Buffer type unmanned aerial vehicle control right handover method with landing damping structure

Abstract

The invention relates to the technical field of unmanned aerial vehicle control, in particular to a buffer type unmanned aerial vehicle control right handover method with a landing damping structure, which comprises the following steps of: based on all flight data of an unmanned aerial vehicle, analyzing speed, inclination angle and displacement difference of multiple stages in flight, identifying abnormal fluctuation amplitude and duration, and generating random interference characteristic data. According to the invention, by extracting and analyzing the acceleration, the angular velocity and the environmental parameters in the flight of the unmanned aerial vehicle, the abnormal fluctuation can be identified, the response delay of the flight attitude can be accurately detected when the control right is handed over, and the control deviation caused by control switching is reduced. The attitude is adjusted and corrected through evaluation of the flight angle and speed, and the stability of the flight attitude is further improved. The attitude adjustment in the landing stage prejudges the impact strength and the grounding influence according to real-time sensor data, and dynamically adjusts the hardness of the hydraulic shock absorber so as to reduce the impact force during grounding and realize more stable landing.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) control, and particularly to a buffer-type UAV control right handover method with a landing shock absorption structure. Background Art

[0002] The technical field of UAV control includes aspects such as the startup of UAVs, flight path planning, real-time control, and safe landing. It also covers the communication technology between UAVs and control systems, such as the use of radio frequencies, data encryption, and transmission security. In addition, with the development of technology, UAV control technology is constantly integrating new functions, such as automatic obstacle avoidance, target tracking, and multi-UAV collaborative control.

[0003] Among them, the purpose of the UAV control right handover method is to safely and effectively transfer the control right of the UAV from one control system or operator to another under different operating scenarios. For example, from ground station control to control on an aircraft carrier, or from automatic mode to manual control. The handover of control rights not only needs to ensure the continuity and safety of UAV operations, but also needs to consider the synchronization of control instructions and the seamless transfer of data. It is mostly applied to scenarios such as cross-border surveillance, multi-region scheduling, or disaster response.

[0004] In the prior art, although the continuity of operations and the stability of data transmission can be guaranteed during the handover of control rights, it is difficult to fully consider the real-time fluctuations of various parameters during flight and the influence of random interference when facing changes in flight postures, resulting in possible control deviations or unstable postures during control switching. When encountering complex or changing environments, it is not conducive to quickly avoiding attitude loss of control or reaction delay caused by differences in operator input or sudden environmental changes. In addition, the prior art is prone to excessive impact force or insufficient shock absorption during the landing process of UAVs, increasing the risks during the landing process. Summary of the Invention

[0005] The purpose of the present invention is to solve the disadvantages existing in the prior art, and to propose a buffer-type UAV control right handover method with a landing shock absorption structure.

[0006] To achieve the above purpose, the present invention adopts the following technical solution: A buffer-type UAV control right handover method with a landing shock absorption structure, comprising the following steps:

[0007] S1: Based on all flight data of the UAV, analyze the speed, inclination angle, and displacement differences in multiple stages during flight, identify the abnormal fluctuation amplitude and duration, and generate random interference characteristic data;

[0008] S2: Based on the random interference characteristic data, detect the manipulation differences caused by the operator input switching, judge the response delay in the flight attitude change, and generate a control offset analysis result;

[0009] S3: Based on the control offset analysis result, evaluate the attitude change of the aircraft, perform angle correction and speed adjustment, and generate a control attitude optimization result;

[0010] S4: Based on the control attitude optimization result, judge the impact force during the landing phase, and predict the impact influence when landing, and generate a landing impact prediction result;

[0011] S5: Based on the landing impact prediction result, by calculating the change trend of the landing speed and acceleration, combined with the current attitude of the UAV and the ground height data, dynamically adjust the hydraulic hardness in real time according to the impact intensity, and generate shock absorption hardness optimization data;

[0012] S6: Based on the shock absorption hardness optimization data, analyze the attitude fluctuations during flight, combined with the previously collected operation data, adjust the shock absorption parameters during landing, and generate an enhanced shock absorption response signal.

[0013] The improvement of the present invention is that the random interference characteristic data includes the acceleration change amplitude, angular velocity fluctuation frequency and environmental condition fluctuation value recorded during the flight process, the control offset analysis result includes the attitude response delay detected during the handover of control rights, the direction offset angle caused by the operator input difference and the operation time difference, the control attitude optimization result includes the adjustment value for flight angle correction, the speed correction amount required for attitude stability and the flight balance parameter, the landing impact prediction result includes the impact force prediction value when approaching the ground, the landing acceleration fluctuation range and the change situation of the landing height, the shock absorption hardness optimization data includes the hardness adjustment amplitude required for the hydraulic shock absorber, the hydraulic oil flow rate and the pressure valve opening and closing time, and the enhanced shock absorption response signal includes the real-time adjustment instruction of the shock absorber, the attitude balance control signal and the hardness dynamic adjustment amplitude.

[0014] The improvement of the present invention is that based on all the flight data of the UAV, analyze the speed, inclination angle and displacement differences in multiple stages during flight, identify the abnormal fluctuation amplitude and duration, and the specific steps for generating the random interference characteristic data are as follows.

[0015] S101: Based on all the flight data of the UAV, extract the acceleration, angular velocity and environmental parameters, perform parameter separation for the flight stage, divide the speed, inclination angle and displacement data according to the time axis, and segment and organize the data to generate a flight stage parameter set;

[0016] S102: Based on the flight phase parameter set, by comparing the acceleration and angular velocity changes in multiple flight phases, perform segmented difference calculations to identify the fluctuation amplitude and frequency of the flight phase, and generate the flight amplitude change result;

[0017] S103: Based on the flight amplitude change result, according to the abnormal fluctuation amplitude in the flight phase, screen the abnormal flight parameter range and classify it as an abnormal data segment to generate random interference characteristic data.

