number of equidistant or approximately equidistant grid units under the premise of taking into account both surveying accuracy and flight efficiency; then, for each grid unit, the center point is calculated according to its four vertex coordinates or longitude and latitude information, and the center point is regarded as the surveying point that needs to be visited and observed by the drone. In this way, it can not only ensure the coverage of key terrain features, but also make the subsequent route planning more concise and easy; In a preferred embodiment of the present invention, the process of obtaining the quantity m includes: Setting the objective function ,y k represents the target value. When the kth UAV is the target UAV, y k =1, K represents the total number of drones in the drone hive; when the kth drone is not the target drone, y k =0; Solving the objective function by integer linear programming combined with preset constraints to obtain the quantity m; In a preferred embodiment of this embodiment, the constraint conditions specifically include: A single surveying point is visited by the target UAV at least once; A single target drone only departs from the drone hive once, and a single target drone must return to the drone hive once; The distance that a single UAV takes from the UAV hive to the UAV hive is recorded as the target distance. The single target distance is less than 0.8L, and the target distance corresponds to only one route. L represents the maximum cruising range of the UAV. It should be noted that in order to meet the needs of surveying and mapping tasks while taking into account flight safety and resource efficiency, we introduced several key constraints. The first is the coverage constraint, which ensures that each monitoring point can be visited by at least one drone. This is particularly critical in applications such as geological disaster monitoring or open-pit mine surveys, and can avoid any blind spots in the area. When the number of drones is limited and the monitoring points are widely distributed, the coverage constraint can guide the planning algorithm to give priority to an efficient access sequence, which helps to improve the overall patrol efficiency. The second is that all target drones must depart from the same base station or airport and eventually return, which is not only convenient for unified management and scheduling, but also makes subsequent decision-making measures (such as detecting the remaining fuel and power storage status of drones or executing additional loads) more direct. The third is the cruising range constraint. By limiting the total length of the flight route to less than 0.8L, it can effectively prevent the drone from running out of energy midway during long-distance or high-intensity tasks. The target distance corresponds to only one route to avoid the situation where the drone "forms a circle on the way" but fails to complete the visit of the established monitoring points, eliminating potential independent small loops to ensure that only one connected loop is formed throughout the whole process. Combined with these constraints, the integer linear programming algorithm will automatically optimize the assignment method and route allocation of drones, and select the solution that best meets the mission requirements from the feasible solution set, so that m can meet the surveying and mapping coverage and endurance safety while also taking into account the effective utilization of resources, thereby improving the overall efficiency of multi-drone collaborative operations; Obtain a flight route of a single target UAV, and the target UAV goes to the mapping point along the flight route for geographic mapping; when the target UAV i enters the next grid area a on the corresponding flight route, collect the environmental conditions at the mapping point A corresponding to the grid area a, input the environmental conditions into the pre-trained scoring model to output the signal transmission score; It is worth noting that the route corresponding to the target distance is marked as the corresponding flight route of the target UAV; It should be noted that each target drone is first assigned a unique flight route, which is determined based on the constraint that "the target distance corresponds to only one route". For example, when the drone is numbered i, its corresponding flight route R is uniquely marked to ensure that the drone starts from the hive, passes through all survey points in sequence, and finally returns to the hive. During the execution process, drone i strictly flies along route R. When it reaches each pre-set grid area (such as area a), the system automatically starts the sensor to collect the environmental conditions of the central survey point A in the area, such as temperature, humidity, terrain undulations and obstacle information. Subsequently, these collected data will be transmitted in real time to a pre-trained signal transmission scoring model, which outputs a signal transmission score based on the input environmental conditions to evaluate the stability and effectiveness of the current data transmission. Since the flight route R is fixed and unique, drone i can accurately visit each grid center one by one according to the planned route to avoid duplication or omission, thereby achieving seamless coverage of the entire area. This method not only clarifies the specific path that each drone needs to take, but also predicts possible communication obstacles in advance through real-time environmental data collection and scoring, thereby improving the accuracy, safety and