An aircraft altitude maintenance method, apparatus, device, and medium

Abstract

This invention discloses a method, apparatus, equipment, and medium for maintaining aircraft altitude, relating to the field of UAV altitude maintenance technology. The system employs a ground-air cooperative system composed of a UAV and an unmanned vehicle, effectively broadening the field of vision. Working together, they can perform tasks such as indoor and outdoor reconnaissance and emergency rescue. Simultaneously, a large-capacity battery on the ground ensures the UAV's long-term loiter time, improving operational duration and efficiency. The use of a single-point lidar ensures high precision (centimeter-level), offering higher accuracy and less environmental constraint compared to traditional barometers and GPS altitude setting, and allowing for both indoor and outdoor use. Compared to traditional terrain-following methods, an altitude de-alteration method is employed to remove most of the impact of terrain changes on the UAV's altitude. Furthermore, an adaptive weighted recursive mean filtering method is introduced, enabling the UAV to maintain a constant altitude with the unmanned vehicle even under terrain-changing conditions.

Description

Technical Field

[0001] This invention relates to the field of drone altitude maintenance technology, and in particular to a method, apparatus, equipment and medium for maintaining the altitude of an aircraft in a ground-air cooperative system under terrain changes. Background Technology

[0002] Compared to other ground robots, drones have advantages such as convenience and speed, but they also have disadvantages such as poor stability, especially altitude control, which greatly affects the stable flight of drones. Altitude hold, as a crucial part of stable drone flight, provides a prerequisite for the next complex tasks of drones, such as indoor and outdoor positioning, tracking, and path planning.

[0003] The altitude hold function of drones utilizes different sensors depending on the usage scenario. Outdoors, sensors that provide absolute altitude data, such as GPS and barometers, are typically used. Indoors, sensors such as barometers and laser rangefinders are commonly used; alternatively, a fusion method combining barometers, accelerometers, and GPS can be employed. Among these methods, barometers are highly susceptible to wind interference, resulting in significant altitude data drift in complex environments such as indoors; GPS accuracy is low and is limited by signal strength, rendering it unusable in areas with weak or no signal; laser rangefinders offer high accuracy but use relative distance as altitude, leading to abrupt changes in altitude data on uneven ground; and multi-sensor fusion, with its numerous sensors, places a heavy burden on small, low-payload drones, resulting in low efficiency and significant data fluctuations due to variations in the environments to which the sensors are adapted.

[0004] The prior art provides an adaptive motion planning method for quadrotor aircraft based on terrain following. It uses lidar to acquire terrain information, employs a Gaussian filtering algorithm for trajectory planning, and establishes a UAV model. The lidar feeds back the terrain undulation information in front and below to the aircraft, enabling it to follow undulating terrain and maintain a consistent distance from the ground even in changing terrain.

[0005] This invention uses a Gaussian filtering algorithm for altitude and trajectory planning. However, Gaussian filtering has a delay problem when processing sensor data, which leads to a delay in altitude control and lag during rapid altitude adjustments, resulting in poor real-time performance. Summary of the Invention

[0006] In view of the above problems, the present invention provides an aircraft altitude maintaining method, apparatus, device and medium for overcoming the above problems or at least partially solving the above problems.

[0007] This invention provides the following solution:

[0008] A method for maintaining the altitude of an aircraft, comprising:

[0009] The method is applied to a ground-to-air cooperative system, which includes a ground-based unmanned vehicle (UAV) and a drone connected by a tethered cable. The drone is equipped with a vertically downward-facing single-point lidar and a camera, and the ground-based UAV is equipped with image markers and an encoder.

[0010] The current distance data of the UAV relative to the ground and the previous distance data collected by the single-point lidar are obtained, and the sudden change threshold is determined.

[0011] The initial UAV relative to the ground altitude data after terrain abrupt change is calculated by using the altitude data demutation model combined with the mutation threshold, the current distance data, and the previous distance data;

[0012] An adaptive weighted recursive mean filtering algorithm is used to process the initial UAV altitude data after the terrain change in real time and smoothness to obtain the target UAV altitude data relative to the ground after the terrain change.

[0013] The encoder measures the length of the pulled-out tether cable and the camera tracks the image marker to obtain the horizontal distance between the UAV and the ground unmanned vehicle. The tether cable catenary model is used to calculate the target UAV relative to the ground unmanned vehicle height data.

[0014] By combining the target UAV's altitude data relative to the ground and the target UAV's altitude data relative to the unmanned vehicle, complementary filtering is used to fuse the data and the resulting fused altitude data is calculated using an algorithm. This fused altitude data is then used as the UAV's altitude-keeping data.

[0015] Preferably, the demutation method of the height data demutation model includes:

[0016] Determine whether the current altitude data of the UAV needs to be processed by comparing the current distance data with a preset mutation threshold.

