A method and system for aerial surveying and control of unmanned aerial vehicles (UAVs) for geological exploration.

Abstract

This invention provides a UAV aerial survey control method and system for geological exploration, belonging to the fields of UAV flight control and geological exploration aerial survey technology. By introducing historical wall-oriented aerial survey control profile data, the method enables the UAV to have table-readable lateral distance targets, yaw orientation targets, forward velocity targets, and safe bandwidth at different mileage positions along the wall. It constructs an image state association record and extracts wall-oriented yaw deviation evidence from the images, allowing the UAV to perform flight control attitude correction based on the actual wall-oriented imaging state. A comprehensive evaluation mechanism is introduced to unify lateral error, orientation error, image evidence reliability, and lateral error change trends into the risk scoring and threshold judgment process. This makes the correction mode switching more suitable for scenarios where crosswinds change suddenly, lighting shadows, and weak textures lead to unstable evidence, thereby reducing delayed correction and misjudgment. This allows the UAV to first obtain a stable and controllable wall-oriented state in high-risk sections, improving safety and continuity.

Description

Technical Field

[0001] This invention relates to the fields of unmanned aerial vehicle (UAV) flight control and geological survey aerial measurement technology, specifically to a UAV aerial survey control method and system for geological survey. Background Technology

[0002] In geological exploration, UAV aerial surveying is commonly used to acquire high-resolution image data of target areas such as fault zones, rock mass structural surfaces, collapse boundaries, and landslide fissure zones. This data supports subsequent geological interpretation, structural line extraction, geological hazard identification, and measurement analysis. Especially in terrain conditions such as canyons, steep cliffs, and mine slopes, geological targets are often distributed in narrow strips along rock walls or slopes. Aerial surveying missions require UAVs to fly close to the rock walls along the corridor, keeping the camera continuously facing the rock wall and obtaining sufficient effective overlap to ensure usable image continuity and a basis for geometric reconstruction in key sections. Current aerial surveying techniques typically involve planning fixed flight routes before the mission, automatically flying according to waypoints and taking timed exposures during the mission, with flight control focusing on waypoint tracking and altitude maintenance. In ordinary open environments, these methods can achieve survey area coverage with minimal intervention.

[0003] However, in application scenarios such as aerial surveying along the walls of deeply incised canyons, the flight environment is characterized by narrow passages, significant lateral wind disturbances, frequent rock wall obstructions and sharp bends, and strong changes in lighting and shadows. This can lead to several issues even when the drone flies along the predetermined waypoints: First, the lateral distance between the drone and the rock wall may continuously deviate, resulting in safety risks and image obstruction if the drone gets too close, or insufficient resolution and reduced target coverage if the drone drifts too far. Second, the drone's yaw direction may deviate, causing the camera's main field of view to gradually shift away from the rock wall, resulting in insufficient effective wall-facing area for multiple consecutive frames of images. This can create gaps in key fault sections where images appear to have been taken but are difficult to use for subsequent results. Third, in areas with strong shadows, dust reflections, or weak textures, the instability of the image evidence can cause delays or misjudgments when switching correction modes based on a single error indicator.

[0004] Therefore, there is an urgent need for a UAV aerial survey control method that can combine historical wall-oriented control experience with real-time aerial survey status and introduce wall effectiveness and evidence reliability assessment, so as to dynamically generate route and attitude control commands that are more in line with the actual scenario during the aerial survey process. Summary of the Invention

[0005] The purpose of this invention is to provide an unmanned aerial survey control method for geological exploration, so as to solve at least one of the above-mentioned technical problems.

[0006] To achieve the above objectives, the first aspect of the present invention provides an unmanned aerial vehicle (UAV) aerial survey control method for geological exploration. The method includes the following steps: acquiring historical wall-direction aerial survey control profile data for close-to-wall aerial surveys, and establishing a wall-direction control profile table based on the historical wall-direction aerial survey control profile data; acquiring real-time flight status information and aerial survey image information of the UAV during the aerial survey, and establishing an image status association record based on the real-time flight status information and the aerial survey image information; determining the current position mileage of the UAV on the reference centerline corresponding to the wall-direction control profile table based on the real-time flight status information, and extracting lateral distance target, yaw direction target, forward velocity target, and safety bandwidth from the wall-direction control profile table to form a control target; extracting image yaw deviation evidence based on the image status association record, and combining the control target and the real-time flight status information to form a control error; generating a route dynamic adjustment command and attitude control command for aerial survey flight based on the control error, and outputting the route dynamic adjustment command and the attitude control command to the UAV flight control execution, so that the UAV dynamically adjusts its flight route and flight attitude during the aerial survey.

[0007] Optionally, acquiring historical wall-direction aerial survey control profile data for wall-hugging aerial surveys, and establishing a wall-direction control profile table based on the historical wall-direction aerial survey control profile data, includes: acquiring historical wall-direction aerial survey control profile data; wherein the historical wall-direction aerial survey control profile data includes at least reference centerline information, reference lateral distance information, reference yaw heading information, reference forward velocity information, and safety bandwidth information; discretizing the reference centerline along its length direction based on the reference centerline information to form a centerline point series corresponding to the length position, and establishing a length index based on the centerline point series; aligning or interpolating the reference lateral distance information, the reference yaw heading information, the reference forward velocity information, and the safety bandwidth information based on the length index; forming control profile records corresponding to each length position according to the alignment or interpolation results, and establishing a wall-direction control profile table based on the control profile records.

[0008] Optionally, the process involves acquiring real-time flight status information and aerial survey image information of the UAV during the aerial survey, and establishing an image status association record based on the real-time flight status information and the aerial survey image information. This includes: acquiring real-time flight status information collected by the UAV during the aerial survey, and writing the real-time flight status information into a status sequence in chronological order; wherein the real-time flight status information includes at least current position, current speed information, and current yaw information; acquiring aerial survey images collected by the camera mounted on the UAV during the aerial survey, which include aerial survey image information and corresponding exposure time information; selecting the flight status information closest to the exposure time from the status sequence based on the exposure time information, and associating the aerial survey image information with the flight status information to form an image status association record; and acquiring aerial survey camera parameter information; wherein the aerial survey camera parameter information includes at least image width information and horizontal field of view information.

