Hyperspectral push-broom route planning method, device and equipment and storage medium
By calculating the theoretical missing length of turning waypoints in river monitoring and inserting compensating waypoints, an optimized UAV operation route is generated, which solves the problems of data omission and redundancy in river monitoring and achieves efficient river coverage and data collection.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-16
- Publication Date
- 2026-03-31
AI Technical Summary
In existing technologies for river monitoring, pushbroom hyperspectral imaging UAVs suffer from issues such as data omissions and redundant data in their flight path planning, making it difficult to balance the integrity of river coverage with data collection efficiency.
By detecting the turning angle of waypoints, calculating the theoretical missed sampling length, and inserting compensation waypoints into the initial route, an optimized operational route is generated. Combined with speed control and operational status management, a river scanning route with no omissions is formed.
It achieved full coverage scanning of the river channel, avoided redundant data collection, improved monitoring efficiency and data quality, reduced path redundancy, and improved the economy of route planning.
Smart Images
Figure CN121761895A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of unmanned aerial vehicle (UAV) flight path planning, and in particular to a hyperspectral pushbroom flight path planning method, apparatus, equipment, and storage medium. Background Technology
[0002] Hyperspectral remote sensing technology can acquire detailed spectral information of ground objects and is indispensable in fields such as river monitoring. Unmanned aerial vehicles (UAVs) equipped with pushbroom hyperspectral imagers have become a key means of detailed remote sensing monitoring of rivers due to their maneuverability, low cost, and high resolution. Pushbroom instruments obtain two-dimensional images by continuously scanning perpendicular to the flight path and stitching the images together; therefore, the UAV's flight path planning directly determines the completeness and efficiency of data acquisition.
[0003] Existing pushbroom hyperspectral imaging UAVs typically employ a parallel navigation mode along the river's centerline when planning river scanning routes. An initial route, aligned with the river's centerline, is generated based on a digital elevation model or map data. The UAV then collects data by flying along waypoints at a fixed altitude and speed. However, this existing parallel navigation mode has drawbacks: in river bends, sudden changes in the UAV's course can create fan-shaped missed data areas, leading to data stitching failures. Furthermore, current technologies often significantly increase the route overlap rate to prevent missed data collection, generating substantial redundant data and impacting monitoring efficiency.
[0004] Existing technologies struggle to balance the integrity of river coverage with data collection efficiency. Therefore, a new route planning method is urgently needed to improve operational efficiency while ensuring complete river data collection. Summary of the Invention
[0005] In view of this, embodiments of the present invention provide a hyperspectral push-broom route planning method, apparatus, equipment and storage medium to completely acquire hyperspectral data of river bends and reduce redundant operations.
[0006] In a first aspect, embodiments of the present invention provide a hyperspectral pushbroom path planning method, comprising: Obtain the UAV's flight scan parameters and initial flight path; The turning angle corresponding to each waypoint on the initial flight path is detected, and the theoretical missed sampling length of each waypoint is determined based on the flight scan parameters and the turning angle. Based on the initial route and the theoretical under-collection length of each turning waypoint, determine the compensation waypoint corresponding to each turning waypoint; The UAV operation route is generated based on the initial route and the compensated waypoints.
[0007] In one possible implementation, the flight scanning parameters include flight altitude and scanning field of view. The step of determining the theoretical missed sampling length for each waypoint based on the flight scan parameters and the turning angle includes: Calculate the flight path scanning width based on the flight altitude and the scanning field of view; Based on the turning angle and the route scan width, calculate the theoretical missed sampling length for each turning waypoint.
[0008] In one possible implementation, determining the compensation waypoint corresponding to each turning waypoint based on the initial route and the theoretical under-collection length of each turning waypoint includes: For each waypoint, determine the target route from the previous waypoint to that waypoint; On the extension line of the target route, at a distance equal to the theoretical under-collection length from the turning waypoint, determine the compensation waypoint for the turning waypoint.