[0017] After determining that the current altitude data needs to be processed, the difference between the current distance data and the previous distance data is calculated to obtain the distance change value;

[0018] The initial drone's altitude relative to the ground is calculated using the distance change value and the current distance data.

[0019] Preferably: the distance change values ​​are obtained multiple times and summed to obtain the summed distance change value;

[0020] The initial UAV relative to the ground altitude data is obtained by using the summed distance change value and the current distance data.

[0021] Preferably, the processing flow of the adaptive weighted recursive mean filtering algorithm includes:

[0022] The weighting coefficients are determined based on the error between the estimated height and the expected height, and the weighting factors are determined using an inverse proportional function.

[0023] Normalize the weighting coefficients;

[0024] The height data after adaptive weighted recursive filtering is calculated using the normalized weighting coefficients and the initial UAV relative to the ground height data, and is used as the target UAV relative to the ground height data.

[0025] Preferably: the catenary model of the tethered cable obtains the height data of the target UAV relative to the unmanned vehicle by calculating the following formula:

[0026] d s =SC

[0027] In the formula: d s The value represents the height of the target drone relative to the unmanned vehicle, S represents the length of the tethered cable that has been pulled out, and C represents the sag of the cable.

[0028] Preferably, the length S of the pulled-out tethered cable is calculated using the following formula:

[0029]

[0030] The cable sag C is calculated using the following formula:

[0031]

[0032] In the formula: T represents horizontal tension, μ represents cable linear density, g represents gravitational acceleration, sinh represents hyperbolic sine function, and L represents the horizontal distance between the UAV and the unmanned vehicle.

[0033] Preferably, the complementary filtering fusion algorithm is expressed by the following formula:

[0034] h fused =αd stable +(1-α)d s

[0035] Where: h fused d represents the fused height data. stable This represents the target drone's altitude relative to the ground, d. s This represents the altitude of the target drone relative to the unmanned vehicle, and α represents the weighting coefficient.

[0036] An aircraft altitude-keeping device is applied to a ground-air cooperative system, the ground-air cooperative system including a ground unmanned vehicle and an unmanned aerial vehicle connected by a tethered cable, the unmanned aerial vehicle being equipped with a vertically downward single-point lidar and a camera, and the ground unmanned vehicle being equipped with image markers and an encoder; the device, used to execute the aforementioned aircraft altitude-keeping method, includes:

[0037] The data acquisition unit is used to acquire the current distance data of the UAV relative to the ground and the previous distance data collected by the single-point lidar, and to determine the sudden change threshold.

[0038] The demutation unit is used to calculate the initial UAV relative to the ground altitude data after terrain mutation by combining the mutation threshold, the current distance data and the previous distance data with the altitude data demutation model;

[0039] The UAV relative ground height calculation unit is used to perform real-time and smoothness processing on the initial UAV height data after the terrain change using an adaptive weighted recursive mean filtering algorithm to obtain the target UAV relative ground height data after the terrain change.

[0040] The drone-to-unmanned vehicle height calculation unit is used to obtain the length of the tethered cable that has been pulled out by the encoder and the horizontal distance of the drone relative to the ground unmanned vehicle obtained by the camera tracking the image mark, and to calculate the target drone-to-unmanned vehicle height data of the drone relative to the ground unmanned vehicle using the tethered cable catenary model.

[0041] The data fusion unit is used to combine the target UAV's altitude data relative to the ground and the target UAV's altitude data relative to the unmanned vehicle using complementary filtering and fusion algorithms to obtain fused altitude data, and to use the fused altitude data as the altitude-keeping data of the UAV.

[0042] An aircraft altitude-keeping device, the device including a processor and a memory:

[0043] The memory is used to store program code and transmit the program code to the processor;

[0044] The processor is used to execute the above-described aircraft altitude maintaining method according to the instructions in the program code.

[0045] A computer-readable storage medium for storing program code for performing the above-described aircraft altitude-maintaining method.

[0046] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0047] This application provides an aircraft altitude-maintaining method, apparatus, device, and medium. The ground-air cooperative system, composed of a UAV and an unmanned vehicle, effectively broadens the field of view. Working together, they can perform tasks such as indoor and outdoor reconnaissance and emergency rescue. Simultaneously, the large-capacity battery on the ground ensures the UAV's long-term loiter time, improving operational duration and efficiency. The use of a single-point lidar ensures high precision (centimeter-level), offering higher accuracy and less environmental constraint compared to traditional barometers and GPS altitude setting, and can be used both indoors and outdoors. Compared to traditional terrain-following methods, an altitude de-alteration method is employed to remove most of the impact of terrain changes on the UAV's altitude. An adaptive weighted recursive mean filtering method is then introduced to ensure the UAV maintains a constant altitude with the unmanned vehicle even under terrain changes. An encoder is installed on the unmanned vehicle to measure the length of the extended tethered cable. A catenary model is used to simulate the state of the tethered cable in the air, and the UAV's altitude is estimated from the catenary model. This altitude is unaffected by terrain changes. To obtain a more reliable altitude under abrupt terrain changes, the altitude estimated by a single-point lidar and the altitude estimated by the catenary model are fused. Since the single-point lidar has a high frequency and the data obtained from the catenary model has a low frequency, complementary filtering is used to fuse the two sets of data.