[0009] Optionally, based on the real-time flight status information, the current position mileage of the UAV on the reference centerline corresponding to the wall-directed control profile table is determined, and the lateral distance target, yaw direction target, forward velocity target, and safety bandwidth are extracted from the wall-directed control profile table to form a control target. This includes: performing projection positioning processing based on the current position in the UAV's real-time flight status information and the reference centerline to determine the current position mileage of the UAV on the reference centerline; performing table lookup or interpolation processing based on the current position mileage in the wall-directed control profile table to obtain the lateral distance target, yaw direction target, forward velocity target, and safety bandwidth corresponding to the current position mileage; and summing the lateral distance target, the yaw direction target, the forward velocity target, and the safety bandwidth to form a control target.

[0010] Optionally, based on the image state association record, image yaw deviation evidence is extracted, and combined with the control target and the real-time flight state information to form a control error, including: based on the image state association record, extracting the current aerial survey image and its corresponding flight state information, and determining the image width and horizontal field of view corresponding to the current aerial survey image based on the aerial survey camera parameter information; based on the current aerial survey image, performing edge response statistics or texture response statistics to determine the horizontal center position of the region representing the main texture of the rock wall, and calculating the pixel offset based on the horizontal center position and the image center position; calculating the image yaw correction angle based on the pixel offset, the image width, and the horizontal field of view, and calculating the target yaw deviation based on the yaw orientation target and the current yaw information in the flight state information; combining the target yaw deviation with the image yaw correction angle to form an orientation error, and writing the orientation error into the control error.

[0011] Optionally, the control error is formed by combining the control target and the real-time flight status information, including: performing lateral deviation calculation based on the current position of the UAV and the reference centerline to obtain the signed lateral distance of the UAV relative to the reference centerline; calculating the lateral error based on the lateral distance target and the signed lateral distance, and writing the lateral error into the control error.

[0012] Optionally, before generating route dynamic adjustment commands and attitude control commands for aerial survey flights based on the control error, the method further includes: performing a comprehensive evaluation based on the lateral error, the orientation error, the reliability of image yaw deviation evidence, and the changing trend of the lateral error to generate a correction mode marker; specifically including: obtaining the pixel offset corresponding to the latest aerial survey image based on the image state association record, and generating the reliability of image yaw deviation evidence based on edge response statistics; calculating the change in lateral error based on the lateral error at adjacent control cycle times, and inputting the lateral error, the orientation error, the reliability of image yaw deviation evidence, and the change in lateral error into a risk scoring model to obtain a risk score; performing a correction determination based on the risk score and a correction threshold to generate a correction mode marker; wherein, a strong correction mode marker is generated when the risk score reaches a strong correction threshold or the absolute value of the pixel offset reaches an image inaccuracy threshold, and a flexible correction mode marker is generated when the risk score is lower than the strong correction threshold and meets the flexible correction condition.

[0013] Optionally, based on the control error, attitude control commands for aerial survey flight are generated, including: performing proportional conversion processing based on the orientation error to generate a yaw command increment; generating a yaw control command based on the current yaw information and the yaw command increment; performing change rate limitation processing or range limitation processing on the yaw control command to generate an executable yaw control command; and outputting the executable yaw control command to the UAV flight control execution.

[0014] Optionally, based on the control error, a dynamic route adjustment command for aerial survey flight is generated, including: in flexible correction mode, performing proportional conversion processing based on the lateral error to generate a lateral speed control command; in strong correction mode, generating a forced lateral speed control command based on the sign of the lateral error and a preset lateral speed upper limit; generating a forward speed control command based on the forward speed target, and outputting the lateral speed control command and the forward speed control command to the UAV flight control execution.

[0015] A second aspect of the present invention provides an unmanned aerial vehicle (UAV) aerial survey control system for geological exploration. The system is used to execute the aforementioned UAV aerial survey control method for geological exploration. The system includes: an acquisition unit, configured to acquire historical wall-direction aerial survey control profile data for close-to-wall aerial surveys, and establish a wall-direction control profile table based on the historical wall-direction aerial survey control profile data; an establishment unit, configured to acquire real-time flight status information and aerial survey image information of the UAV during the aerial survey, and establish an image status association record based on the real-time flight status information and the aerial survey image information; and a formation unit, configured to determine the location of the UAV on the wall-direction control profile based on the real-time flight status information. The table corresponds to the current position mileage on the reference centerline. Lateral distance target, yaw heading target, forward velocity target, and safety bandwidth are extracted from the wall-directed control profile table to form the control target. An extraction unit is used to extract yaw deviation evidence from the image based on the image state association record, and combine the control target with the real-time flight state information to form the control error. An execution unit is used to generate dynamic route adjustment commands and attitude control commands for aerial survey flights based on the control error, and output the dynamic route adjustment commands and attitude control commands to the UAV flight control execution, so that the UAV dynamically adjusts its flight route and attitude during the aerial survey process.

[0016] Through the above technical solutions, this invention introduces historical wall-oriented aerial survey control profile data, enabling wall-hugging aerial surveys to have table-readable lateral distance targets, yaw orientation targets, forward speed targets, and safe bandwidth at different mileage positions, avoiding the insufficient adaptability of a single fixed route in sharp bends and narrow sections of canyons; by constructing image state association records and extracting wall-hugging yaw deviation evidence from the images, flight control can not only fly according to waypoints but also perform attitude correction based on the actual wall-hugging imaging state; through a comprehensive evaluation mechanism, lateral error, orientation error, image evidence reliability, and lateral error change trends are unified into the risk scoring and threshold judgment process, making the correction mode switching more consistent with real-world scenarios where crosswinds change suddenly, and light and shadow are weak and textures cause unstable evidence, thereby reducing delayed correction and misjudgment; by linking lateral dynamic adjustment and forward speed suppression in strong correction mode, the UAV first obtains a stable and controllable wall-hugging state in high-risk sections before resuming the aerial survey rhythm, improving safety and continuity.