[0018] The improvement of the present invention is as follows. Based on the random interference characteristic data, detect the control difference caused by the operator's input switch, judge the response delay in the flight attitude change, and generate the specific steps of the control offset analysis result as follows.

[0019] S201: Based on the random interference characteristic data, combined with the acceleration and angular velocity in real-time flight, extract the sensor output at the moment of handover of control rights, identify the critical moment of input change, perform time-point cutting on the data, and generate operation input change data;

[0020] S202: Based on the operation input change data, compare the input switch point with the real-time parameters of the flight attitude, detect the attitude adjustment response time after the operator's input switch, calculate the delay change, judge the lag situation of the flight attitude response, and generate the attitude response change result;

[0021] S203: Based on the attitude response change result, combined with the influence of the operator's input on the attitude stability, analyze the attitude change amplitude and offset amount during the handover of control rights, and comprehensively consider the control difference and attitude offset situation to generate the control offset analysis result.

[0022] The improvement of the present invention is as follows. Based on the control offset analysis result, evaluate the attitude change of the aircraft, perform angle correction and speed adjustment, and generate the specific steps of the control attitude optimization result as follows.

[0023] S301: Based on the control offset analysis result, extract the angle and speed data in the current flight attitude, perform real-time analysis of the angle and speed changes, capture the attitude offset value during flight through difference calculation, evaluate the attitude change trend, and generate attitude difference data;

[0024] S302: Based on the attitude difference data, compare the attitude offset value with the expected value of the target attitude, adjust the attitude control instruction of the aircraft, correct the angle and speed change amplitude, recalculate the correction parameters of the angle and speed, and generate attitude correction parameters;

[0025] S303: Based on the attitude correction parameters, feedback the attitude stability of the aircraft, and according to the corrected angle and speed changes, recalibrate the angle control and stability parameters of the aircraft to generate the control attitude optimization result.

[0026] The improvement of the present invention is as follows. Based on the optimized control attitude result, the impact force during the landing phase is judged, and the impact effect at the moment of touchdown is predicted. The specific steps for generating the touchdown impact prediction result are as follows:

[0027] S401: Based on the optimized control attitude result, call the real-time sensor data of the drone approaching the ground, extract the current flight altitude, landing speed, and acceleration information, synchronize the data with the flight attitude change, and generate real-time landing data;

[0028] S402: Based on the real-time landing data, analyze the speed and acceleration fluctuations during the landing process, combine with the current attitude of the aircraft, evaluate the stability during landing, calculate the attitude adjustment requirements during the landing phase, and generate a landing attitude analysis result;

[0029] S403: Based on the landing attitude analysis result, calculate the impact force at the moment of touchdown, combine with the landing speed, acceleration, and altitude change of the aircraft, evaluate the touchdown impact effect, and generate a touchdown impact prediction result.

[0030] The improvement of the present invention is that for the calculation of the impact force at the moment of touchdown, according to the formula:

[0031]

[0032] The impulse I of the impact force is obtained;

[0033] where F is the impact force at touchdown, t is the contact time at the moment of touchdown, k is the damping coefficient, v is the speed at touchdown, a is the acceleration during landing, and h is the altitude of the aircraft.

[0034] The improvement of the present invention is as follows. Based on the touchdown impact prediction result, by calculating the change trend of the landing speed and acceleration, combining with the current attitude of the drone and the ground altitude data, the hydraulic hardness is dynamically adjusted in real time according to the impact intensity, and the specific steps for generating the shock absorption hardness optimization data are as follows:

[0035] S501: Based on the touchdown impact prediction result, extract the landing speed, acceleration, and flight attitude data, combine with the real-time ground altitude, calculate the change of speed and acceleration when approaching the ground, analyze the change trend of the impact intensity in multiple time periods, and generate touchdown speed attitude data;

[0036] S502: Based on the touchdown speed attitude data, evaluate the current hydraulic oil flow rate of the hydraulic shock absorber, calculate the pressure impact of the change of the impact intensity on the hydraulic structure, adjust the opening of the control valve of the pressure sensor, and dynamically modify the hydraulic damping to generate hydraulic damping control data;

[0037] S503: Based on the hydraulic damping control data, by monitoring the change of impact intensity in real time, adjust the hardness response of the hydraulic shock absorber, balance the impact intensity and the reaction time of the shock absorption structure, optimize the working state of the shock absorber, and generate shock absorption hardness optimization data.

[0038] The present invention is improved in that for evaluating the current hydraulic oil flow rate of the hydraulic shock absorber, according to the formula:

[0039]

[0040] Calculate the pressure impact of the change in impact intensity on the hydraulic structure to obtain the hydraulic pressure P;

[0041] Wherein, F is the impact force when grounding, A is the piston area, V is the volume of the hydraulic oil, M is the flow velocity of the hydraulic oil, g is the acceleration due to gravity, h′ is the height difference passed by the hydraulic oil, M 2 is the square of the flow velocity, and 2gh′ is the gravitational potential energy.

[0042] The present invention is improved in that based on the shock absorption hardness optimization data, analyze the attitude fluctuations during flight, combine the previously collected operation data, and adjust the shock absorption parameters during landing. The specific steps for generating an enhanced shock absorption response signal are as follows.