[0048] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0050] Figure 1 This is a flowchart of an aircraft altitude maintenance method provided in an embodiment of the present invention;

[0051] Figure 2 This is a schematic diagram of the air-ground cooperative system provided in an embodiment of the present invention;

[0052] Figure 3 This is a schematic diagram of high mutation provided in an embodiment of the present invention;

[0053] Figure 4 This is a schematic diagram illustrating the sudden change in height above the unmanned vehicle platform provided in an embodiment of the present invention;

[0054] Figure 5 This is a schematic diagram of a catenary model of a tethered cable provided in an embodiment of the present invention;

[0055] Figure 6 This is an illustration of the drone's altitude maintenance effect under terrain change conditions provided in an embodiment of the present invention;

[0056] Figure 7 This is a schematic diagram of the AprilTag tag provided in an embodiment of the present invention;

[0057] Figure 8 This is a schematic diagram of an aircraft altitude maintaining device provided in an embodiment of the present invention;

[0058] Figure 9 This is a schematic diagram of an aircraft altitude-maintaining device provided in an embodiment of the present invention. Detailed Implementation

[0059] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention are within the scope of protection of the present invention.

[0060] See Figure 1 This invention provides a method for maintaining the altitude of an aircraft, such as... Figure 1 As shown, this method is applied to a ground-to-air cooperative system, which includes a ground-based unmanned vehicle and a drone connected by a tethered cable. The drone is equipped with a vertically downward-facing single-point lidar and a camera, and the ground-based unmanned vehicle is equipped with image markers and an encoder. The method may include:

[0061] S101: Obtain the current distance data of the UAV relative to the ground and the previous distance data collected by the single-point lidar, and determine the sudden change threshold;

[0062] S102: The initial UAV relative to ground altitude data after terrain abrupt change is calculated by combining the altitude data demutation model with the mutation threshold, the current distance data, and the previous distance data; specifically, the demutation method of the altitude data demutation model provided in this application embodiment includes:

[0063] Determine whether the current altitude data of the UAV needs to be processed by comparing the current distance data with a preset mutation threshold.

[0064] After determining that the current altitude data needs to be processed, the difference between the current distance data and the previous distance data is calculated to obtain the distance change value;

[0065] The initial drone's altitude relative to the ground is calculated using the distance change value and the current distance data.

[0066] Furthermore, the distance change values ​​are obtained multiple times and summed to obtain the summed distance change value;

[0067] The initial UAV relative to the ground altitude data is obtained by using the summed distance change value and the current distance data.

[0068] S103: The initial UAV altitude data after the terrain change is processed in real time and with smoothness using an adaptive weighted recursive mean filtering algorithm to obtain the target UAV's altitude data relative to the ground after the terrain change; specifically, in this application embodiment, the processing flow of the adaptive weighted recursive mean filtering algorithm may include:

[0069] The weighting coefficients are determined based on the error between the estimated height and the expected height, and the weighting factors are determined using an inverse proportional function.

[0070] Normalize the weighting coefficients;

[0071] The height data after adaptive weighted recursive filtering is calculated using the normalized weighting coefficients and the initial UAV relative to the ground height data, and is used as the target UAV relative to the ground height data.

[0072] S104: Obtain the length of the tethered cable measured by the encoder and the horizontal distance of the UAV relative to the ground unmanned vehicle obtained by the camera tracking the image marker, and calculate the target UAV relative to the ground unmanned vehicle height data using the tethered cable catenary model; in specific implementation, this application embodiment can provide the tethered cable catenary model to calculate the target UAV relative to the unmanned vehicle height data using the following formula:

[0073] d s =SC

[0074] In the formula: d s The value represents the height of the target drone relative to the unmanned vehicle, S represents the length of the tethered cable that has been pulled out, and C represents the sag of the cable.

[0075] The length S of the pulled-out mooring cable is calculated using the following formula:

[0076]

[0077] The cable sag C is calculated using the following formula:

[0078]

[0079] In the formula: T represents horizontal tension, μ represents cable linear density, g represents gravitational acceleration, inh represents hyperbolic sine function, and L represents the horizontal distance between the UAV and the unmanned vehicle.

[0080] S105: Combining the target UAV's altitude data relative to the ground and the target UAV's altitude data relative to the unmanned vehicle, complementary filtering is used to fuse the data and the algorithm is used to calculate the fused altitude data. The fused altitude data is then used as the altitude-keeping data for the UAV.