[0017] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0018] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0019] Figure 1 This is a flowchart of the steps of an unmanned aerial survey control method for geological exploration provided by one embodiment of the present invention;

[0020] Figure 2 This is a system structure diagram of an unmanned aerial survey control system for geological exploration provided by one embodiment of the present invention. Detailed Implementation

[0021] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0022] like Figure 1 As shown, this invention provides a UAV aerial survey control method for geological exploration, the method comprising:

[0023] S10: Obtain historical wall-direction aerial survey control profile data for wall-hugging aerial surveys, and establish a wall-direction control profile table based on the historical wall-direction aerial survey control profile data.

[0024] Specifically, this embodiment of the invention acquires historical wall-direction aerial survey control profile data for wall-following aerial surveys and establishes a wall-direction control profile table, enabling subsequent aerial survey processes to find lateral distance targets, yaw heading targets, forward velocity targets, and safe bandwidth matching any location, thereby providing a consistent reference basis for dynamic flight control.

[0025] It should be noted that historical wall-direction aerial survey control profile data can originate from historical mission results, manually marked flyable corridors, or reference paths extracted from existing surveying results. It should also be noted that historical wall-direction aerial survey control profile data is not limited to a single source; as long as it can provide a continuous reference centerline and corresponding control target along the length direction, it meets the input requirements of this invention's implementation method.

[0026] In this embodiment of the invention, acquiring historical wall-direction aerial survey control profile data for wall-hugging aerial surveys and establishing a wall-direction control profile table based on the historical wall-direction aerial survey control profile data includes: acquiring historical wall-direction aerial survey control profile data; wherein the historical wall-direction aerial survey control profile data includes at least reference centerline information, reference lateral distance information, reference yaw heading information, reference forward velocity information, and safety bandwidth information; discretizing the reference centerline along its length direction based on the reference centerline information to form a centerline point series corresponding to the length position, and establishing a length index based on the centerline point series; aligning or interpolating the reference lateral distance information, the reference yaw heading information, the reference forward velocity information, and the safety bandwidth information based on the length index; forming control profile records corresponding to each length position according to the alignment or interpolation results, and establishing a wall-direction control profile table based on the control profile records.

[0027] First, perform step S101: acquire historical wall-direction aerial survey control profile data.

[0028] In step S101, historical wall-oriented aerial survey control profile data is acquired. The data includes at least: reference centerline information, reference lateral distance information, reference yaw heading information, reference forward velocity information, and safety bandwidth information.

[0029] Among them, the reference centerline is used to describe the dominant path of the close-to-the-wall aerial survey corridor; the reference lateral distance is used to constrain the positional relationship of the UAV relative to the corridor to avoid being too close or too far from the wall; the reference yaw orientation is used to constrain the camera to continuously face the rock wall, so that the geological target remains in the camera's main field of view; the reference forward velocity is used to constrain the aerial survey rhythm, so that the exposure spacing and overlap requirements are guaranteed on the flight control side; and the safety bandwidth is used to define the acceptable lateral deviation range, providing a safe semantic boundary for subsequent yaw correction mode switching.

[0030] In one example scenario, deeply incised canyon sections often present both narrow passages and lateral wind disturbances. The safety bandwidth can be set as a value that varies with mileage, using a smaller range in narrow sections to improve safety and a larger range in open sections to improve efficiency. The above method of setting values ​​is only an example and does not limit the specific value strategy.

[0031] Next, perform step S102: Discretize the reference centerline and establish a length index.

[0032] In step S102, the centerline is discretized along the length direction based on the reference centerline information to form a centerline point column that corresponds one-to-one with the length position, and a length index is established based on the centerline point column.

[0033] In practical applications, the UAV's position changes continuously during the flight control cycle, while the control profile is typically stored in the form of a discrete table in engineering implementation. By discretizing the centerline and establishing an index, the process of mapping the current position to the length position can be transformed into an executable lookup or interpolation operation, improving real-time performance and stability. During operation, the discretization spacing can be set according to the aerial survey speed, terrain curvature, and control cycle frequency. For example, denser discrete points can be used in sharp curves to improve the spatial resolution of target extraction.

[0034] Then, step S103 is performed: the control information is aligned or interpolated by length index and a profile record is created.

[0035] In step S103, the reference lateral distance information, reference yaw heading information, reference forward velocity information, and safety bandwidth information are aligned or interpolated based on the length index to form a control profile record that corresponds one-to-one with each length position.

[0036] In practical applications, different control information may originate from different precisions or different sampling points. If they are not aligned, it will lead to missing items or jumps when looking up tables later. By aligning or interpolating, each length position can have a complete set of control targets, thereby avoiding flight control jitter caused by discontinuity of control targets. In an optional implementation, yaw heading can be processed with angle continuity to avoid abrupt changes when crossing angle boundaries.

[0037] Finally, execute step S104: create and output the wall control profile table.

[0038] In step S104, a wall-direction control profile table is established based on the above control profile records, and it is used as the lookup data source for subsequent extraction of lateral distance targets, yaw heading targets, forward velocity targets, and safety bandwidth.

[0039] It should be understood that the wall-directed control profile table can be stored at the flight control terminal, the payload terminal, or the ground station terminal; as long as it can be read in the flight control cycle and used to generate control targets, it falls within the scope of the embodiments of the present invention.

[0040] S20: Acquire real-time flight status information and aerial survey image information of the UAV during the aerial survey process, and establish an image status association record based on the real-time flight status information and the aerial survey image information.

[0041] Specifically, during aerial survey flights, the dynamic adjustment of the UAV's route and attitude control rely on real-time status information, while the effectiveness of wall imaging depends on aerial survey imagery information. This invention's embodiment correlates these two aspects over time, which is a crucial foundation for transforming imagery evidence into control error.