[0043] S601: Based on the shock absorption hardness optimization data, extract the speed and inclination angle data during the flight of the UAV, call the air pressure and wind speed information, and combine the past flight attitude fluctuation data to calculate the impact of the attitude fluctuations during flight on the shock absorption structure during landing, and generate attitude fluctuation analysis data;

[0044] S602: Based on the attitude fluctuation analysis data, compare the inclination angle of the aircraft and the air pressure fluctuation, adjust the response speed of the shock absorber, optimize the working efficiency and hardness control of the shock absorber, and generate shock absorption structure adjustment parameters;

[0045] S603: Based on the shock absorption structure adjustment parameters, monitor the attitude fluctuations during the landing process of the aircraft in real time, adjust the shock absorber parameters, and combine the attitude data and the response of the shock absorber to the environmental conditions to generate an enhanced shock absorption response signal.

[0046] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0047] In the present invention, by extracting and analyzing the acceleration, angular velocity, and environmental parameters during the flight of the drone, abnormal fluctuations can be identified, ensuring that the response delay of the flight attitude can be accurately detected during the handover of control rights, and reducing the control deviation caused by control switching. Through the evaluation of the flight angle and speed, the attitude is adjusted and corrected to further improve the stability of the flight attitude. During the landing phase, the attitude is adjusted according to real-time sensor data to predict the impact force and the influence of grounding, and the hardness of the hydraulic shock absorber is dynamically adjusted to reduce the impact force during grounding and achieve a smoother landing. By synchronously adjusting the landing speed, acceleration, and attitude, the shock absorption response of the drone during landing is strengthened, effectively reducing the impact of external environmental changes on flight and landing. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a flowchart of a method for handing over control rights of a buffer-type drone with a landing shock absorption structure proposed by the present invention;

[0049] Figure 2 is a schematic diagram of the detailed process of step S1 in the present invention;

[0050] Figure 3 is a schematic diagram of the detailed process of step S2 in the present invention;

[0051] Figure 4 is a schematic diagram of the detailed process of step S3 in the present invention;

[0052] Figure 5 is a schematic diagram of the detailed process of step S4 in the present invention;

[0053] Figure 6 is a schematic diagram of the detailed process of step S5 in the present invention;

[0054] Figure 7 is a schematic diagram of the detailed process of step S6 in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0055] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0056] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. In addition, in the description of the present invention, the meaning of "a plurality of" is two or more, unless otherwise specifically defined.

[0057] Please refer to Figure 1 , the present invention provides a technical solution: a buffering type UAV control right handover method with a landing shock absorption structure, including the following steps:

[0058] S1: Based on all flight data of the UAV, analyze the speed, inclination angle, and displacement differences in multiple stages during flight, identify the abnormal fluctuation amplitude and duration, and generate random interference characteristic data;

[0059] S2: Based on the random interference characteristic data, detect the control differences caused by the operator's input switching, judge the response delay in the flight attitude change, and generate a control offset analysis result;

[0060] S3: Based on the control offset analysis result, evaluate the attitude change of the aircraft, perform angle correction and speed adjustment, and generate a control attitude optimization result;

[0061] S4: Based on the control attitude optimization result, judge the impact force during the landing stage, and predict the impact effect when landing, and generate a landing impact prediction result;

[0062] S5: Based on the landing impact prediction result, by calculating the change trend of the landing speed and acceleration, combined with the current attitude of the UAV and the ground height data, dynamically adjust the hydraulic hardness in real time according to the impact intensity, and generate shock absorption hardness optimization data;

[0063] S6: Based on the shock absorption hardness optimization data, analyze the attitude fluctuation during flight, combined with the previously collected operation data, adjust the shock absorption parameters during landing, and generate an enhanced shock absorption response signal.

[0064] The random interference characteristic data includes the amplitude of acceleration change, the fluctuation frequency of angular velocity, and the fluctuation value of environmental conditions recorded during flight. The control offset analysis results include the attitude response delay detected during the handover of control rights, the direction offset angle caused by operator input differences, and the operation time difference. The control attitude optimization results include the adjustment value for flight angle correction, the speed correction amount required for attitude stability, and the flight balance parameters. The ground impact prediction results include the predicted impact force value when approaching the ground, the fluctuation range of landing acceleration, and the change in ground contact height. The shock absorption hardness optimization data includes the adjustment amplitude of hardness required for the hydraulic shock absorber, the flow rate of hydraulic oil, and the opening and closing time of the pressure valve. The enhanced shock absorption response signal includes the real-time adjustment instruction of the shock absorber, the attitude balance control signal, and the dynamic adjustment amplitude of hardness.

[0065] Please refer to Figure 2 , based on all the flight data of the unmanned aerial vehicle (UAV), analyze the speed, inclination angle, and displacement differences in multiple flight phases, identify the abnormal fluctuation amplitude and duration, and the specific steps to generate the random interference characteristic data are as follows.

[0066] S101: Based on all the flight data of the UAV, extract the acceleration, angular velocity, and environmental parameters, separate the parameters of the flight phase, divide the speed, inclination angle, and displacement data according to the time axis, and segment and organize the data to generate the flight phase parameter set.

[0067] Align the data recorded by various sensors during flight to a unified time axis, separate all the data according to the flight phase, and collect the data according to the time period. Next, extract and separate the speed, inclination angle, and displacement of these segmented data to ensure that the details of various data in different flight phases are completely captured. The separation of data needs to be supplemented according to the attitude changes during flight. After segmentation, it is also necessary to classify and organize the data of each phase, mark the abnormal changes during flight in the corresponding time period data set. By supplementing the collection of acceleration, angular velocity, and other data, it is possible to accurately record the fluctuation changes in different flight phases and generate the flight phase parameter set.