[0081] In a specific implementation, the complementary filtering fusion algorithm described in this application embodiment can be represented by the following formula:

[0082] h fused =αd stable +(1-α)d s

[0083] Where: h fused d represents the fused height data. stable This represents the target drone's altitude relative to the ground, d. s This represents the altitude of the target drone relative to the unmanned vehicle, and α represents the weighting coefficient.

[0084] The aircraft altitude maintenance method provided in this application utilizes a ground-air collaborative system composed of an unmanned vehicle and a tethered drone to perform tasks such as indoor emergency rescue. It also introduces tethering cables, laser ranging modules, and algorithms to ensure that the drone can maintain its current altitude even in the event of sudden terrain changes, thus ensuring system stability.

[0085] The ground-air cooperative system consists of an unmanned vehicle and a tethered drone. The unmanned vehicle and the drone are connected by a tethered cable. The drone is powered by a ground power source to ensure long-term loitering. The drone is equipped with a single-point lidar for altitude acquisition and a camera for reconnaissance. By affixing corresponding patterns to the unmanned vehicle on the ground, the camera recognizes the patterns to track the unmanned vehicle.

[0086] A method for maintaining UAV altitude based on laser ranging is provided. Since the ground-air cooperative system is mainly used for indoor reconnaissance and search and rescue, in order to ensure accurate indoor altitude determination and remove the influence of ground terrain or obstacles on UAV altitude, the altitude is first measured by vertically downward single-point laser radar. Then, an altitude data de-mutation model is introduced, and an adaptive weighted recursive mean filtering algorithm is added to ensure the real-time performance and smoothness of altitude data, so as to ensure that a constant altitude is maintained under the condition of terrain abrupt changes.

[0087] It also provides a method for maintaining the altitude of a drone based on a catenary model with tethered cables. By measuring the length of the released tethered cable using the encoder of the ground-based unmanned vehicle and tracking the image marker on the unmanned vehicle with the camera, the horizontal distance between the drone and the unmanned vehicle can be calculated. Combined with the cable density and the catenary model, the current altitude of the drone can be estimated and used for maintaining the drone's altitude.

[0088] Additionally, a drone altitude-keeping method combining laser and tethered cable fusion is provided. This method uses complementary filtering to fuse processed laser ranging data (high-frequency signal) and altitude calculated based on tethered cable length (low-frequency signal) as the data source for drone altitude-keeping, thereby achieving precise altitude determination.

[0089] The method for maintaining aircraft altitude provided in this application will be described in detail below.

[0090] The aircraft altitude-maintaining method provided in this application embodiment is mainly applied to the ground-air cooperative system of unmanned vehicle 4 and tethered drone 1, such as Figure 2 As shown, the system is used for indoor reconnaissance and search and rescue. Indoors, the drone mainly maintains a constant absolute altitude and carries reconnaissance equipment such as cameras to conduct reconnaissance. Since there is no GPS for altitude setting indoors, and the barometer is greatly affected by wind disturbance, maintaining the precise altitude of the drone for indoor reconnaissance and search and rescue is a challenge.

[0091] This method utilizes a single-point lidar 2 mounted on the bottom of the UAV 1 to measure the relative height with the ground, and introduces an adaptive weighted recursive mean filter. The data after processing by adding the length of the tether cable 3 is used as the height. The two are fused to ensure that the UAV maintains a constant height in complex indoor terrain, removes the influence of ground obstacles on the UAV's height, and the UAV maintains a constant height to track the ground unmanned vehicle 4 to perform related tasks.

[0092] The method provided in this application uses data related to a single-point LiDAR and the length of the tethered cable as the data source for the drone's altitude. Specific embodiments are as follows:

[0093] First, a high-precision single-point lidar based on the Time-of-Flight (ToF) principle, mounted on a drone, is used to measure the relative distance between the drone and the ground. This altitude data is used for drone altitude control. Since this invention is primarily used in indoor reconnaissance, search and rescue, and emergency rescue scenarios, these scenarios are generally complex, with cluttered ground environments that can affect the distance measurement of the vertically downward-facing single-point lidar. This can cause the drone to fluctuate violently, potentially leading to system malfunction. Therefore, this system requires the drone to maintain a constant altitude relative to the unmanned vehicle. Thus, it handles sudden altitude changes due to terrain alterations, such as... Figure 3 , Figure 4 As shown.

[0094] Figure 3 In the diagram, A represents the ground before the mutation, B represents the ground after the mutation, and d represents the ground after the mutation. l For height data before the mutation, d c Δd represents the change in height data before and after the mutation.

[0095] Figure 4 In the diagram, C represents the pre-mutation location, and D represents the post-mutation ground level. l For height data before the mutation, d c Δd represents the change in height data before and after the mutation.