[0042] In this embodiment of the invention, real-time flight status information and aerial survey image information of a UAV during aerial surveying are acquired, and an image status association record is established based on the real-time flight status information and the aerial survey image information. This includes: acquiring real-time flight status information collected by the UAV during aerial surveying and writing the real-time flight status information into a status sequence in chronological order; wherein the real-time flight status information includes at least current position, current speed information, and current yaw information; acquiring aerial survey images collected by the camera mounted on the UAV during aerial surveying, which include aerial survey image information and corresponding exposure time information; selecting the flight status information closest to the exposure time from the status sequence based on the exposure time information, and associating the aerial survey image information with the flight status information to form an image status association record; and acquiring aerial survey camera parameter information; wherein the aerial survey camera parameter information includes at least image width information and horizontal field of view information.

[0043] First, perform step S201: collect real-time flight status information and write it into the status sequence.

[0044] In step S201, real-time flight status information of the UAV is collected in the aerial survey flight control loop. The flight status information includes at least the current position, current speed information and current yaw information, and is written into the status sequence in chronological order.

[0045] In practical applications, flight control relies on the difference between the current state and the target state; the state sequence is used both for current control calculations and for correlation with image exposure times, thereby ensuring that image evidence can be traced back to the corresponding attitude and position. During operation, the control cycle frequency can be set according to the flight control capabilities; a higher frequency allows for a finer-grained trend of error changes.

[0046] Next, perform step S202: collect aerial survey image information and obtain exposure time information.

[0047] In step S202, aerial survey image information is acquired when the camera exposes and generates aerial survey images, and the corresponding exposure time information is obtained. This step is used to ensure a clear temporal correspondence between subsequent image evidence extraction and flight status.

[0048] It should be noted that the exposure time information can be provided by the camera timestamp, flight control trigger receipt, or unified clock synchronization mechanism, as long as the control cycle time corresponding to the image can be located.

[0049] Then, perform step S203: establish image status association records.

[0050] In step S203, the flight status information closest to the exposure time is selected from the status sequence based on the exposure time information, and the aerial survey image information is associated with the flight status information to form an image status association record.

[0051] It should be noted that the subsequent deviation of the rock wall in the image can be directly mapped to the yaw state at that time, and thus used to construct orientation error and correction commands.

[0052] Finally, step S204 is executed: camera parameter information is obtained and used as the source of image evidence calculation.

[0053] In step S204, aerial survey camera parameter information is acquired, including at least image width information and horizontal field of view information. This camera parameter information is used as the parameter source for subsequent calculation of image yaw correction angles. In practical applications, pixel offset needs to be mapped to angular deviation through the field of view to form a correction amount that can be directly used for flight control. Camera parameters can be obtained from camera calibration information, equipment specifications, or mission configuration; this invention does not limit the method of acquisition.

[0054] S30: Based on the real-time flight status information, determine the current position mileage of the UAV on the reference centerline corresponding to the wall control profile table, and extract the lateral distance target, yaw orientation target, forward velocity target and safety bandwidth from the wall control profile table to form a control target.

[0055] Specifically, by mapping the current position of the UAV to the reference centerline mileage position corresponding to the wall-directed control profile table, and extracting the corresponding control target at that mileage position, the flight control can automatically switch to the appropriate lateral distance target, yaw heading target, and forward velocity target in different terrain sections, thereby having control setpoints that vary along the mileage.

[0056] In this embodiment of the invention, based on the real-time flight status information, the current position mileage of the UAV on the reference centerline corresponding to the wall-directed control profile table is determined. Lateral distance target, yaw direction target, forward velocity target, and safety bandwidth are extracted from the wall-directed control profile table to form a control target. This includes: performing projection positioning processing based on the current position in the UAV's real-time flight status information and the reference centerline to determine the current position mileage of the UAV on the reference centerline; performing table lookup or interpolation processing based on the current position mileage in the wall-directed control profile table to obtain the lateral distance target, yaw direction target, forward velocity target, and safety bandwidth corresponding to the current position mileage; and summing the lateral distance target, yaw direction target, forward velocity target, and safety bandwidth to form a control target.

[0057] First, execute step S301: Perform projection positioning to determine the current location mileage.

[0058] In step S301, projection positioning processing is performed based on the current position of the UAV and the reference center line to determine the current position mileage of the UAV on the reference center line.

[0059] In practical applications, the close-to-wall aerial survey corridor exhibits distinct along-line characteristics. Mapping two-dimensional positions to one-dimensional mileage simplifies the control target lookup problem into a one-dimensional indexing problem, improving real-time performance and reducing unnecessary path replanning. During operation, methods such as nearest point projection or nearest line segment projection can be used; different implementation methods are applicable as long as they achieve consistent mileage indexing results.

[0060] Next, execute step S302: look up the table or interpolate to obtain the control target.

[0061] In step S302, a lookup or interpolation process is performed in the wall control profile table based on the current position mileage to obtain the lateral distance target, yaw heading target, forward speed target, and safety bandwidth corresponding to the current position mileage. This step ensures that complete control targets can be obtained at any mileage position, avoiding local mismatches caused by relying solely on fixed waypoints.

[0062] In one example, if entering a sharp bend or narrow section, the lateral distance target given in the profile table can be moderately increased, the yaw heading target can be moderately adjusted to maintain alignment with the wall, and the safety bandwidth can be tightened to strengthen safety constraints.

[0063] Finally, step S303 is executed: a control target is formed and used as input for subsequent error and instruction generation.

[0064] In step S303, the lateral distance target, yaw heading target, forward velocity target, and safety bandwidth are combined to form the control target, and the control target is used as the data input for subsequent formation of control error and generation of route dynamic adjustment command and attitude control command.

[0065] It should be understood that the control target can be used directly for error calculation or as a normalization benchmark in the determination of the correction mode, so that the errors at different mileage positions can be compared on the same scale.