[0068] S102: Based on the flight phase parameter set, calculate the differences in segments by comparing the acceleration and angular velocity changes in multiple flight phases, identify the fluctuation amplitude and frequency of the flight phase, and generate the flight amplitude change result.

[0069] By comparing the acceleration and angular velocity changes in different flight phases, according to the formula:

[0070]

[0071] Calculate the flight phase fluctuation amplitude. In the formula, A diff represents the fluctuation amplitude, Amax Represents the maximum acceleration, A min Represents the minimum acceleration, T total Represents the total time of this stage.

[0072] Based on the acceleration data collected by the acceleration sensor, A max and A min can be obtained by frame-by-frame comparison. Each frame of data represents the acceleration magnitude at the moment of flight attitude change, T total is the data time length for each flight stage.

[0073] Set the parameter A min = 12m / s 2 ,A min = 3m / s 2 ,T total = 5s, substituting into the formula gives:

[0074]

[0075] The result shows that the acceleration change per second is 1.8m / s 3 . Combining with the angular velocity data, compare this fluctuation amplitude with other stages, and summarize the fluctuation range in combination with its frequency data to generate the flight amplitude change result.

[0076] S103: Based on the flight amplitude change result, according to the abnormal fluctuation amplitude in the flight stage, screen the abnormal flight parameter range and classify it as an abnormal data segment to generate random interference characteristic data.

[0077] By screening the fluctuation amplitude data of each flight stage, compare the fluctuation data with the preset abnormal fluctuation amplitude threshold, extract the fluctuation data exceeding the threshold. The abnormal fluctuation amplitude is set by the reference values of multiple historical flight data. Next, classify the fluctuation data exceeding the threshold as an abnormal data segment. During the data classification process, distinguish various abnormal segments according to different time periods and fluctuation amplitudes, and mark their positions during flight. Finally, through multiple screening and classification processes, screen out the abnormal flight parameter range and generate the corresponding random interference characteristic data.

[0078] Please refer to Figure 3 ,Based on the random interference characteristic data, detect the control differences caused by the operator input switching, judge the response delay in the flight attitude change, and the specific steps to generate the control offset analysis result are as follows:

[0079] S201: Based on the random interference characteristic data, combine the acceleration and angular velocity in real-time flight, extract the sensor output at the moment of handover of control rights, identify the critical moment of input change, cut the data at the time point, and generate operation input change data;

[0080] By extracting the real-time data output by the sensor, at the critical moment of handover of control rights, it is necessary to segment the sensor data to ensure that the specific time point of the input change can be identified. During this process, the real-time data is synchronized with the time point of the input switch. By setting a time window, the acceleration and angular velocity data before and after the input change are obtained. Then, the data is cut at the time point, and the data is cut and re-labeled along the time axis so that the data can be accurately aligned with the critical moment of the input change. After completing this process, a time series containing the input change data is generated, and then the operation input change data is output.

[0081] S202: Based on the operation input change data, compare the input switch point with the real-time parameters of the flight attitude, detect the attitude adjustment response time after the operator's input switch, calculate the delay change, judge the lag situation of the flight attitude response, and generate the attitude response change result;

[0082] Detect the attitude adjustment response time after the operator's input switch. According to the formula:

[0083] Δt = t response -t switch

[0084] Calculate the delay time of the input switch. In the formula, Δt represents the delay time, and t response represents the moment of the flight attitude adjustment response, and t switch represents the moment when the input switch occurs.

[0085] According to the sensor data, t switch is the time point of the operator's input switch, which can be obtained by detecting the moment of the input signal change, and t response is the moment of the aircraft attitude adjustment, which can be determined by detecting the change of attitude parameters such as angular velocity.

[0086] If t switch = 2.5s, t response = 3.0s, then:

[0087] Δt = 3.0s - 2.5s = 0.5s

[0088] The result shows that after the operator's input switch, the attitude response of the aircraft occurs 0.5 seconds later. This delay time can be further used to judge the lag situation of the flight attitude response and generate the attitude response change result.

[0089] S203: Based on the attitude response change result, combined with the influence of the operator's input on the attitude stability, analyze the attitude change amplitude and offset amount during the handover of control rights, and comprehensively consider the control difference and attitude offset situation to generate the control offset analysis result.

[0090] By analyzing the flight attitude changes caused by the operator input switching, it is necessary to calculate the attitude adjustment amplitude and offset during the handover of flight control rights. When analyzing these parameters, in combination with the real-time attitude parameters of the aircraft after the input change, by extracting the angular changes of attitude adjustment and attitude offset data. Then, compare the angular changes caused by the operator input with the attitude stability standard to judge the control differences of the operator at different input switching points. Finally, by synthesizing these control differences and attitude offsets, obtain the impact of the handover of control rights on the aircraft attitude and generate the control offset analysis result.

[0091] Please refer to Figure 4 , based on the control offset analysis result, evaluate the attitude changes of the aircraft, perform angle correction and speed adjustment, and the specific steps to generate the control attitude optimization result are as follows.

[0092] S301: Based on the control offset analysis result, extract the angle and speed data in the current flight attitude, perform real-time analysis of the angle and speed changes, capture the attitude offset values during flight through difference calculation, evaluate the attitude change trend, and generate attitude difference data.

[0093] By collecting the angle and speed data in real time, synchronizing the collected data with the flight state data, extracting the angular changes in each time period, and then, according to the collected flight data, analyzing the fluctuation amplitude in the flight attitude by comparing the angle and speed values in different time periods. Finally, by monitoring the attitude change trend in real time, further calculate these values, capture the attitude offset values during flight, and classify them into the attitude change records to form an attitude data set. At the same time, combined with the attitude offset values, evaluate the overall change trend of the flight attitude to ensure that the attitude change trend can correctly reflect the fluctuations of the flight state and generate attitude difference data.