[0009] In one possible implementation, generating the UAV operation route based on the initial route and the compensated waypoints includes: The compensation waypoint corresponding to each turning waypoint is inserted between the turning waypoint and the waypoint preceding the turning waypoint in the initial route to obtain the UAV operation route.
[0010] In one possible implementation, generating the UAV operation route based on the initial route and the compensated waypoints further includes: At each waypoint, at the compensation waypoint, on the flight segment leading to that waypoint, the operation status of the hyperspectral imager in the UAV is set to off; For the remaining segments of the flight, set the hyperspectral imager in the UAV to be operational.
[0011] In one possible implementation, calculating the theoretical missed length for each waypoint based on the turning angle and the route scan width includes: according to Calculate the theoretical missing length; where For turning waypoints The theoretical length of missed sampling, The scan width of the flight path, For turning waypoints The corresponding angle size.
[0012] In one possible implementation, the flight scan parameters further include the number of scan line pixels and the scan rotation speed; the method further includes: The maximum permissible flight speed of the UAV on the UAV operation route is determined based on the scan width of the flight path, the number of pixels in the scan line, and the scan rotation speed.
[0013] Secondly, embodiments of the present invention provide a hyperspectral pushbroom path planning device, comprising: The parameter acquisition module is used to acquire the UAV's flight scan parameters and initial flight path; The missing data length module is used to detect the turning angle size corresponding to each turning waypoint on the initial route, and determine the theoretical missing data length of each turning waypoint based on the flight scan parameters and the turning angle size; The waypoint compensation module is used to determine the compensation waypoint corresponding to each waypoint based on the initial route and the theoretical under-collection length of each waypoint. The operation route generation module is used to generate the UAV operation route based on the initial route and the compensation waypoints.
[0014] Thirdly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores a computer program and the processor executes the steps of the method as described in the first aspect or any implementation thereof.
[0015] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in the first aspect or any implementation thereof.
[0016] The beneficial effects of the embodiments of the present invention compared with the prior art are as follows: In this embodiment of the invention, the turning angle corresponding to each turning waypoint on the initial route is detected. Based on the flight scan parameters and the turning angle, the theoretical missed sampling length of each turning waypoint is determined, quantifying the range of the missed sampling area and avoiding the blindness of missing sampling compensation. Based on the initial route and the theoretical missed sampling length of each turning waypoint, a compensation waypoint corresponding to each turning waypoint is determined. Based on the quantified missed sampling length and the UAV flight path, compensation waypoints are set at river bends, providing core assurance for full river coverage scanning. Based on the initial route and compensation waypoints, a UAV operation route is generated, forming a river scanning route that balances operational efficiency and complete coverage. This embodiment of the invention generates an optimized operation route by combining UAV flight scan parameters and initial route data, quantifying the missed sampling length by turning waypoint angles, and accurately matching compensation waypoints. This achieves complete river coverage while avoiding path redundancy caused by blindly adding waypoints, improving the efficiency and economy of route planning. Attached Figure Description
[0017] Figure 1 This is a schematic diagram illustrating the implementation process of a hyperspectral pushbroom route planning method provided in an embodiment of the present invention; Figure 2This is a schematic diagram of an initial flight path provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the theoretical missed sampling length and compensation waypoints provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of an unmanned aerial vehicle (UAV) operation route provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of a hyperspectral pushbroom route planning device provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation
[0018] The present application will be described more clearly below with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the function of the present application, but do not limit the present application in any way. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application. These all fall within the protection scope of the present application.
[0019] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.
[0020] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.
[0021] In the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0022] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.
[0023] Furthermore, the term "multiple" mentioned in the embodiments of this application should be interpreted as two or more.