[0096] This application provides a threshold-based method for detecting terrain abrupt changes, enabling UAVs to recognize terrain changes. The relative distance data (i.e., UAV altitude data) obtained by a single-point lidar is then processed, and an adaptive weighted recursive mean filtering algorithm is introduced to further process the altitude data. Finally, the UAV uses the processed altitude data to maintain a stable altitude during flight.

[0097] The specific implementation steps are as follows:

[0098] Step 1: Read the current distance data d of the single-point lidar c A threshold for mutation is given, which can be adjusted as needed. When the terrain change value is less than the threshold, the drone altitude data is not processed, that is, the drone altitude can fluctuate within the threshold range.

[0099] Step 2: Detect any sudden changes in the terrain below the drone and record the current distance data d of the single-point lidar. c and the distance data d at the previous time step l And calculate the absolute value of the difference between the distance data at the current time and the previous time, |d|. c -d l |;The following formula (1) is used to determine whether the terrain changes abruptly:

[0100] |d c -d l |>threshold (1)

[0101] If the conditions of formula (1) are met, then the terrain has changed abruptly, and the distance data needs to be processed before being used as UAV altitude data; otherwise, the terrain has not changed abruptly.

[0102] Step 3: Record and calculate the change in distance Δd when the terrain changes abruptly. For a single terrain change, i.e., when the terrain changes only once, the change in distance Δd is calculated as shown in the following formula (2):

[0103] Δ d =d c-d l (2)

[0104] Formula (2) can only guarantee the stable flight of the UAV under a single terrain change, but cannot satisfy the condition of continuous terrain changes. In order to ensure the stable flight of the UAV under the condition of continuous terrain changes, when formula (1) in step 2 is satisfied: |d c -d l When the condition is |>threshold, Δd is accumulated as shown in the following formula (3):

[0105]

[0106] In formula (3), i represents the i-th mutation. According to formula (3), as long as the mutation condition is met, the change value Δd of the distance during the terrain mutation is calculated and accumulated with the previous value. At this time, the calculated change value Δd of the distance simultaneously meets the processing requirements of height data in the case of one mutation and continuous or multiple mutations.

[0107] Step 4: Calculate stable altitude data d by combining the distance change value Δd under the terrain change. When the UAV altitude has not yet undergone the first change, Δd is 0. When the change value is greater than the threshold, Δd will be accumulated regardless of whether the distance data decreases or increases. The stable UAV altitude data d is as follows: (4)

[0108] d = d c -Δ d (4)

[0109] After processing by formula (4), the UAV altitude data can maintain a relatively stable value before and after the terrain change, so the UAV can maintain a relatively stable altitude (initial UAV altitude data relative to the ground).

[0110] Step 5: After height abrupt change removal, the impact of terrain abrupt changes on height is significantly reduced, but small fluctuations still exist. Therefore, an adaptive weighted recursive mean filter is introduced for further processing. First, the weighting coefficients are determined. The weighting coefficients are dynamically adjusted based on the error between the estimated height and the expected height. The larger the error, the smaller the weight should be. An inverse proportional function is used to determine the weighting factor, and the sum of the absolute value of the error and a positive real number is taken as the denominator to avoid the situation where the weight is infinitely large when the error is 0 or negative.

[0111]

[0112] In the formula: e is the weighting coefficient corresponding to the i-th data point; i R represents the error corresponding to the i-th height data. + It is a positive real number.

[0113] Step 6: Normalize the weighting coefficients:

[0114]

[0115] In the formula: ω i is the normalized weighting coefficient corresponding to the i-th data.

[0116] Step 7: Calculate the height data after adaptive weighted recursive filtering:

[0117]

[0118] In the formula: d stable This is to obtain the stable altitude (target UAV altitude relative to the ground) after adaptive weighted recursive mean filtering of the altitude demutation data.

[0119] Step 8: Process the height data d stable The position loop sent to the UAV flight control system is processed through a dual closed-loop system consisting of the flight control position loop and the velocity loop, which solves the problem of maintaining altitude for the UAV under sudden terrain changes.

[0120] To ensure the accuracy of altitude data, this invention also utilizes an encoder installed on the ground-based unmanned vehicle to measure the length of the pulled-out tether cable. Then, using a catenary model of the tether cable, the altitude of the UAV relative to the unmanned vehicle is calculated. A schematic diagram of the catenary model is shown below. Figure 5 As shown.

[0121] The length S of the pulled-out tethered cable can be measured by an encoder, and the cable linear density is μ. The horizontal distance L between the drone and the unmanned vehicle can be obtained by tracking the unmanned vehicle with a camera mounted on the drone.