[0094] S302: Based on the attitude difference data, compare the attitude offset value with the expected value of the target attitude, adjust the attitude control command of the aircraft, correct the amplitude of the angle and speed changes, recalculate the correction parameters of the angle and speed, and generate attitude correction parameters.

[0095] Compare the attitude offset value with the expected value of the target attitude according to the formula:

[0096] Δθ=θ target -θ actual

[0097] Calculate the angle correction value. In the formula, Δθ represents the angle correction value, θ target represents the angle of the target attitude, θ actual represents the angle of the current attitude.

[0098] First, the angle θ of the target attitudetarget The actual angle θ can be set by flying the predetermined flight path. actual Obtained through real-time attitude sensor measurements.

[0099] If the target angle θ target =30°, current angle θ actual =25°, then:

[0100] Δθ=30°-25°=5°

[0101] The results show that the current aircraft attitude deviates from the target attitude by 5 degrees, and it is necessary to correct the angle and speed changes by adjusting the control instructions to generate attitude correction parameters.

[0102] S303: Based on the attitude correction parameters, the attitude stability of the aircraft is fed back. According to the corrected angle and speed changes, the angle control and stability parameters of the aircraft are recalibrated to generate a control attitude optimization result.

[0103] By feeding back the corrected angle and speed data, these corrected data are synchronized with the aircraft's control equipment, and the corrected data is input into the attitude control module through the feedback loop. Then, the aircraft's attitude is adjusted according to the corrected angle and speed data, and the current attitude control instructions are compared with the corrected parameters to generate new attitude control instructions. At the same time, it is also necessary to monitor the aircraft's attitude stability in real time to ensure that there is no new attitude offset during the adjustment process. Finally, the correction of the aircraft's angle and speed is completed, and the aircraft's angle control and stability parameters are recalibrated to generate the control attitude optimization result.

[0104] See also Figure 5 Based on the control attitude optimization results, the impact force during the landing phase is determined, and the impact of the touchdown is predicted. The specific steps for generating the touchdown impact prediction results are as follows:

[0105] S401: Based on the control attitude optimization results, call the real-time sensor data of the UAV approaching the ground, extract the current flight altitude, landing speed and acceleration information, synchronize the data with the flight attitude changes, and generate real-time landing data;

[0106] It is necessary to extract the current flight altitude, landing speed and acceleration information, combine the altitude information obtained by the real-time sensor with the landing speed of the drone to ensure data synchronization, and correspond the data of different time periods to the timeline of flight attitude changes. Then, the altitude, speed and acceleration data are segmented to ensure data continuity and consistency. Then, the trend of flight attitude changes is compared with the acceleration changes obtained by the sensor to generate real-time landing data based on flight attitude synchronization, and ensure that the data matches the real-time changes in the aircraft attitude.

[0107] S402: Analyze the speed and acceleration fluctuations during the landing process based on real-time landing data, combine with the current attitude of the aircraft, evaluate the stability during landing, calculate the attitude adjustment requirements during the landing phase, and generate the landing attitude analysis result;

[0108] For analyzing the speed and acceleration fluctuations during the landing process, according to the formula:

[0109]

[0110] Calculate the force at the moment of touchdown;

[0111] Among them, F represents the impact force at touchdown, which is calculated through parameters such as the mass and acceleration of the UAV. m is the mass of the UAV, obtained from the design parameters of the UAV or the specified values in the aircraft manual. a is the acceleration during landing, obtained by real-time measurement with an acceleration sensor. v is the speed at touchdown, measured by a speed sensor or calculated from the time derivative of the altitude change. g is the acceleration due to gravity, and h is the altitude of the aircraft, obtained by real-time measurement with an altitude sensor.

[0112] Set the parameter of the UAV mass m = 5 kg, acceleration a = 2 9.8 m / s 2 , the speed at touchdown v = 3 m / s, altitude h = 10 m, and acceleration due to gravity g = 2 9.8 m / s 2 , then:

[0113]

[0114] The result shows that the impact force of the UAV at touchdown is 51.3 Newtons. Based on the magnitude of this impact force, the stability during landing can be further evaluated and the attitude can be adjusted to generate the landing attitude analysis result.

[0115] S403: Based on the landing attitude analysis result, calculate the impact force at the moment of touchdown, combine with the landing speed, acceleration, and altitude change of the aircraft, evaluate the impact of the touchdown, and generate the touchdown impact prediction result.

[0116] For calculating the impact force at the moment of touchdown, according to the formula:

[0117]

[0118] Obtain the impulse of the impact force;

[0119] Among them, I represents the impact of the impact force at the moment of grounding on the drone, F is the impact force at the time of grounding, t is the contact time at the moment of grounding, which is measured by a real-time sensor when the drone touches the ground, k is the damping coefficient (a dimensionless parameter) representing the impact of the shock absorber performance, obtained from the design parameters of the drone or the performance standards of the shock absorption system, v is the speed at the time of grounding, which is measured in real time by the drone's speed sensor or calculated through the derivative of the height change, a is the acceleration during landing, which is measured by an acceleration sensor during the landing process, and h is the height of the aircraft, for which real-time data is provided by the height sensor.

[0120] Set the parameters F = 51.3 N, contact time t = 0.05 s, damping coefficient k = 0.5, speed v = 3 m / s, height h = 10 m, and acceleration a = 9.8 m / s 2 , then:

[0121]

[0122] The results show that the impulse at the time of grounding is 2.51 Newton-seconds. Combining the changes in speed, acceleration, and height, the impact intensity of the drone at the time of grounding is evaluated, and finally, a pre-judgment result of the grounding impact is generated.