[0024] In hyperspectral remote sensing monitoring of rivers, drones equipped with pushbroom hyperspectral imagers are commonly used to collect data. These instruments perform continuous scanning along a scan line perpendicular to the flight direction, then stitch the data together to form a complete river image. In practice, existing solutions are mostly based on digital elevation models or map data, planning drone flight paths along the river's centerline and controlling the drone to fly at a fixed altitude and speed along waypoints. However, natural rivers have many bends. When the drone flies past waypoints in a bend, its course suddenly changes. Since the pushbroom's scanning direction remains perpendicular to the flight direction, this results in fan-shaped missed areas at bends, directly causing breaks in the hyperspectral data stitching. To avoid these missed areas, operators often significantly increase the flight path overlap rate, setting up parallel supplementary flight paths to the left and right of the river's centerline. This, in turn, leads to repeated scanning of straight sections, generating massive amounts of redundant data, wasting drone power and storage space, and reducing operational efficiency.
[0025] Therefore, existing methods cannot balance the need for river coverage integrity and high efficiency of data collection. Developing a hyperspectral push-broom route planning method that accurately solves the problem of missed data collection at bends without adding excessive redundancy has important practical significance and application value.
[0026] See Figure 1 This invention provides a hyperspectral pushbroom path planning method, detailed below: Step S101: Obtain the flight scan parameters and initial flight path of the UAV.
[0027] Here, flight scanning parameters include the UAV's flight parameters and the scanning parameters of the hyperspectral imager mounted on the UAV. For example, flight parameters include, but are not limited to, flight altitude and speed, while scanning parameters include, but are not limited to, scanning field of view, number of pixels per scan line, and scanning rotation speed.
[0028] In one possible implementation, the method for obtaining the initial flight path includes: Based on the geographical data of the river to be monitored, determine the centerline of the river to be monitored; Based on the inflection point of the centerline of the river to be monitored, multiple turning points and their corresponding coordinates are determined.
[0029] Waypoints are the core basic units for route planning and flight control in navigation scenarios such as aviation, navigation, and drones. They are used to connect and form a complete route, guiding the carrier (aircraft, ships, drones, etc.) to achieve fixed-point flight and path turning. In addition to turning waypoints determined based on the turning point of the river centerline, the initial route can also include waypoints with different functions or locations, such as origin and destination waypoints and straight-line positioning waypoints. In this solution, determining turning waypoints based on the turning point of the river centerline is only one part of the initial route construction. The initial route can also incorporate other waypoints according to actual monitoring needs to ensure that the route can fully adapt to the complex scenarios of river monitoring.
[0030] By determining the turning point and coordinates based on the inflection point of the river centerline, the initial route accurately matches the location and direction of the river to be monitored, ensuring that the route covers the target monitoring area.
[0031] Step S102: Detect the turning angle size corresponding to each turning waypoint on the initial route, and determine the theoretical missed sampling length of each turning waypoint based on the flight scan parameters and the turning angle size.
[0032] The waypoint angle refers to the angle by which the heading angle changes when an aircraft turns between two adjacent segments. Figure 2 This is a schematic diagram of the initial flight path hyperspectral imager scanning range and missed areas provided in an embodiment of the present invention, as shown below. Figure 2 As shown, the scanning range of the pushbroom hyperspectral imager is to both sides of the initial flight path, and the width is the scanning width. The rectangular projection range at the waypoint , , and At this location, the pushbroom hyperspectral imager exhibits a fan-shaped missed sampling area.
[0033] In one possible implementation, the theoretical missed sampling length for each waypoint is determined based on flight scan parameters and turn angle, including: Calculate the scan width of the flight path based on the flight altitude and the scanning field of view; Calculate the theoretical missed length for each waypoint based on the turning angle and the scan width of the route.
[0034] like Figure 3 As shown, This is the theoretical missed detection length calculated in this embodiment. This embodiment first calculates the scan width using flight altitude and field of view, then combines this with the turning angle to quantify the missed detection length, achieving quantitative analysis of the missed detection range at each turning waypoint and avoiding ambiguity in missed detection assessment.
[0035] Step S103: Determine the compensation waypoint corresponding to each turning waypoint based on the initial route and the theoretical under-collection length of each turning waypoint.