efficiency of the overall surveying and mapping operation; In another preferred embodiment of the present invention, the process of obtaining the pre-trained scoring model includes: Establishing a data set, wherein the data set stores environmental conditions with labeled signal transmission scores; Establishing a scoring model based on deep learning, and training and verifying the scoring model based on the data set to obtain a pre-trained scoring model; When the signal transmission score is less than a preset signal transmission score threshold, the mapping point A is recorded as an abnormal point. After the target drone i collects geographic mapping data at the abnormal point, the target drone closest to the target drone i is obtained and recorded as the target drone j. It is understandable that when it is detected that the environmental conditions corresponding to a certain mapping point A cause the signal transmission score to be lower than the preset threshold, the mapping point will be automatically marked as an abnormal point, so as to timely identify areas with poor communication environment and prevent data loss or delay when directly transmitting data to the ground center in these areas, thereby affecting the timeliness and accuracy of the overall mapping task. For example, in complex terrain such as mountains or canyons, due to terrain obstruction or electromagnetic interference, drones may face weak signals in some areas. At this time, if the collected data is directly transmitted, it is likely that it will not be able to reach the ground station due to signal interruption; therefore, at the abnormal point, drone i will automatically search and obtain the target drone closest to it after completing the geographic mapping data collection, and record the drone as the target drone j. In this way, the data can be first transmitted to drone j, which is closer and has a better signal environment, and then drone j will forward it later to reliably deliver the data to the ground center. Through this collaborative operation mode, not only can the communication shortcomings of a single drone caused by environmental factors be effectively compensated, but also the data integrity and transmission stability of the entire operation network can be ensured; Obtaining the distance D between the target drone i and the target drone j, controlling the movement of the target drone i and the target drone j according to the distance D, and after the movement is completed, the target drone i transmits the collected geographic surveying and mapping data to the target drone j, and moves from the current position to the next surveying and mapping point on the corresponding flight route after the transmission is completed; the target drone j transmits the received geographic surveying and mapping data to the ground center, and moves from the current position to the next surveying and mapping point on the corresponding flight route after the transmission is completed; In a preferred embodiment of the present invention, controlling the movement of the target UAV i and the target UAV j according to the distance D includes: When the distance D≤Dys, the target UAV i and the target UAV j do not move, and Dys represents the preset optimal transmission distance; When the distance D>Dys, the following steps are performed: Obtain the route corresponding to the distance D, record it as the standard line, control the target UAV i to move the target distance d=(D-Dys) / 2 along the standard line toward the target UAV j; control the target UAV j to move the target distance d along the standard line toward the target UAV i; It is understandable that when the distance D between the target UAV i and the target UAV j is too large, it may cause the transmission signal to attenuate, or even the risk of interrupting communication due to the long distance. Therefore, an optimal transmission distance Dys is set: when D≤Dys, it indicates that the two UAVs are already in the ideal transmission range, and no movement adjustment is required at this time, which saves energy and ensures the efficiency of data transmission; when D>Dys, action is required. In the scheme, by obtaining the straight standard line corresponding to the actual distance D and calculating the target distance d=(D-Dys) / 2, UAV i and UAV j are commanded to move the same distance d along the standard line toward each other, so that the final distance is shortened to the optimal transmission distance Dys, thereby ensuring that the communication link between the two UAVs is in the best state during data transmission, and the signal attenuation is minimized, thereby improving the reliability and accuracy of data transmission; secondly, by balancing the moving distance of the two UAVs, it avoids excessive power consumption or reduced flight stability due to excessive flight load on one side, and ensures the energy efficiency and mission endurance of the overall system; It is worth noting that when the target UAV j is at an abnormal point, the target UAV j transmits the received geographic mapping data of the target UAV i to the remaining target UAVs, and the remaining target UAVs transmit it to the ground center; It should be noted that the method by which the target drone j transmits the received geographic mapping data of the target drone i to the remaining target drones is the same as the method by which the target drone i transmits the geographic mapping data to the target drone j. First, find the target drone closest to the target drone j, and then execute the subsequent steps, which will not be repeated here.