[0123] Please refer to Figure 6 , based on the pre-judgment result of the grounding impact, by calculating the changing trends of the landing speed and acceleration, and combining the current attitude of the drone and the ground height data, the specific steps to dynamically adjust the hydraulic hardness in real time according to the impact intensity and generate the optimized data of the shock absorption hardness are as follows.

[0124] S501: Based on the pre-judgment result of the grounding impact, extract the landing speed, acceleration, and flight attitude data, combine with the real-time ground height, calculate the changes in speed and acceleration when approaching the ground, analyze the changing trends of the impact intensity in multiple time periods, and generate the grounding speed and attitude data;

[0125] By extracting the data of the landing speed, acceleration, and flight attitude, integrating these data with the real-time ground height data, matching the speed, acceleration, and height in each time period through time series processing, then analyzing the changing trends of speed and acceleration in each time period, especially paying attention to the acceleration change when approaching the ground, identifying the moments with large acceleration fluctuations during the descent by comparing different height and speed data, synchronously comparing these data with the flight attitude changes, generating a set of time series data reflecting the relationship between the aircraft attitude changes and the acceleration and speed fluctuations, and finally generating the grounding speed and attitude data according to these analysis results.

[0126] S502: Based on the ground speed and attitude data, evaluate the current hydraulic oil flow rate of the hydraulic shock absorber, calculate the pressure impact of the change in impact intensity on the hydraulic structure, adjust the opening of the control valve of the pressure sensor, dynamically modify the hydraulic damping, and generate hydraulic damping control data;

[0127] For evaluating the current hydraulic oil flow rate of the hydraulic shock absorber, according to the formula:

[0128]

[0129] Calculate the pressure impact of the change in impact intensity on the hydraulic structure;

[0130] Among them, P is the hydraulic pressure, representing the pressure generated inside the hydraulic cylinder due to the impact force and the change in flow rate. F is the impact force at grounding, A is the piston area, representing the effective area where the hydraulic oil acts inside the hydraulic cylinder, provided by the design parameters of the hydraulic cylinder. V is the volume of the hydraulic oil, usually determined by the design parameters of the hydraulic system. M is the flow velocity of the hydraulic oil, measured in real time by the flow sensor of the hydraulic system, reflecting the flow rate of the hydraulic oil in the hydraulic structure. g is the acceleration due to gravity, used to represent the acceleration under the action of gravity. h′ is the height difference through which the hydraulic oil passes, obtained from the design parameters of the hydraulic structure, representing the height change of the hydraulic oil passing through the hydraulic cylinder. v 2 is the square of the flow velocity, used to represent the kinetic energy of the hydraulic oil, indicating the impact of the kinetic energy generated by the moving hydraulic oil on the pressure. 2gh′ is the gravitational potential energy, representing the impact of the potential energy generated due to the height difference of the hydraulic oil on the pressure.

[0131] If the impact force F = 1000N, the piston area A = 0.01m 2 , the volume of the hydraulic oil V = 0.05m 3 , the flow velocity of the hydraulic oil M = 2m / s, the height difference h = 1m, and the acceleration due to gravity g = 9.8m / s 2 , then:

[0132]

[0133] First, calculate the preliminary value of the pressure:

[0134]

[0135] Next, calculate the impact of the additional kinetic energy on the pressure:

[0136]

[0137] Substitute it into the formula:

[0138] P = 200Pa·(1 + 0.204) = 200·1.204 = 240.8Pa

[0139] The results show that the pressure in the current hydraulic system is 240.8 Pascals. This pressure change needs to be adapted by adjusting the opening of the hydraulic valve, dynamically adjusting the hydraulic damping to cope with the change in impact intensity, and finally generating hydraulic damping control data.

[0140] S503: Based on the hydraulic damping control data, by real-time monitoring the change in impact intensity, adjust the hardness response of the hydraulic shock absorber, balance the impact intensity and the response time of the shock absorption structure, optimize the working state of the shock absorber, and generate shock absorption hardness optimization data.

[0141] By adjusting the damping coefficient of the hydraulic shock absorber, the damping coefficient is corrected according to the feedback value to ensure that the shock absorber can provide sufficient hardness to relieve the impact when the impact occurs. At the same time, by adjusting the hydraulic working pressure, optimize the working state of the shock absorber, balance the shock absorption response time and the impact buffering effect. Finally, through continuous monitoring feedback, confirm the performance of the hydraulic shock absorber under different impact intensities, and generate shock absorption hardness optimization data for subsequent performance optimization.

[0142] Please refer to Figure 7 , based on the shock absorption hardness optimization data, analyze the attitude fluctuations during flight, combine with the previously collected operation data, adjust the shock absorption parameters during landing, and the specific steps to generate an enhanced shock absorption response signal are as follows.

[0143] S601: Based on the shock absorption hardness optimization data, extract the speed and inclination angle data during the flight of the UAV, call the air pressure and wind speed information, combine with the past flight attitude fluctuation data, calculate the impact of the attitude fluctuations during flight on the shock absorption structure during landing, and generate attitude fluctuation analysis data.

[0144] Obtain the real-time data of the flight speed and inclination angle, perform correlation processing with the air pressure and wind speed information, use the historical flight data for retrospective analysis of attitude fluctuations. Then, call the recorded flight attitude fluctuation data, compare the data during the current flight process with the historical data, match the change in the inclination angle with the fluctuations in air pressure and wind speed during the analysis process, obtain the overall trend of attitude fluctuations during flight by comparing the correlation between the change in the inclination angle and environmental parameters at different flight stages, and determine the possible affected time and range of the shock absorption structure in combination with the flight history data. Finally, generate attitude fluctuation analysis data based on these trend data.