[0036] In one possible implementation, the compensation waypoint for each turning waypoint is determined based on the initial route and the theoretical under-collection length of each turning waypoint, including: For each waypoint, determine the target route from the previous waypoint to that waypoint; On the extension of the target route, at a distance equal to the theoretical under-collection length from the turning waypoint, determine the compensation waypoint for the turning waypoint.
[0037] like Figure 3 As shown, at waypoints Distance on the extended line for Location settings encrypted waypoints When operating, the drone is controlled to fly to encrypted waypoints. To achieve Coverage collection of the missed sampling area. This embodiment of the invention uses the direction in which the UAV flies from the previous waypoint to the current turning waypoint in the initial flight path as a basis. Based on the theoretical missed sampling length, a compensation waypoint is accurately located on the extended flight segment line to ensure that the scanning operation range of the compensation waypoint can cover the theoretical missed sampling area.
[0038] Step S104: Generate the UAV operation route based on the initial route and the compensation waypoints.
[0039] In one possible implementation, the UAV operation route is generated based on the initial route and compensated waypoints, including: The compensation waypoint corresponding to each turning waypoint is inserted into the initial route between that turning waypoint and the waypoint preceding that turning waypoint to obtain the UAV operation route.
[0040] Assuming the initial route is When a certain waypoint is turned Corresponding compensation waypoints Insert into and After that, the waypoint execution order of the drone operation route changed to: Push-broom hyperspectral analyzers can be used in... to The entire flight segment was covered by hyperspectral data collection of areas missed during the initial flight path.
[0041] In the optimized flight path, the drone executes a "push-sweep-reverse-push-sweep" flight pattern: Forward push-broom phase: from the waypoint of the initial route fly to the compensation waypoint The hyperspectral analyzer is turned on to perform push-broom data acquisition to ensure full coverage without any missed samples; Retreat transition segment: from the compensation waypoint Return to the waypoint of the initial route ; Next forward push-broom phase: from the waypoint of the initial route Continue flying to the next waypoint or compensation waypoint, restart the hyperspectral imager operation, and perform push-broom data acquisition to ensure full coverage and no missed data.
[0042] In this embodiment of the invention, a compensation waypoint is inserted between the corresponding turning waypoint and the previous waypoint to form an operational route that can completely scan the river channel. Without changing the collection range of the initial route, it ensures that the missed areas are accurately covered, and the collected data is continuous and covered without blind spots.
[0043] In this embodiment of the invention, the turning angle corresponding to each turning waypoint on the initial route is detected. Based on the flight scan parameters and the turning angle, the theoretical missed sampling length of each turning waypoint is determined, quantifying the range of the missed sampling area and avoiding the blindness of missing sampling compensation. Based on the initial route and the theoretical missed sampling length of each turning waypoint, a compensation waypoint corresponding to each turning waypoint is determined. Based on the quantified missed sampling length and the UAV flight path, compensation waypoints are set at river bends, providing core assurance for full river coverage scanning. Based on the initial route and compensation waypoints, a UAV operation route is generated, forming a river scanning route that balances operational efficiency and complete coverage. This embodiment of the invention generates an optimized operation route by combining UAV flight scan parameters and initial route data, quantifying the missed sampling length by turning waypoint angles, and accurately matching compensation waypoints. This achieves complete river coverage while avoiding path redundancy caused by blindly adding waypoints, improving the efficiency and economy of route planning.
[0044] In some embodiments, during the process of the UAV returning from the compensated waypoint to the corresponding turning waypoint (i.e., the aforementioned back-off transition segment: from the compensated waypoint) Return to the waypoint of the initial route Since the flight path overlaps with the already scanned area, continuous scanning will generate redundant data. However, the compensation waypoint has already filled in the missed areas at the turning waypoint, and the flight path is connected when returning to the turning waypoint, without the need for additional data collection. Therefore, the scanning operation during UAV flight can be set as follows: Compensation waypoints corresponding to each turning waypoint to that turning point For the flight segment, set the operation status of the hyperspectral imager in the UAV to off; For the remaining segments of the flight, set the hyperspectral imager in the UAV to be operational.