[0066] S40: Based on the image status association record, extract image yaw deviation evidence, and combine it with the control target and the real-time flight status information to form a control error.

[0067] Specifically, the key to this step is to transform the aerial survey imagery of the wall into angular correction evidence that can be used for flight control, and to combine it with the control target and real-time status to form control error, thereby providing direct input for subsequent command generation.

[0068] In this embodiment of the invention, based on the image state association record, image yaw deviation evidence is extracted, and combined with the control target and the real-time flight state information to form a control error. This includes: extracting the current aerial survey image and its corresponding flight state information based on the image state association record, and determining the image width and horizontal field of view corresponding to the current aerial survey image based on the aerial survey camera parameter information; performing edge response statistics or texture response statistics based on the current aerial survey image to determine the horizontal center position of the region representing the main texture of the rock wall, and calculating the pixel offset based on the horizontal center position and the image center position; calculating the image yaw correction angle based on the pixel offset, the image width, and the horizontal field of view; calculating the target yaw deviation based on the yaw orientation target and the current yaw information in the flight state information; combining the target yaw deviation with the image yaw correction angle to form an orientation error, and writing the orientation error into the control error.

[0069] Based on this, the control target and the real-time flight status information are combined to form a control error, including: performing lateral deviation calculation based on the current position of the UAV and the reference centerline to obtain the signed lateral distance of the UAV relative to the reference centerline; calculating the lateral error based on the lateral distance target and the signed lateral distance, and writing the lateral error into the control error.

[0070] First, perform step S401: extract pixel offset.

[0071] In step S401, the current aerial survey image and its corresponding flight status information are extracted based on the image status association record, and edge response statistics or texture response statistics are performed based on the aerial survey image to determine the horizontal center position of the main texture area of ​​the rock wall; then the pixel offset is calculated based on the horizontal center position and the image center position.

[0072] In practical applications, during close-to-rock aerial surveys, rock walls typically appear as areas with denser textures and edges, especially in fault and joint fracture zones where edge responses are more pronounced. By centering the rock wall based on statistical results of edges or textures, a quantitative representation of whether the rock wall is positioned to the left or right in the image can be obtained.

[0073] It should be noted that edge response statistics can be implemented using mature operators, such as extracting edges and statistically analyzing left and right distributions by using gradient magnitude thresholds; the specific operator selection is not limited to one type, as long as it can output a stable statistical center.

[0074] Next, perform step S402: calculate the image yaw correction angle.

[0075] In step S402, the image yaw correction angle is calculated based on the pixel offset, image width, and horizontal field of view. The image yaw correction angle satisfies the following:

[0076] ;

[0077] in, Correct the yaw angle for the image; W is the pixel offset; W is the image width. is the horizontal field of view; k is the image number.

[0078] In this embodiment of the invention, the proportion of image offset to the width of the image is mapped to the angular deviation in the field of view, thereby converting image evidence into an angular quantity that can be directly used by the flight control.

[0079] Then, step S403 is executed: orientation error is generated and written into control error.

[0080] In step S403, the target yaw deviation is calculated based on the yaw orientation target and the current yaw information in the flight status information. The target yaw deviation is then combined with the image yaw correction angle to form an orientation error, which satisfies the following:

[0081] ;

[0082] in, This is for orientation error; To yaw toward the target; t represents the current yaw information; t represents the control cycle time.

[0083] In this embodiment of the invention, the yaw direction to the target reflects how the wall should be aligned according to the historical corridor, and the image correction angle reflects whether the rock wall in the current image deviates from the main field of view. The superposition of the two can enhance the scene adaptability of wall alignment control. It should be understood that the image correction angle can also be smoothed over time, for example, by taking the average of the most recent several frames to reduce jitter. This processing is an optional engineering implementation and does not constitute a limitation.

[0084] Finally, step S404 is executed: lateral error is generated and written into the control error.

[0085] In step S404, a lateral deviation calculation is performed based on the current position of the UAV and the reference centerline to obtain the signed lateral distance of the UAV relative to the reference centerline; a lateral error is calculated based on the lateral distance target and the signed lateral distance, wherein the lateral error satisfies:

[0086] ;

[0087] in, This refers to lateral error; For targets at lateral distance; This represents the signed horizontal distance.

[0088] In this embodiment of the invention, under the wall-hugging corridor model, the reference centerline and the lateral distance target together constitute the lateral reference of the flyable corridor; the signed lateral distance characterizes the current deviation direction and degree, and can thus be used to generate lateral dynamic adjustment commands. It should be noted that the sign convention of the signed lateral distance can be determined according to the definition of the centerline normal, as long as it remains consistent throughout the entire process.

[0089] S50: Based on the control error, generate dynamic route adjustment commands and attitude control commands for aerial survey flights, and output the dynamic route adjustment commands and attitude control commands to the UAV flight control execution, so that the UAV can dynamically adjust its flight route and flight attitude during the aerial survey process.

[0090] Specifically, this step not only switches the correction mode based on whether the lateral error exceeds the limit, but also considers the orientation error, the reliability of image evidence, and the trend of lateral error changes, so that the correction mode switching is more in line with the real risk mechanism of canyon-wall aerial surveying.

[0091] In this embodiment of the invention, before generating route dynamic adjustment commands and attitude control commands for aerial survey flights based on the control error, the method further includes: performing a comprehensive evaluation based on the lateral error, the orientation error, the reliability of image yaw deviation evidence, and the changing trend of the lateral error to generate a correction mode marker; specifically including: obtaining the pixel offset corresponding to the latest aerial survey image based on the image state association record, and generating the reliability of image yaw deviation evidence based on edge response statistics; calculating the change in lateral error based on the lateral error at adjacent control cycle times, and inputting the lateral error, the orientation error, the reliability of image yaw deviation evidence, and the change in lateral error into a risk scoring model to obtain a risk score; performing a correction determination based on the risk score and a correction threshold to generate a correction mode marker; wherein, a strong correction mode marker is generated when the risk score reaches a strong correction threshold or the absolute value of the pixel offset reaches an image inaccuracy threshold, and a flexible correction mode marker is generated when the risk score is lower than the strong correction threshold and meets the flexible correction condition.