[0145] S602: Based on the attitude fluctuation analysis data, compare the inclination angle of the aircraft and the air pressure fluctuations, adjust the response speed of the shock absorber, optimize the working efficiency and hardness control of the shock absorber, and generate shock absorption structure adjustment parameters.

[0146] Obtain the correlation data of the inclination angle and air pressure fluctuation through the data comparison module. Combine the current attitude information of the aircraft, and use the correlation analysis method to analyze the influence of the inclination angle fluctuation and air pressure fluctuation on the response speed of the shock absorber. During the analysis process, synchronously compare the response speed of the shock absorber under different air pressure conditions with the historical data. Then, match and analyze the time period of the inclination angle fluctuation with the time period of the air pressure change to identify the influence of the attitude fluctuation on the response speed of the shock absorber. Finally, obtain the optimal response speed adjustment plan for the shock absorber, optimize the working efficiency and hardness control of the shock absorber, and generate shock absorption structure adjustment parameters to ensure the best working state of the shock absorber under different flight states.

[0147] S603: Based on the shock absorption structure adjustment parameters, monitor the attitude fluctuation during the landing process of the aircraft in real time, adjust the shock absorber parameters, and generate an enhanced shock absorption response signal by combining the attitude data and the response of the shock absorber to the environmental conditions.

[0148] Monitor the attitude fluctuation of the aircraft during the landing process in real time, collect real-time data such as the inclination angle, acceleration, wind speed, and air pressure of the aircraft, integrate these data with the control parameters in the shock absorption structure through sensor fusion technology. Then, through the environmental sensor and attitude sensor network, analyze the current response of the shock absorber, dynamically track the attitude change of the aircraft, and adjust and match the current flight attitude with the response parameters of the shock absorption system. Finally, automatically adjust the response parameters of the shock absorber according to the amplitude and frequency of the aircraft attitude fluctuation, so that the shock absorber can optimize the shock absorption effect under different environmental conditions and attitudes, generate an enhanced shock absorption response signal, and realize the attitude adjustment during the landing process of the aircraft.

[0149] The above is only the preferred embodiment of the present invention, and it is not intended to limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical solution content of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A buffer-type UAV control right handover method with a landing shock absorption structure, characterized in that, It includes the following steps: Based on all the flight data of the drone, analyze the speed, inclination angle, and displacement differences in multiple flight stages, identify the abnormal fluctuation amplitude and duration, and generate random interference characteristic data; Based on the random interference characteristic data, detect the control differences caused by the operator's input switch, judge the response delay in the flight attitude change, and generate a control offset analysis result; Based on the control offset analysis result, evaluate the attitude change of the aircraft, perform angle correction and speed adjustment, and generate a control attitude optimization result; Based on the control attitude optimization result, judge the impact force during the landing stage, and predict the impact effect when landing, and generate a landing impact prediction result; Based on the landing impact prediction result, by calculating the change trend of the landing speed and acceleration, combining the current attitude of the drone and the ground height data, dynamically adjust the hydraulic hardness in real time according to the impact intensity, and generate shock absorption hardness optimization data; Based on the shock absorption hardness optimization data, analyze the attitude fluctuation during flight, combine the previously collected operation data, adjust the shock absorption parameters during landing, and generate an enhanced shock absorption response signal.

2. The buffer-type UAV control right handover method with a landing shock absorption structure according to claim 1, characterized in that: The random interference characteristic data includes the acceleration change amplitude, angular velocity fluctuation frequency, and environmental condition fluctuation value recorded during the flight. The control offset analysis result includes the attitude response delay detected during the handover of control rights, the direction offset angle caused by the operator's input difference, and the operation time difference. The control attitude optimization result includes the adjustment value for flight angle correction, the speed correction amount required for attitude stability, and the flight balance parameters. The landing impact prediction result includes the predicted impact force value when approaching the ground, the landing acceleration fluctuation range, and the change of the landing height. The shock absorption hardness optimization data includes the hardness adjustment amplitude required for the hydraulic shock absorber, the hydraulic oil flow rate, and the pressure valve opening and closing time. The enhanced shock absorption response signal includes the real-time adjustment instruction of the shock absorber, the attitude balance control signal, and the hardness dynamic adjustment amplitude.

3. The buffer-type UAV control right handover method with a landing shock absorption structure according to claim 1, characterized in that: The specific steps of generating random interference characteristic data by analyzing the speed, inclination angle, and displacement differences in multiple flight stages based on all the flight data of the drone are as follows: Based on all the flight data of the drone, extract the acceleration, angular velocity, and environmental parameters, separate the parameters of the flight stage, divide the speed, inclination angle, and displacement data according to the time axis, and segment and organize the data to generate a flight stage parameter set; Based on the flight stage parameter set, through comparing the acceleration and angular velocity changes in multiple flight stages, perform segmented difference calculations to identify the fluctuation amplitude and frequency of the flight stage, and generate a flight amplitude change result; Based on the flight amplitude change result, according to the abnormal fluctuation amplitude in the flight stage, screen the abnormal flight parameter range and classify it as an abnormal data segment to generate random interference characteristic data.