[0122] The specific implementation steps are as follows:

[0123] Step 1: Solve for the horizontal tension T by using the catenary arc length formula in reverse:

[0124]

[0125] Step 2: Calculate the sag C:

[0126]

[0127] Step 3: Calculate the drone altitude d derived from the tethered data. s :

[0128] d s =SC (10)

[0129] Finally, by fusing the algorithm-processed single-point lidar altitude data (target UAV altitude data relative to the ground) d stableAnd the height data calculated using the catenary model (the height data of the target drone relative to the unmanned vehicle) d s The single-point lidar data has a high frequency, while the tethered cable height data has a low frequency. Therefore, complementary filtering is used to fuse the two data. The fused height data is h. fused :

[0130] h fused =αd stable +(1-α)d s (11)

[0131] In the formula: α represents the weighting coefficient.

[0132] As can be seen, the aircraft altitude-maintaining method provided in this application is a ground-air cooperative system composed of an unmanned vehicle and a tethered drone. The unmanned vehicle is equipped with a large-capacity battery and an automatic cable retraction device, and is equipped with an encoder to measure the length of the cable pulled out by the automatic cable retraction device. An AprilTag mark is affixed to the top as a marker for the drone to track the unmanned vehicle. The drone is equipped with a vertically downward single-point lidar and a camera. The drone and the unmanned vehicle are connected by a tethered cable to perform tasks such as indoor and outdoor emergency rescue.

[0133] Based on changes in terrain, a threshold can be set to first establish a terrain mutation model to significantly reduce the impact of terrain on the drone's altitude. Then, an adaptive weighted recursive mean filtering algorithm is introduced to filter out drone altitude fluctuations caused by terrain changes, enabling the drone to maintain a relatively constant altitude relative to the unmanned vehicle.

[0134] A catenary model is introduced to estimate the UAV altitude using the length of the tethered cable. Complementary filtering is used to fuse the processed high-frequency single-point lidar altitude and the altitude estimated by the processed low-frequency catenary model; this fusion of two sets of data improves reliability.

[0135] To verify the effectiveness of the method provided in this application, Figure 6 To illustrate altitude maintenance under terrain changes, the expected flight altitude of the UAV was set to be 1m above the relative height of the UAV platform. Then, a box approximately 0.5m high and a box approximately 0.25m high were used to simulate terrain changes. As shown in the figure, after processing the single-point lidar data, the impact of terrain changes on the UAV's altitude was significantly reduced. After filtering, small altitude fluctuations were eliminated, and the altitude de-sudden change effect was significant.

[0136] By attaching stickers to the top of the driverless car, such as Figure 7As shown in the AprilTag marker, the drone can use its camera to identify the AprilTag marker and calculate the horizontal relative distance and heading angle between the drone and the unmanned vehicle. Based on the calculated distance and yaw, the drone can track the unmanned vehicle on the ground to perform tasks such as indoor emergency rescue and reconnaissance, such as emergency rescue and inspection in factories, substations, mines and tunnels. Combined with the unmanned vehicle's mapping and positioning, path planning and other algorithms, it can autonomously perform corresponding tasks.

[0137] In summary, the aircraft altitude-maintaining method provided in this application employs a ground-air cooperative system composed of a UAV and an unmanned vehicle, which effectively broadens the field of vision. The two systems work together to perform tasks such as indoor and outdoor reconnaissance and emergency rescue. Simultaneously, the large-capacity battery on the ground ensures the UAV's long-term loiter time, improving operational duration and efficiency. The use of a single-point lidar ensures high precision (centimeter-level), offering higher accuracy and less environmental constraint compared to traditional barometers and GPS altitude setting, and allowing for both indoor and outdoor use. Compared to traditional terrain-following methods, an altitude de-alteration method is employed to remove most of the impact of terrain changes on the UAV's altitude. An adaptive weighted recursive mean filtering method is then introduced to ensure the UAV maintains a constant altitude with the unmanned vehicle even under terrain changes. An encoder is installed on the unmanned vehicle to measure the length of the extended tethered cable. A catenary model is then used to simulate the cable's state in the air, and the UAV's altitude is estimated from the catenary model. This altitude is unaffected by terrain changes. To obtain a more reliable altitude under abrupt terrain changes, the altitude estimated by a single-point lidar and the altitude estimated by the catenary model are fused. Since the single-point lidar has a high frequency and the data obtained from the catenary model has a low frequency, complementary filtering is used to fuse the two sets of data.

[0138] See Figure 8 The present invention can also provide an aircraft altitude maintaining device, such as... Figure 8 As shown, an application is made to an air-ground cooperative system, which includes a ground-based unmanned vehicle and an unmanned aerial vehicle connected by a tethered cable. The unmanned aerial vehicle is equipped with a vertically downward-facing single-point lidar and a camera, and the ground-based unmanned vehicle is equipped with image markers and an encoder. The device used to execute the aforementioned aircraft altitude-keeping method includes:

[0139] The data acquisition unit 801 is used to acquire the current distance data of the UAV relative to the ground and the previous distance data collected by the single-point lidar, and to determine the sudden change threshold.