[0045] The embodiments of the present invention not only avoid redundant data collection in overlapping areas, but also ensure the integrity of coverage of missed areas and the efficiency of route connection, thereby improving the operational efficiency and data quality of hyperspectral monitoring of rivers.
[0046] In some embodiments, the turning angles of turning points differ for river channels with varying degrees of curvature. The missed sampling length changes with the turning angle and the line scan width, and cannot be estimated empirically. Therefore, calculating the theoretical missed sampling length for each turning point based on the turning angle and the line scan width can include: according to Calculate the theoretical missing length; where For turning waypoints The theoretical length of missed sampling, For the width of the flight path scan, For turning waypoints The corresponding angle size.
[0047] The embodiments of the present invention can accurately calculate the theoretical uncollected length of turning points in rivers with different degrees of curvature and shape, avoiding the errors of empirical estimation.
[0048] In some embodiments, if the flight speed of the UAV exceeds the data acquisition and processing capabilities of the scanner, the scan line may not be able to completely cover the monitoring area, resulting in discontinuous or even failed data acquisition. Therefore, it is necessary to constrain the flight speed of the UAV on the flight path. Thus, this method can determine the maximum permissible flight speed of the UAV on the UAV operation flight path based on the scan width of the flight path, the number of pixels in the scan line, and the scan rotation speed.
[0049] In actual drone flights, by controlling the drone's flight speed to not exceed the maximum permissible flight speed, data errors caused by exceeding the scanning operation capacity are avoided, thus ensuring the integrity and effectiveness of hyperspectral data acquisition.
[0050] In this embodiment of the invention, by quantifying the missed sampling length of turning waypoints, accurately setting compensation waypoints and integrating them into the operation route, the entire river area is scanned without omissions. At the same time, the path redundancy caused by blindly adding waypoints is avoided, and the integrity of coverage and the rationality of the route are taken into account. Combined with operation status control and speed constraints, redundant data collection in overlapping areas is reduced, and the effectiveness of hyperspectral data is ensured, ultimately improving the operation efficiency and data quality of river monitoring.
[0051] Based on the above, the hyperspectral push-broom flight path planning method is explained in detail below: (1) Obtain the flight scan parameters and initial flight path of the UAV.
[0052] The UAV flight platform used in this embodiment of the invention can be a quadcopter UAV, equipped with a GPS positioning module, an inertial measurement unit, and a flight controller, with a wingspan of 2-3 meters and a weight of 5-15 kg. The UAV is connected to the hyperspectral imager controller via an onboard computer, providing a stable flight platform for the pushbroom hyperspectral imager, and can fly automatically along a planned route. When performing river monitoring tasks, the UAV can receive route commands and adjust its flight attitude and speed in real time.
[0053] The pushbroom hyperspectral imager used in this embodiment of the invention may include a spectral dispersive device, a linear array detector, an optical lens, and a scanning control unit. Its overall dimensions are approximately 200×150×100mm, and it weighs 2-5kg. Mounted on the underside of a UAV, with the lens pointing vertically downwards, it uses a prism or grating to disperse the incident light, and then a linear array detector synchronously acquires spectral data. The pushbroom hyperspectral imager can acquire continuous spectral information of river water bodies and generate a hyperspectral data cube.
[0054] The acquired UAV flight scan parameters may include the UAV's flight altitude. Hyperspectral scanning field of view The number of pixels N per scan line, and the scanning speed of the hyperspectral analyzer. .
[0055] according to and Calculate the scan width of a single flight path. .
[0056]
[0057] according to , and Calculate the maximum permissible flight speed of the drone. And set the flight speed .
[0058]
[0059] Based on digital elevation models or map data, a route is generated that aligns with the centerline of the river to be monitored and consists of a series of continuous waypoints. The initial route formed, each waypoint Includes east and north coordinates .