4. The buffer-type UAV control right handover method with a landing shock absorption structure according to claim 1, characterized in that: The specific steps of generating a control offset analysis result by detecting the control differences caused by the operator's input switch based on the random interference characteristic data are as follows: Based on the random interference feature data, combined with the acceleration and angular velocity during real-time flight, extract the sensor output at the moment of handover of control rights, identify the critical moment of input change, perform time-point cutting on the data, and generate operation input change data; Based on the operation input change data, compare the input switching point with the real-time parameters of the flight attitude, detect the attitude adjustment response time after the operator input switch, calculate the delay change, judge the lag situation of the flight attitude response, and generate an attitude response change result; Based on the attitude response change result, combined with the influence of the operator input on the attitude stability, analyze the attitude change amplitude and offset amount during the handover of control rights, and comprehensively consider the control difference and attitude offset situation to generate a control offset analysis result.

5. The buffer-type UAV control right handover method with a landing shock absorption structure according to claim 1, characterized in that: Based on the control offset analysis result, evaluate the attitude change of the aircraft, perform angle correction and speed adjustment, and the specific steps to generate an optimized control attitude result are as follows. Based on the control offset analysis result, extract the angle and speed data in the current flight attitude, perform real-time analysis of the angle and speed changes, capture the attitude offset value during flight through difference calculation, evaluate the attitude change trend, and generate attitude difference data; Based on the attitude difference data, compare the attitude offset value with the expected value of the target attitude, adjust the attitude control command of the aircraft, correct the angle and speed change amplitude, and recalculate the correction parameters of the angle and speed to generate attitude correction parameters; Based on the attitude correction parameters, feedback the attitude stability of the aircraft, and according to the corrected angle and speed changes, recalibrate the angle control and stability parameters of the aircraft to generate an optimized control attitude result.

6. The buffer-type UAV control right handover method with a landing shock absorption structure according to claim 1, characterized in that: Based on the optimized control attitude result, judge the impact force during the landing phase and predict the impact effect at the moment of touchdown. The specific steps to generate a touchdown impact prediction result are as follows. Based on the optimized control attitude result, call the real-time sensor data of the UAV approaching the ground, extract the current flight altitude, landing speed, and acceleration information, and synchronize the data with the flight attitude change to generate real-time landing data; Based on the real-time landing data, analyze the speed and acceleration fluctuations during the landing process, combined with the current attitude of the aircraft, evaluate the stability during landing, calculate the attitude adjustment requirements during the landing phase, and generate a landing attitude analysis result; Based on the landing attitude analysis result, calculate the impact force at the moment of touchdown, and combined with the landing speed, acceleration, and height change of the aircraft, evaluate the touchdown impact effect to generate a touchdown impact prediction result.

7. The buffer-type UAV control right handover method with a landing shock absorption structure according to claim 6, characterized in that: For the calculation of the impact force at the moment of touchdown, according to the formula: Obtain the impulse I of the impact force; Where, F is the impact force at touchdown, t is the contact time at the moment of touchdown, k is the damping coefficient, v is the speed at touchdown, a is the acceleration during landing, and h is the height of the aircraft.

8. The buffer-type UAV control right handover method with a landing shock absorption structure according to claim 1, characterized in that: Based on the touchdown impact prediction result, by calculating the change trend of the landing speed and acceleration, combined with the current attitude of the UAV and the ground height data, dynamically adjust the hydraulic hardness in real time according to the impact intensity to generate optimized shock absorption hardness data. The specific steps are as follows. Based on the ground impact prediction result, extract the landing speed, acceleration, and flight attitude data, combine with the real-time ground height, calculate the changes in speed and acceleration when approaching the ground, analyze the change trend of the impact intensity in multiple time periods, and generate the ground speed and attitude data; Based on the ground speed and attitude data, evaluate the current hydraulic oil flow rate of the hydraulic shock absorber, calculate the pressure impact of the change in impact intensity on the hydraulic structure, adjust the control valve opening of the pressure sensor, dynamically modify the hydraulic damping, and generate the hydraulic damping control data; Based on the hydraulic damping control data, by monitoring the change in impact intensity in real time, adjust the hardness response of the hydraulic shock absorber, balance the impact intensity and the response time of the shock absorption structure, optimize the working state of the shock absorber, and generate the shock absorption hardness optimization data.

9. The buffer-type UAV control right handover method with a landing shock absorption structure according to claim 8, characterized in that: For the evaluation of the current hydraulic oil flow rate of the hydraulic shock absorber, according to the formula: Calculate the pressure impact of the change in impact intensity on the hydraulic structure to obtain the hydraulic pressure P; Among them, F is the impact force when grounded, A is the piston area, V is the volume of the hydraulic oil, M is the flow velocity of the hydraulic oil, g is the acceleration due to gravity, h′ is the height difference through which the hydraulic oil passes, M 2 is the square of the flow velocity, and 2gh′ is the gravitational potential energy.

10. The buffer type UAV control right handover method with a landing shock absorption structure according to claim 1, characterized in that: Based on the shock absorption hardness optimization data, analyze the attitude fluctuations during flight, combine with the previously collected operation data, and adjust the shock absorption parameters during landing. The specific steps to generate the enhanced shock absorption response signal are as follows. Based on the shock absorption hardness optimization data, extract the speed and inclination data during the flight of the UAV, call the air pressure and wind speed information, and combine with the past flight attitude fluctuation data to calculate the impact of the attitude fluctuations during flight on the shock absorption structure during landing, and generate the attitude fluctuation analysis data; Based on the attitude fluctuation analysis data, compare the aircraft inclination and air pressure fluctuations, adjust the response speed of the shock absorber, optimize the working efficiency and hardness control of the shock absorber, and generate the shock absorption structure adjustment parameters; Based on the shock absorption structure adjustment parameters, monitor the attitude fluctuations during the landing process of the aircraft in real time, adjust the shock absorber parameters, and combine the attitude data and environmental conditions to generate the enhanced shock absorption response signal.

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