[0140] The demutation unit 802 is used to calculate the initial UAV relative to the ground altitude data after terrain mutation by combining the mutation threshold, the current distance data and the previous distance data with the altitude data demutation model;

[0141] The UAV relative ground height calculation unit 803 is used to perform real-time and smoothness processing on the initial UAV height data after the terrain change using an adaptive weighted recursive mean filtering algorithm to obtain the target UAV relative ground height data after the terrain change.

[0142] The drone-to-unmanned vehicle height calculation unit 804 is used to obtain the length of the tethered cable that has been pulled out by the encoder and the horizontal distance of the drone relative to the ground unmanned vehicle obtained by the camera tracking the image mark, and to calculate the target drone-to-unmanned vehicle height data of the drone relative to the ground unmanned vehicle using the tethered cable catenary model.

[0143] The data fusion unit 805 is used to combine the target UAV's altitude data relative to the ground and the target UAV's altitude data relative to the unmanned vehicle using complementary filtering and fusion algorithms to obtain fused altitude data, and to use the fused altitude data as the altitude-keeping data of the UAV.

[0144] This invention can also provide an aircraft altitude-keeping device, the device including a processor and a memory:

[0145] The memory is used to store program code and transmit the program code to the processor;

[0146] The processor is used to execute the steps of the above-described aircraft altitude maintaining method according to the instructions in the program code.

[0147] like Figure 9 As shown in the figure, an aircraft altitude-keeping device provided in this embodiment of the invention may include: a processor 10, a memory 11, a communication interface 12, and a communication bus 13. The processor 10, memory 11, and communication interface 12 all communicate with each other through the communication bus 13.

[0148] In this embodiment of the invention, the processor 10 may be a central processing unit (CPU), a graphics processing unit (GPU), an application-specific integrated circuit, a digital signal processor, a field-programmable gate array, or other programmable logic devices.

[0149] The processor 10 can call programs stored in the memory 11. Specifically, the processor 10 can execute operations in the embodiments of the aircraft altitude maintaining method.

[0150] The memory 11 is used to store one or more programs. The programs may include program code, which includes computer operation instructions. In this embodiment of the invention, the memory 11 stores at least a program for implementing the following functions:

[0151] The method is applied to a ground-to-air cooperative system, which includes a ground-based unmanned vehicle (UAV) and a drone connected by a tethered cable. The drone is equipped with a vertically downward-facing single-point lidar and a camera, and the ground-based UAV is equipped with image markers and an encoder.

[0152] The current distance data of the UAV relative to the ground and the previous distance data collected by the single-point lidar are obtained, and the sudden change threshold is determined.

[0153] The initial UAV relative to the ground altitude data after terrain abrupt change is calculated by using the altitude data demutation model combined with the mutation threshold, the current distance data, and the previous distance data;

[0154] An adaptive weighted recursive mean filtering algorithm is used to process the initial UAV altitude data after the terrain change in real time and smoothness to obtain the target UAV altitude data relative to the ground after the terrain change.

[0155] The encoder measures the length of the pulled-out tether cable and the camera tracks the image marker to obtain the horizontal distance between the UAV and the ground unmanned vehicle. The tether cable catenary model is used to calculate the target UAV relative to the ground unmanned vehicle height data.

[0156] By combining the target UAV's altitude data relative to the ground and the target UAV's altitude data relative to the unmanned vehicle, complementary filtering is used to fuse the data and the resulting fused altitude data is calculated using an algorithm. This fused altitude data is then used as the UAV's altitude-keeping data.

[0157] In one possible implementation, the memory 11 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function (such as file creation or data read / write). The data storage area may store data created during use, such as initialization data.

[0158] In addition, memory 11 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device or other volatile solid-state storage device.

[0159] Communication interface 12 can be an interface for the communication module, used to connect with other devices or systems.

[0160] Of course, it should be noted that, Figure 9 The structure shown does not constitute a limitation on the aircraft altitude-keeping device in the embodiments of the present invention. In practical applications, the aircraft altitude-keeping device may include more than Figure 9 More or fewer components as shown, or combinations of certain components.

[0161] This invention also provides a computer-readable storage medium for storing program code for performing the steps of the above-described aircraft altitude-maintaining method.