[0092] Based on this, attitude control commands for aerial survey flights are generated based on the control error, including: performing proportional conversion processing based on the orientation error to generate a yaw command increment; generating a yaw control command based on the current yaw information and the yaw command increment; performing change rate limitation processing or range limitation processing on the yaw control command to generate an executable yaw control command; and outputting the executable yaw control command to the UAV flight control execution.

[0093] Based on this, and based on the control error, dynamic route adjustment commands for aerial survey flights are generated, including: in flexible correction mode, performing proportional conversion processing based on the lateral error to generate lateral speed control commands; in strong correction mode, generating forced lateral speed control commands based on the sign of the lateral error and a preset lateral speed upper limit; generating forward speed control commands based on the forward speed target; and outputting the lateral speed control commands and the forward speed control commands to the UAV flight control execution.

[0094] First, perform step S501: generate the reliability of image evidence and the trend of lateral error changes.

[0095] In step S501, the pixel offset corresponding to the latest aerial survey image is obtained based on the image state association record, and the reliability of the image yaw deviation evidence is generated based on the edge response statistics used to determine the pixel offset; simultaneously, the change in lateral error is calculated based on the lateral error at adjacent control cycle times. The image evidence reliability is used to characterize whether the current image offset is credible.

[0096] In one alternative implementation, reliability can be constructed using the concentration of edge response statistics: higher reliability is indicated when the edge response is concentrated on one side and has a significant peak; lower reliability is indicated when the edge response is discrete, the peak is not significant, or it is affected by shadow noise. The change in lateral error is used to characterize whether lateral drift is rapidly deteriorating. During sudden changes in crosswinds in a canyon, the instantaneous value of the lateral error may not yet exceed the limit, but its rate of increase indicates that it will soon enter a danger zone; incorporating the trend into the assessment can trigger strong corrections in advance, improving safety and continuity.

[0097] Next, perform step S502: calculate the risk score and generate the correction mode label.

[0098] In step S502, the lateral error, orientation error, image evidence reliability, and lateral error change are input into the risk scoring model to obtain a risk score, which satisfies the following:

[0099] ;

[0100] Where R(t) is the risk score; w1, w2, w3, w4 are weighting coefficients; and Band(t) is the security bandwidth. The allowable orientation error threshold; The reliability of the image yaw deviation evidence; Δt is the time interval between adjacent control cycles; This is the normalized threshold for the change in lateral error.

[0101] In this embodiment of the invention, the risk scoring formula includes a first term characterizing the proportion of lateral deviation relative to the safe bandwidth; a second term characterizing the proportion of directional deviation relative to the acceptable threshold; a third term characterizing the decision risk caused by unreliable image evidence; and a fourth term characterizing the risk of the rate of deterioration of lateral deviation. Through this combination, the correction mode switching not only considers the extent of deviation but also whether it is worsening and the reliability of the image evidence.

[0102] Subsequently, a correction determination is performed based on the risk score and the correction threshold: a strong correction mode marker is generated when the risk score reaches or exceeds the strong correction threshold; a flexible correction mode marker is generated when the risk score is below the strong correction threshold and the flexible correction conditions are met. Furthermore, a strong correction mode marker is directly generated when the absolute value of the pixel offset reaches or exceeds the image misalignment threshold. This direct triggering mechanism is used to cover certain special cases: for example, if the lateral error is still within the safe bandwidth, but the camera's main field of view has significantly deviated from the rock face, then using flexible correction would result in multiple consecutive frames failing to align with the rock face, thus creating gaps in critical sections.

[0103] Traditional methods generate flexible or strong correction modes by comparing lateral error with the safe bandwidth alone. This is prone to misjudgment when the lateral error has not yet exceeded the limit but the effectiveness of aerial surveying has significantly decreased. In contrast, the embodiments of this invention adopt a risk scoring model that comprehensively considers lateral error, orientation error, image evidence reliability, and lateral error variation. This approach has significant advantages in the following typical scenarios:

[0104] (1) Significant deviation in body orientation but normal lateral distance: In canyon wall aerial surveying, crosswinds or sharp bends can cause the UAV to yaw and drift, causing the camera's main field of view to deviate from the rock wall. At this time, the lateral error may still be within the safe bandwidth. Traditional judgment will maintain flexible correction, which will result in insufficient alignment of multiple consecutive frames of images with the wall and a decrease in effective overlap, eventually leading to gaps in key segments that cannot be modeled. The embodiments of the present invention introduce both orientation error and image pixel offset thresholds, which can directly trigger strong correction when the wall misalignment just occurs, avoiding misjudgment.

[0105] (2) The trend of lateral error changes too fast but the instantaneous value does not exceed the limit: In the narrow section of the canyon, the lateral error may increase rapidly (e.g., a sudden gust of wind). Traditionally, only looking at the instantaneous lateral error will delay the triggering of strong correction, which may pose a risk of sticking to the wall or sudden loss of shooting coverage. The embodiment of the present invention incorporates the change in lateral error into the risk score, which can switch to the strong correction mode in advance, thereby improving safety and the continuity of aerial survey.

[0106] (3) Low reliability of image evidence leads to unstable decision-making based on a single indicator: Under strong shadows, dust or reflection interference, relying solely on lateral error may not reflect the actual wall effect; the embodiments of the present invention introduce image yaw deviation evidence reliability, making mode switching more in line with the availability of on-site images and reducing erroneous control strategies under special lighting conditions.

[0107] It should be noted that, without changing the basic ideas of comprehensive evaluation and mode switching, different normalization methods or threshold setting strategies can be adopted.

[0108] Then, step S503 is executed: attitude control commands are generated and output for execution.

[0109] In step S503, a proportional conversion process is performed based on the orientation error to generate a yaw command increment. Subsequently, a yaw control command is generated based on the current yaw information and the yaw command increment.