[0020] A geological surveying and mapping collaborative operation system based on unmanned aerial vehicles, comprising: Task allocation module: divide the area to be surveyed into grids to obtain several grid areas, take the center point of the grid area as the survey point, and mark any m drones in the drone hive as target drones, where m is a preset number; Initial control module: obtain the flight route of a single target UAV, and the target UAV goes to the mapping point along the flight route for geographic mapping; when the target UAV i enters the next grid area a on the corresponding flight route, collect the environmental conditions at the mapping point A corresponding to the grid area a, input the environmental conditions into the pre-trained scoring model to output the signal transmission score; Selection module: when the signal transmission score is less than a preset signal transmission score threshold, the mapping point A is recorded as an abnormal point, and when the target drone i collects geographic mapping data at the abnormal point, the target drone closest to the target drone i is obtained and recorded as target drone j; Control optimization module: obtain the distance D between the target drone i and the target drone j, control the movement of the target drone i and the target drone j according to the distance D, and after the movement is completed, the target drone i transmits the collected geographic mapping data to the target drone j, and moves from the current position to the next mapping point on the corresponding flight route after the transmission is completed; the target drone j transmits the received geographic mapping data to the ground center, and moves from the current position to the next mapping point on the corresponding flight route after the transmission is completed.

[0021] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A geological surveying and mapping collaborative operation method based on unmanned aerial vehicles, characterized in that: The following steps are involved: Divide the area to be surveyed into grids to obtain a number of grid areas, take the center points of the grid areas as survey points, and mark any m drones in the drone hive as target drones, where m is a preset number; Acquire a flight route of a single target UAV, and the target UAV travels along the flight route to the surveying point for geographic surveying; When the target UAV i enters the next grid area a on the corresponding flight route, the environmental conditions on the surveying point A corresponding to the grid area a are collected, and the environmental conditions are input into the pre-trained scoring model to output the signal transmission score; When the signal transmission score is less than a preset signal transmission score threshold, the mapping point A is recorded as an abnormal point. After the target drone i collects geographic mapping data at the abnormal point, the target drone closest to the target drone i is obtained and recorded as the target drone j. Obtain the distance D between the target UAV i and the target UAV j, and control the movement of the target UAV i and the target UAV j according to the distance D. After the movement is completed, the target UAV i transmits the collected geographic mapping data to the target UAV j, and moves from the current position to the next mapping point on the corresponding flight route after the transmission is completed; the target UAV j transmits the received geographic mapping data to the ground center, and moves from the current position to the next mapping point on the corresponding flight route after the transmission is completed.

2. The method for collaborative geological surveying and mapping based on unmanned aerial vehicles according to claim 1, characterized in that: Controlling the movement of the target UAV i and the target UAV j according to the distance D includes: When the distance D≤Dys, the target UAV i and the target UAV j do not move, and Dys represents the preset optimal transmission distance; When the distance D>Dys, the following steps are performed: The route corresponding to the distance D is obtained and recorded as the standard line. The target UAV i is controlled to move along the standard line toward the target UAV j by a target distance d=(D-Dys) / 2; the target UAV j is controlled to move along the standard line toward the target UAV i by a target distance d.

3. The method for collaborative geological surveying and mapping based on unmanned aerial vehicles according to claim 2, characterized in that: When the target UAV j is at an abnormal point, the target UAV j transmits the received geographic mapping data of the target UAV i to the remaining target UAVs, and the remaining target UAVs transmit it to the ground center.

4. The method for collaborative geological surveying and mapping based on unmanned aerial vehicles according to claim 1, characterized in that: The process of obtaining a pre-trained scoring model includes: Establishing a data set, wherein the data set stores environmental conditions with labeled signal transmission scores; A scoring model is established based on deep learning, and the scoring model is trained and verified based on the data set to obtain a pre-trained scoring model.

5. The method for collaborative geological surveying and mapping based on unmanned aerial vehicles according to claim 1, characterized in that: The process of obtaining the quantity m includes: Setting the objective function ,y k represents the target value. When the kth UAV is the target UAV, y k =1, K represents the total number of drones in the drone hive; when the kth drone is not the target drone, y k =0; The objective function is solved by integer linear programming in combination with preset constraints to obtain the quantity m.

6. The method for collaborative geological surveying and mapping based on unmanned aerial vehicles according to claim 5, characterized in that: The constraints specifically include: A single surveying point is visited by the target UAV at least once; A single target drone only departs from the drone hive once, and a single target drone must return to the drone hive once; The distance that a single UAV takes from the UAV hive to the UAV hive is recorded as the target distance. The single target distance is less than 0.8L, and the target distance corresponds to only one route. L represents the maximum cruising range of the UAV.

7. The method for collaborative geological surveying and mapping based on unmanned aerial vehicles according to claim 6, characterized in that: The route corresponding to the target distance is marked as the corresponding flight route of the target UAV.

8. A geological surveying and mapping collaborative operation system based on unmanned aerial vehicles, characterized in that: include: Task allocation module: divide the area to be surveyed into grids to obtain several grid areas, take the center point of the grid area as the survey point, and mark any m drones in the drone hive as target drones, where m is a preset number; Initial control module: obtaining a flight route of a single target UAV, and the target UAV goes to the mapping point along the flight route for geographic mapping; When the target UAV i enters the next grid area a on the corresponding flight route, the environmental conditions on the surveying point A corresponding to the grid area a are collected, and the environmental conditions are input into the pre-trained scoring model to output the signal transmission score; Selection module: when the signal transmission score is less than a preset signal transmission score threshold, the mapping point A is recorded as an abnormal point, and when the target drone i collects geographic mapping data at the abnormal point, the target drone closest to the target drone i is obtained and recorded as target drone j; Control optimization module: obtain the distance D between the target drone i and the target drone j, control the movement of the target drone i and the target drone j according to the distance D, and after the movement is completed, the target drone i transmits the collected geographic mapping data to the target drone j, and moves from the current position to the next mapping point on the corresponding flight route after the transmission is completed; the target drone j transmits the received geographic mapping data to the ground center, and moves from the current position to the next mapping point on the corresponding flight route after the transmission is completed.

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