[0162] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0163] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0164] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0165] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A method for maintaining the altitude of an aircraft, characterized in that, The method is applied to a ground-to-air cooperative system, which includes a ground-based unmanned vehicle (UAV) and a drone connected by a tethered cable. The drone is equipped with a vertically downward-facing single-point lidar and a camera, and the ground-based UAV is equipped with image markers and an encoder. The current distance data of the UAV relative to the ground and the previous distance data collected by the single-point lidar are obtained, and the sudden change threshold is determined. The initial UAV relative to the ground altitude data after terrain abrupt change is calculated by using an altitude data demutation model combined with the mutation threshold, the current distance data, and the previous distance data; An adaptive weighted recursive mean filtering algorithm is used to process the initial UAV altitude data after the terrain change in real time and smoothness to obtain the target UAV altitude data relative to the ground after the terrain change. The encoder measures the length of the pulled-out tether cable and the camera tracks the image marker to obtain the horizontal distance between the UAV and the ground unmanned vehicle. The tether cable catenary model is used to calculate the target UAV relative to the ground unmanned vehicle height data. By combining the target UAV's altitude data relative to the ground and the target UAV's altitude data relative to the unmanned vehicle, complementary filtering is used to fuse the data and the resulting fused altitude data is calculated using an algorithm. This fused altitude data is then used as the UAV's altitude-keeping data.

2. The aircraft altitude maintenance method according to claim 1, characterized in that, The demutation method of the height data demutation model includes: Determine whether the current altitude data of the UAV needs to be processed by comparing the current distance data with a preset mutation threshold. After determining that the current altitude data needs to be processed, the difference between the current distance data and the previous distance data is calculated to obtain the distance change value; The initial drone's altitude relative to the ground is calculated using the distance change value and the current distance data.

3. The aircraft altitude maintenance method according to claim 2, characterized in that, The distance change values ​​are obtained multiple times and summed to obtain the summed distance change value. The initial UAV relative to the ground altitude data is obtained by using the summed distance change value and the current distance data.

4. The aircraft altitude maintenance method according to claim 1, characterized in that, The processing flow of the adaptive weighted recursive mean filtering algorithm includes: The weighting coefficients are determined based on the error between the estimated height and the expected height, and the weighting factors are determined using an inverse proportional function. Normalize the weighting coefficients; The height data after adaptive weighted recursive filtering is calculated using the normalized weighting coefficients and the initial UAV relative to the ground height data, and is used as the target UAV relative to the ground height data.

5. The aircraft altitude maintaining method according to claim 1, characterized in that, The catenary model of the tethered cable obtains the height data of the target UAV relative to the unmanned vehicle by calculating the following formula: d s =S-C In the formula: d s The value represents the height of the target drone relative to the unmanned vehicle, S represents the length of the tethered cable that has been pulled out, and C represents the sag of the cable.

6. The aircraft altitude maintaining method according to claim 5, characterized in that, The length S of the pulled-out mooring cable is calculated using the following formula: The cable sag C is calculated using the following formula: In the formula: T represents horizontal tension, μ represents cable linear density, g represents gravitational acceleration, sinh represents hyperbolic sine function, and L represents the horizontal distance between the UAV and the unmanned vehicle.

7. The aircraft altitude maintaining method according to claim 1, characterized in that, The complementary filtering fusion algorithm is expressed by the following formula: h fused =αd stable +(1-α)d s Where: h fused d represents the fused height data. stable This represents the target drone's altitude relative to the ground, d. s This represents the altitude of the target drone relative to the unmanned vehicle, and α represents the weighting coefficient.

8. An aircraft altitude maintaining device, characterized in that, The system is applied to a ground-air cooperative system, which includes a ground unmanned vehicle and a drone connected by a tethered cable. The drone is equipped with a vertically downward single-point lidar and a camera, and the ground unmanned vehicle is equipped with image markers and an encoder. For performing the aircraft altitude holding method according to any one of claims 1-7, the apparatus comprises: The data acquisition unit is used to acquire the current distance data of the UAV relative to the ground and the previous distance data collected by the single-point lidar, and to determine the sudden change threshold. The demutation unit is used to calculate the initial UAV relative to the ground altitude data after terrain mutation by combining the mutation threshold, the current distance data and the previous distance data with the altitude data demutation model; The UAV relative ground height calculation unit is used to perform real-time and smoothness processing on the initial UAV height data after the terrain change using an adaptive weighted recursive mean filtering algorithm to obtain the target UAV relative ground height data after the terrain change. The drone-to-unmanned vehicle height calculation unit is used to obtain the length of the tethered cable that has been pulled out by the encoder and the horizontal distance of the drone relative to the ground unmanned vehicle obtained by the camera tracking the image mark, and to calculate the target drone-to-unmanned vehicle height data of the drone relative to the ground unmanned vehicle using the tethered cable catenary model. The data fusion unit is used to combine the target UAV's altitude data relative to the ground and the target UAV's altitude data relative to the unmanned vehicle using complementary filtering and fusion algorithms to obtain fused altitude data, and to use the fused altitude data as the altitude-keeping data of the UAV.

9. An aircraft altitude-keeping device, characterized in that, The device includes a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is configured to execute the aircraft altitude maintaining method according to any one of claims 1-7 according to the instructions in the program code.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store program code for performing the aircraft altitude-maintaining method according to any one of claims 1-7.

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