[0060] Figure 2 This is a schematic diagram of the scanning range and missed areas of the hyperspectral imager provided in an embodiment of the present invention. The scanning range of the pushbroom hyperspectral imager is on both sides of the initial flight path, and the width is the scanning width. The rectangular projection range at the waypoint , , and At this location, the pushbroom hyperspectral imager exhibits a fan-shaped missed sampling area.
[0061] (2) Detect the turning angle size corresponding to each turning waypoint on the initial route, and determine the theoretical missing length of each turning waypoint based on the flight scan parameters and the turning angle size.
[0062] The drone sequentially traverses the internal waypoints in the initial flight path. ( ), calculate at waypoints The corner that is, vector with vector The angle between them.
[0063]
[0064] Turns at the initial and final waypoints of the initial route and Set it to 0.
[0065] According to the corner and scan width Calculate the theoretical undermining length The calculation formula is:
[0066] (3) Determine the compensation waypoint corresponding to each turning waypoint based on the initial route and the theoretical under-collection length of each turning waypoint.
[0067] at the waypoint arrive Distance on the extended line for Location settings encrypted waypoints . The coordinate calculation method is as follows: Depend on and Calculate the angle between vectors :
[0068] Angle between vectors and theoretical undermining length Calculate encrypted waypoints Coordinates:
[0069]
[0070] Figure 3 This is a schematic diagram illustrating the theoretical missed sampling length and compensation waypoints provided in an embodiment of the present invention. For turning waypoints... According to vector with vector Determine the corner The theoretical undermining length was calculated. At the waypoint arrive Distance on the extended line for Location settings encrypted waypoints .vector The angle between the x-axis and the positive x-axis direction is ,according to Sure coordinates .
[0071] (4) Generate the UAV operation route based on the initial route and the compensation waypoint.
[0072] Figure 4 This is a schematic diagram of the unmanned aerial vehicle (UAV) operation route provided in an embodiment of the present invention. Insert into and The drone operation route is obtained from this information, and the waypoint execution order of the drone operation route is as follows: Push-broom hyperspectral analyzers can be used in... to The entire flight segment was covered by hyperspectral data collection of areas missed during the initial flight path.
[0073] The drone's flight control system loads the final optimized flight path sequence to maintain flight speed. It is 0.8 ; In the optimized flight path, the drone executes a "push-sweep-reverse-push-sweep" flight pattern: Forward push-broom phase: from the waypoint of the initial route fly to the compensation waypoint The hyperspectral analyzer is turned on to perform push-broom data acquisition to ensure full coverage without any missed samples; Retreat transition segment: from the compensation waypoint Return to the waypoint of the initial route Change the flight direction, shut down the hyperspectral instrument, stop pushbroom data acquisition, avoid repeated scanning of the same area, and save storage space and battery power; Next forward push-broom phase: from the waypoint of the initial route Continue flying to the next compensation waypoint The hyperspectral analyzer was restarted to perform push-broom data acquisition, ensuring full coverage and no missed data.
[0074] (5) Drones are used to scan the river channel.
[0075] The drones perform flight missions along the operational routes and collect data; After landing, the drone downloads hyperspectral data for further processing and analysis.
[0076] In this embodiment of the invention, by accurately calculating the scanning width, turning point angle, and theoretical missed sampling length, compensation waypoints are added to the initial route, effectively filling the fan-shaped missed sampling area in the river bend and achieving full coverage of hyperspectral data acquisition. Combined with speed constraints and the "push-scan-back-push-scan" operation mode, the integrity and effectiveness of data acquisition are ensured, while avoiding redundant data caused by repeated scanning, thus improving the efficiency and economy of river monitoring.
[0077] See Figure 5 This invention provides a hyperspectral pushbroom path planning device 5, comprising: The parameter acquisition module 51 is used to acquire the flight scan parameters and initial flight path of the UAV. The missing data length module 52 is used to detect the turning angle size corresponding to each turning waypoint on the initial route, and determine the theoretical missing data length of each turning waypoint based on the flight scan parameters and the turning angle size; The waypoint compensation module 53 is used to determine the compensation waypoint corresponding to each waypoint based on the initial route and the theoretical under-collection length of each waypoint. The operation route generation module 54 is used to generate the UAV operation route based on the initial route and compensation waypoints.