[0110] ;

[0111] ;

[0112] in, This is the increment for the yaw command; This is the yaw ratio factor; This is a yaw control command.

[0113] In this embodiment of the invention, the yaw control command undergoes rate of change limitation processing or range limitation processing to generate executable yaw control commands and output them to the UAV flight control execution. Yaw correction must consider the rate of change of the aircraft's attitude and load stability. Amplitude limiting processing can avoid rapid swaying caused by image noise, making the aerial survey image more stable.

[0114] Finally, step S504 is executed: generate route dynamic adjustment instructions and forward speed control instructions and output them for execution.

[0115] In step S504, in flexible correction mode, proportional conversion processing is performed based on lateral error to generate lateral velocity control commands:

[0116] ;

[0117] in, This is a lateral speed control command; This is the horizontal scaling factor.

[0118] In strong correction mode, a forced lateral velocity control command is generated based on the sign of the lateral error and the preset upper limit of lateral velocity:

[0119] ;

[0120] in, This represents the upper limit of lateral speed.

[0121] Simultaneously, forward velocity control commands are generated based on the forward velocity target, and scaling processing is performed on the forward velocity target in strong correction mode:

[0122] ;

[0123] in, Forward speed control command; β represents the forward velocity target; β is the scaling factor.

[0124] In this embodiment of the invention, lateral speed control commands and forward speed control commands are output to the UAV flight control execution, enabling the UAV to perform dynamic lateral adjustments while maintaining aerial survey propulsion, and to achieve aerial survey rhythm control in conjunction with dynamic forward speed adjustments. In strong correction mode, reducing the forward speed provides time margin for lateral pull-back and yaw adjustment, avoiding continuous loss of target area due to deviation while advancing at high speed in high-risk sections; in flexible correction mode, the forward speed target is maintained to ensure efficiency and coverage rhythm.

[0125] Therefore, this embodiment of the invention introduces historical wall-oriented aerial survey control profile data, enabling wall-hugging aerial surveys to have table-accessible lateral distance targets, yaw orientation targets, forward velocity targets, and safe bandwidth at different mileage locations. It constructs an image state association record and extracts wall-hugging yaw deviation evidence from the images, allowing the UAV to perform flight control attitude correction based on the actual wall-hugging imaging state. A comprehensive evaluation mechanism is introduced to unify lateral error, orientation error, image evidence reliability, and lateral error change trends into the risk scoring and threshold determination process. This makes the correction mode switching more suitable for scenarios where crosswinds change suddenly, lighting shadows, and weak textures lead to unstable evidence, thereby reducing delayed correction and misjudgment. This allows the UAV to first obtain a stable and controllable wall-hugging state in high-risk segments, improving safety and continuity.

[0126] like Figure 2As shown, this invention provides an unmanned aerial vehicle (UAV) aerial survey control system for geological exploration. The system executes the aforementioned UAV aerial survey control method for geological exploration. The system includes: an acquisition unit for acquiring historical wall-direction aerial survey control profile data for close-to-wall aerial surveys and establishing a wall-direction control profile table based on the historical wall-direction aerial survey control profile data; an establishment unit for acquiring real-time flight status information and aerial survey image information of the UAV during the aerial survey process and establishing an image status association record based on the real-time flight status information and the aerial survey image information; and a formation unit for determining the position of the UAV under wall-direction control based on the real-time flight status information. The profile table corresponds to the current position mileage on the reference centerline. Lateral distance target, yaw heading target, forward velocity target, and safety bandwidth are extracted from the wall-directed control profile table to form the control target. The extraction unit is used to extract yaw deviation evidence from the image based on the image state association record, and combine the control target with the real-time flight state information to form the control error. The execution unit is used to generate dynamic route adjustment commands and attitude control commands for aerial survey flight based on the control error, and output the dynamic route adjustment commands and attitude control commands to the UAV flight control execution to enable the UAV to dynamically adjust the flight route and flight attitude during the aerial survey.

[0127] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0128] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details described above. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe the various possible combinations.

[0129] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the embodiments of the present invention, they should also be regarded as the content disclosed by the embodiments of the present invention.

Claims

1. A method for controlling unmanned aerial surveys (UAVs) for geological exploration, characterized in that, The method includes the following steps: Acquire historical wall-direction aerial survey control profile data for wall-hugging aerial surveys, and establish a wall-direction control profile table based on the historical wall-direction aerial survey control profile data; Acquire real-time flight status information and aerial survey image information of the UAV during the aerial survey process, and establish an image status association record based on the real-time flight status information and the aerial survey image information; Based on the real-time flight status information, the current position mileage of the UAV on the reference centerline corresponding to the wall control profile table is determined, and the lateral distance target, yaw orientation target, forward velocity target and safe bandwidth are extracted from the wall control profile table to form the control target; Based on the image state association record, image yaw deviation evidence is extracted, and combined with the control target and the real-time flight state information to form a control error; specifically, this includes: based on the image state association record, extracting the current aerial survey image and its corresponding flight state information, and determining the image width and horizontal field of view corresponding to the current aerial survey image based on the aerial survey camera parameter information; based on the current aerial survey image, performing edge response statistics or texture response statistics to determine the horizontal center position of the region representing the main texture of the rock wall, and calculating the pixel offset based on the horizontal center position and the image center position; calculating the image yaw correction angle based on the pixel offset, the image width, and the horizontal field of view; calculating the target yaw deviation based on the yaw orientation target and the current yaw information in the flight state information; combining the target yaw deviation with the image yaw correction angle to form an orientation error, and writing the orientation error into the control error; Based on the control error, dynamic route adjustment commands and attitude control commands are generated for aerial survey flights. The dynamic route adjustment commands and attitude control commands are output to the UAV flight control execution, so that the UAV can dynamically adjust its flight route and flight attitude during the aerial survey process.