[0078] In one possible implementation, the missing data length module 52 is used to calculate the line scan width based on the flight altitude and the scanning field of view. Calculate the theoretical missed length for each waypoint based on the turning angle and the scan width of the route.
[0079] In one possible implementation, waypoint compensation module 53 is used to determine, for each turning waypoint, the target flight segment from the previous waypoint to the turning waypoint; On the extension of the target route, at a distance equal to the theoretical under-collection length from the turning waypoint, determine the compensation waypoint for the turning waypoint.
[0080] In one possible implementation, the operation route generation module 54 is used to insert the compensation waypoint corresponding to each turning waypoint into the initial route between the turning waypoint and the waypoint preceding the turning waypoint, so as to obtain the UAV operation route.
[0081] In one possible implementation, the operation route generation module 54 is also used to set the operation status of the hyperspectral imager in the UAV to off for each compensation waypoint corresponding to each turning waypoint and the segment of flight to that turning waypoint. For the remaining segments of the flight, set the hyperspectral imager in the UAV to be operational.
[0082] In one possible implementation, the missing data length module 52 is also used to determine the missing data length based on... Calculate the theoretical missing length; where For turning waypoints The theoretical length of missed sampling, For the width of the flight path scan, For turning waypoints The corresponding angle size.
[0083] In this embodiment of the invention, the hyperspectral push-broom route planning device completes the acquisition of flight parameters and routes, quantification of missed sampling length, positioning of compensation waypoints, and generation of operation routes through modular collaboration, achieving full-area scanning of the river without omissions, while avoiding path redundancy caused by blindly adding waypoints. Combined with operation status control, it further improves the accuracy of compensation scanning and the effectiveness of data acquisition, ultimately optimizing the operation efficiency and data quality of hyperspectral monitoring of the river.
[0084] See Figure 6 The diagram shows a schematic of the electronic device 6 provided in an embodiment of the present invention, which is described in detail below: like Figure 6 As shown, the electronic device 6 of this embodiment includes a processor 60 and a memory 61. The memory 61 stores a computer program 62. When the processor 60 executes the computer program 62, it implements the steps in the various method embodiments described above. Alternatively, when the processor 60 executes the computer program 62, it implements the functions of each module in the various device embodiments described above.
[0085] For example, computer program 62 may be divided into one or more modules / units, which are stored in memory 61 and executed by processor 60 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 62 in electronic device 6.
[0086] Electronic device 6 may include, but is not limited to, processor 60 and memory 61. Those skilled in the art will understand that... Figure 6 This is merely an example of electronic device 6 and does not constitute a limitation on electronic device 6. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device 6 may also include input / output devices, network access devices, buses, etc.
[0087] Electronic device 6 can be an embedded computer integrated into the UAV or a ground control station. It can run flight path optimization algorithms, receive river geography data and determine the initial flight path, calculate turning angles and missed sampling lengths in real time, dynamically adjust the flight path, and output an optimized UAV operational flight path to ensure full coverage monitoring of the river and avoid data loss in river bends. Electronic device 6 can also receive scanning commands from the UAV flight controller, control the power switch of the hyperspectral imager, and automatically turn data acquisition on or off based on the scanning markers of the flight path segment. During the forward push-broom phase, electronic device 6 turns on the hyperspectral imager and begins data acquisition; during the reversal transition phase, electronic device 6 turns off the hyperspectral imager and stops data acquisition to save storage space.
[0088] The processor 60 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.
[0089] The memory 61 can be an internal storage unit of the electronic device 6, such as a hard disk or RAM. The memory 61 can also be an external storage device of the electronic device 6, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 61 can include both internal and external storage units of the electronic device 6. The memory 61 is used to store the computer program 62 and other programs and data required by the electronic device 6. The memory 61 can also be used to temporarily store data that has been output or will be output.
[0090] For the sake of simplicity and clarity, only the above-described functional modules / units are used as examples. In practical applications, the functions described above can be assigned to different functional modules / units as needed. These modules / units can be implemented in hardware, software, or a combination of both.
[0091] This invention also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the methods described in the above-described method embodiments.
[0092] This invention also provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the methods described in the above-described method embodiments.
[0093] Computer programs include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. Computer-readable media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.
[0094] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not detailed or described in a particular embodiment can be referred to in the relevant descriptions of other embodiments. Unless otherwise specified or in conflict with logic, the terminology and / or descriptions between different embodiments are consistent and can be referenced interchangeably. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.
[0095] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.
Claims
1. A hyperspectral pushbroom flight path planning method, characterized in that, include: Obtain the UAV's flight scan parameters and initial flight path; The turning angle corresponding to each waypoint on the initial flight path is detected, and the theoretical missed sampling length of each waypoint is determined based on the flight scan parameters and the turning angle. Based on the initial route and the theoretical under-collection length of each turning waypoint, determine the compensation waypoint corresponding to each turning waypoint; The UAV operation route is generated based on the initial route and the compensated waypoints.
2. The hyperspectral pushbroom path planning method according to claim 1, characterized in that, The flight scanning parameters include flight altitude and scanning field of view; The step of determining the theoretical missed sampling length for each waypoint based on the flight scan parameters and the turning angle includes: Calculate the flight path scanning width based on the flight altitude and the scanning field of view; Based on the turning angle and the route scan width, calculate the theoretical missed sampling length for each turning waypoint.
3. The hyperspectral pushbroom path planning method according to claim 1, characterized in that, The step of determining the compensation waypoint corresponding to each turning waypoint based on the initial route and the theoretical under-collection length of each turning waypoint includes: For each waypoint, determine the target route from the previous waypoint to that waypoint; On the extension line of the target route, at a distance equal to the theoretical under-collection length from the turning waypoint, determine the compensation waypoint for the turning waypoint.
4. The hyperspectral pushbroom flight path planning method according to any one of claims 1-3, characterized in that, The step of generating a UAV operation route based on the initial route and the compensated waypoints includes: The compensation waypoint corresponding to each turning waypoint is inserted between the turning waypoint and the waypoint preceding the turning waypoint in the initial route to obtain the UAV operation route.
5. The hyperspectral pushbroom path planning method according to claim 4, characterized in that, The step of generating the UAV operation route based on the initial route and the compensated waypoints further includes: At each waypoint, at the compensation waypoint, on the flight segment leading to that waypoint, the operation status of the hyperspectral imager in the UAV is set to off; For the remaining segments of the flight, set the hyperspectral imager in the UAV to be operational.
6. The hyperspectral pushbroom path planning method according to claim 2, characterized in that, The step of calculating the theoretical missed sampling length for each turning waypoint based on the turning angle and the route scan width includes: according to Calculate the theoretical missing length; where For turning waypoints The theoretical length of missed sampling, The scan width of the flight path, For turning waypoints The corresponding angle size.
7. The hyperspectral pushbroom path planning method according to claim 2, characterized in that, The flight scanning parameters also include the number of pixels per scan line and the scanning rotation speed; the method further includes: The maximum permissible flight speed of the UAV on the UAV operation route is determined based on the scan width of the flight path, the number of pixels in the scan line, and the scan rotation speed.
8. A hyperspectral pushbroom flight path planning device, characterized in that, include: The parameter acquisition module is used to acquire the UAV's flight scan parameters and initial flight path; The missing data length module is used to detect the turning angle size corresponding to each turning waypoint on the initial route, and determine the theoretical missing data length of each turning waypoint based on the flight scan parameters and the turning angle size; The waypoint compensation module is used to determine the compensation waypoint corresponding to each waypoint based on the initial route and the theoretical under-collection length of each waypoint. The operation route generation module is used to generate the UAV operation route based on the initial route and the compensation waypoints.
9. An electronic device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method as described in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 7.