2. The UAV aerial survey control method for geological exploration according to claim 1, characterized in that, Acquire historical wall-direction aerial survey control profile data used for wall-hugging aerial surveys, and based on the historical wall-direction aerial survey control profile data, establish a wall-direction control profile table, including: Acquire historical wall-oriented aerial survey control profile data; wherein, the historical wall-oriented aerial survey control profile data includes at least reference centerline information, reference lateral distance information, reference yaw heading information, reference forward velocity information, and safety bandwidth information; Based on the reference centerline information, the reference centerline is discretized along the length direction to form a centerline point column corresponding to the length position, and a length index is established based on the centerline point column; The reference lateral distance information, the reference yaw heading information, the reference forward velocity information, and the safety bandwidth information are aligned or interpolated based on the length index. Based on the alignment or interpolation results, control profile records corresponding to each length position are generated, and a wall-oriented control profile table is established based on the control profile records.

3. The UAV aerial survey control method for geological exploration according to claim 1, characterized in that, Acquire real-time flight status information and aerial survey imagery information of the UAV during the aerial survey process, and establish an image status association record based on the real-time flight status information and the aerial survey imagery information, including: The system acquires real-time flight status information collected by the UAV during aerial surveying and writes the real-time flight status information into a status sequence in chronological order; wherein the real-time flight status information includes at least the current position, current speed information, and current yaw information. Acquire aerial survey images, including aerial survey image information and corresponding exposure time information, collected by the camera mounted on the UAV during the aerial survey process; Based on the exposure time information, the flight state information closest to the exposure time is selected from the state sequence, and the aerial survey image information is associated with the flight state information to form an image state association record; Obtain aerial survey camera parameter information; wherein, the aerial survey camera parameter information includes at least image width information and horizontal field of view information.

4. The UAV aerial survey control method for geological exploration according to claim 1, characterized in that, Based on the real-time flight status information, the current position mileage of the UAV on the reference centerline corresponding to the wall control profile table is determined. Lateral distance target, yaw heading target, forward velocity target, and safe bandwidth are extracted from the wall control profile table to form control targets, including: Projection positioning processing is performed based on the current position of the UAV in real-time flight status information and the reference center line to determine the current position mileage of the UAV on the reference center line. Based on the current position mileage, a lookup or interpolation process is performed in the wall control profile table to obtain the lateral distance target, yaw heading target, forward speed target, and safe bandwidth corresponding to the current position mileage; The lateral distance target, the yaw heading target, the forward velocity target, and the safety bandwidth are combined to form the control target.

5. The UAV aerial survey control method for geological exploration according to claim 4, characterized in that, Combining the control target with the real-time flight status information, a control error is formed, including: Horizontal deviation calculation is performed based on the current position of the UAV and the reference centerline to obtain the signed lateral distance of the UAV relative to the reference centerline; The lateral error is calculated based on the lateral distance target and the signed lateral distance, and the lateral error is written into the control error.

6. The UAV aerial survey control method for geological exploration according to claim 5, characterized in that, Before generating route dynamic adjustment commands and attitude control commands for aerial survey flights based on the control error, the method further includes: performing a comprehensive evaluation based on the lateral error, the orientation error, the reliability of image yaw deviation evidence, and the changing trend of the lateral error to generate a correction mode marker; specifically including: The pixel offset corresponding to the latest aerial survey image is obtained based on the image state association record, and the reliability of the image yaw deviation evidence is generated based on the edge response statistics. The change in lateral error is calculated based on the lateral error at adjacent control cycle times. The lateral error, the orientation error, the reliability of the image yaw deviation evidence, and the change in lateral error are input into the risk scoring model to obtain a risk score. Based on the risk score and the correction threshold, a correction determination is performed to generate a correction pattern label; Specifically, a strong correction mode marker is generated when the risk score reaches the strong correction threshold or the absolute value of the pixel offset reaches the image misalignment threshold; and a flexible correction mode marker is generated when the risk score is below the strong correction threshold and the flexible correction condition is met.

7. The UAV aerial survey control method for geological exploration according to claim 6, characterized in that, Based on the control error, attitude control commands for aerial survey flights are generated, including: Based on the orientation error, a proportional conversion process is performed to generate a yaw command increment, and a yaw control command is generated based on the current yaw information and the yaw command increment. The yaw control command is subjected to rate of change limitation processing or range limitation processing to generate an executable yaw control command, and the executable yaw control command is output to the UAV flight control execution.

8. The UAV aerial survey control method for geological exploration according to claim 7, characterized in that, Based on the control error, dynamic route adjustment commands for aerial survey flights are generated, including: In flexible correction mode, a proportional conversion process is performed based on the lateral error to generate a lateral speed control command; in strong correction mode, a forced lateral speed control command is generated based on the sign of the lateral error and a preset lateral speed upper limit. Based on the forward velocity target, a forward velocity control command is generated, and the lateral velocity control command and the forward velocity control command are output to the UAV flight control execution.

9. A UAV aerial survey control system for geological exploration, characterized in that, The system is used to execute the UAV aerial survey control method for geological exploration as described in any one of claims 1-8, and the system includes: The acquisition unit is used to acquire historical wall-direction aerial survey control profile data for wall-hugging aerial surveys, and to establish a wall-direction control profile table based on the historical wall-direction aerial survey control profile data. A unit is established to acquire real-time flight status information and aerial survey image information of the UAV during the aerial survey process, and to establish an image status association record based on the real-time flight status information and the aerial survey image information; The forming unit is used to determine the current position mileage of the UAV on the reference centerline corresponding to the wall control profile table based on the real-time flight status information, and extract the lateral distance target, yaw orientation target, forward velocity target and safe bandwidth from the wall control profile table to form the control target; The extraction unit is used to extract yaw deviation evidence from the image based on the image state association record, and combine the control target and the real-time flight state information to form a control error; The execution unit is used to generate dynamic route adjustment commands and attitude control commands for aerial survey flights based on the control error, and output the dynamic route adjustment commands and attitude control commands to the UAV flight control execution, so that the UAV can dynamically adjust its flight route and flight attitude during the aerial survey process.

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