Stable air-drop dispensing method for unmanned aerial vehicle swarm under high-speed and large-disturbance conditions

Abstract

According to the stable air-drop dispensing method for the unmanned aerial vehicle swarm under the high-speed and large-disturbance condition, the unmanned aerial vehicles have stable initial conditions, the re-flight success rate is increased, and dispensing of all the unmanned aerial vehicles can be completed under the constraint of limited height and time. By analyzing air-drop test flight data of a large number of scattering units and an unmanned aerial vehicle and summarizing attitude swing characteristics of the scattering units in a parachute state at a balanced falling speed, a quick and stable cabin opening scattering scheme of release condition judgment adaptive grading processing is proposed for the first time; in the first-stage state, a relatively strict criterion is used for constraining the pitch angle and the angular rate at the cabin leaving moment, a relatively good initial condition is provided for the unmanned aerial vehicle, the problem that the cabin opening unmanned aerial vehicle scattering condition is severe under the high-speed and large-disturbance condition is solved, and the re-flight rate of the unmanned aerial vehicle is greatly improved.

Description

Technical Field

[0001] The invention belongs to the field of unmanned aerial vehicle swarm systems, and mainly relates to a method for stable airdrop distribution of unmanned aerial vehicle swarms. Background Art

[0002] When the carrier aircraft deploys the drone swarm system, the carrier aircraft deploys the deployment platform with the deployment unit. After the deployment platform glides at high speed to the target area, it deploys the deployment unit with a large number of swarm drones. The deployment unit opens the deceleration parachute in a timed sequence and decelerates to the equilibrium falling speed. Then it starts to deploy the swarm drones according to a certain deployment strategy, and the drones form a large-scale cluster formation to perform the scheduled task. When the deployment unit deploys the swarm drone, due to the huge disturbance of the deployment unit itself, the attitude and angular velocity change rapidly, if the deployment unit is too much pursued to be in a good attitude at the time of deployment, it is difficult to find a deployment point that meets the requirements by using a more stringent cabin condition judgment, resulting in the drone being unable to complete the cabin exit of all drones under the constraints of the deployment height, time, etc.; if a loose cabin condition judgment is used, the cabin exit attitude of the drone will be more random, which is not conducive to the drone go-around. Therefore, a stable and effective airdrop deployment drone cabin exit scheme is needed, so that the drone has a more stable initial condition and improves the success rate of go-around, and can complete the deployment of all drones under the constraints of limited height and time. Summary of the invention

[0003] In order to overcome the shortcomings of the prior art, the present invention proposes a method for stable aerial delivery and dispersion of a swarm of UAVs under high-speed and large-disturbance conditions, so that the UAVs have stable initial conditions and improve the success rate of go-around, and can complete the delivery and dispersion of all UAVs under the constraints of limited altitude and time.

[0004] A method for stable airdrop distribution of drone swarms under high-speed and large-disturbance conditions comprises the following steps:

[0005] Step 1: Navigation unit data filtering and smoothing;

[0006] The main control unit of the dispensing platform continuously obtains the current pitch angle, roll angle, yaw angle and pitch angle rate from the navigation unit, and smoothes the pitch angle data for the jump points in the pitch angle data used;

[0007] Step 2: Compare and judge the pitch angle after smoothing of the current frame of the navigation unit with the pitch angle after smoothing of the recorded N consecutive frames of the navigation unit to determine the launch conditions;

[0008] Step 2.1: Determine the first-level constrained launch conditions;

[0009] When all the requirements of the first-level constraint launch conditions are met at the same time, the first-level constraint algorithm is used. If any item of the first-level constraint launch condition is not met, jump to step 2.2;

[0010] The first-level constrained launch conditions are:

[0011] a. The current time is greater than the start time t of the first-level constraint 1 and is less than or equal to the termination time t of the first-level constraint 2 ;

[0012] b. The smoothed pitch angle is greater than the first-level constraint threshold δ min ;

[0013] c. The pitch angle rate of the current frame obtained from the navigation unit is greater than the minimum pitch angle rate ωz min and is less than the maximum pitch angular rate ωz max , the minimum value of the pitch angular rate ωz min and the maximum value of the pitch angular rate ωz max is the default value;

[0014] d. If the N / 2th frame of the pitch angle after smoothing of the first N frames is the extreme point of all data;

[0015] e. If before The pitch angle after frame smoothing shows a monotonically increasing trend;

[0016] f. The pitch angle after smoothing the current frame shows a monotonically decreasing trend compared with the pitch angle after smoothing the previous 1 to N / 2 frames;

[0017] g. The UAV launch time interval is t delay Second;

[0018] Step 2.2: Determine the secondary constraint launch conditions. If all the secondary constraint launch conditions are met at the same time, the secondary constraint algorithm is used; if any of the secondary constraint launch conditions is not met, jump to step 2.3;

[0019] The secondary constrained launch conditions are:

[0020] a. The current time is greater than the termination time t of the first-level constraint 2 and is less than or equal to the termination time t of the secondary constraint 3 ;

[0021] b. When the smoothed pitch angle is greater than the secondary constraint threshold δ min_2 ;

[0022] c. No constraints are imposed on the pitch rate;

[0023] d. If the N / 2th frame of the pitch angle after smoothing of the first N frames is the extreme point of all data;

[0024] e. before The pitch angle after frame smoothing shows a monotonically increasing trend;

[0025] f. The pitch angle after smoothing the current frame shows a monotonically decreasing trend compared with the pitch angle after smoothing the previous 1 to N / 2 frames;

[0026] g. UAV launch time interval t delay Second;

[0027] Step 2.3: Determine the three-level constraint launch conditions;

[0028] If the current time is greater than the termination time t of the secondary constraint 3 and the current time is less than the termination time t of the three-level constraint 4 When t delay The drone is launched with a period of seconds; if the current time is less than or equal to the termination time t of the secondary constraint 3 or the current time is greater than or equal to the termination time t of the third-level constraint 4 , the current frame processing is completed, jump to step 1, and start processing the next frame.

[0029] Furthermore, the steps of filtering and smoothing the pitch angle in the obtained navigation data are as follows:

[0030] Step 1-1: Data definition and initialization;

[0031] N smooth Maximum smoothing frames; N smooth =5;

[0032] f1_δ is the pitch angle of the first frame before the current frame; the initial value of the pitch angle of the first frame before the current frame is 0;

[0033] f2_δ is the pitch angle of the second frame before the current frame; the initial value of the pitch angle of the second frame before the current frame is 0;

[0034] f3_δ is the pitch angle of the third frame before the current frame; the initial value of the pitch angle of the third frame before the current frame is 0;

[0035] f4_δ is the pitch angle of the fourth frame before the current frame; the initial value of the pitch angle of the fourth frame before the current frame is 0;

[0036] count is the navigation unit update count; the initial value of count is 0; and count ≤ N smooth ;

[0037] δ is the pitch angle of the current frame;

[0038] ωz is the pitch angular velocity of the current frame;

[0039] sum δ is the cumulative sum of pitch angles;

[0040] δ smooth is the pitch angle after smoothing;

[0041] Step 1-2: Get the pitch angle δ and pitch angular velocity ωz of the navigation unit in the current frame, update the navigation unit update count, and increase the value of count by 1; if count is greater than or equal to N smooth , then let count = N smooth ; Otherwise, keep the value of count;

[0042] Step 1-3: updating the pitch angle of the first frame before the current frame, the pitch angle of the second frame before the current frame, the pitch angle of the third frame before the current frame, and the pitch angle of the fourth frame before the current frame;

[0043] The calculation steps for updating the pitch angle of the first frame before the current frame, the pitch angle of the second frame before the current frame, the pitch angle of the third frame before the current frame, and the pitch angle of the fourth frame before the current frame are as follows:

[0044] f4_δ=f3_δ;

[0045] f3_δ=f2_δ;

[0046] f2_δ=f1_δ;

[0047] f1_δ=δ;

[0048] Step 1-4: Get the smoothed pitch angle;

[0049] Sum the pitch angles of the current frame, the first frame before the current frame, the second frame before the current frame, the third frame before the current frame, and the fourth frame before the current frame;

[0050] sum δ =δ+f1_δ+f2_δ+f3_δ+f4_δ

[0051]

[0052] δ smooth This is the pitch angle after smoothing.

[0053] Furthermore, the steps of the specific algorithm of the first-level constraint are as follows:

[0054] 1) The current time is greater than the start time t of the first-level constraint 1 and is less than or equal to the termination time t of the first-level constraint 2When the condition state is calculated δ and state ωz ;

[0055] When δ smooth >δ min And δ smooth <0, state δ The value of is 1, when δ smooth >δ min or δ smooth <0When any item is not satisfied, state δ The value of is 0;

[0056] When ωz ≥ ωz min When ωz≤0, state ωz The value of is 1; when ωz ≥ ωz min Or ωz≤0, if any of the above conditions is not satisfied, state ωz The value of is 0;

[0057] Where ωz is the pitch rate of the navigation unit; ωz min Minimum value of pitch rate;

[0058] 2) Find out whether the smoothed pitch angle meets the extreme value judgment condition state extreme ;

[0059] If the N / 2th frame in the previous N frames is an extreme point in all data, and the previous The frame shows a monotonically increasing trend, and the current frame and the previous 1~N / 2 frames show a monotonically decreasing trend; the current frame and the previous 1~N / 2 frames show a monotonically decreasing trend, then the extreme value judgment condition state extreme =1; otherwise, the extreme value judgment condition state extreme =0;

[0060] 3) If state δ >0 and state ωz >0 and state extreme >0, and the time constraint is met, the sub-machine is allowed to be placed, and the time of placing the sub-machine is recorded; if state δ >0 or state ωz >0 or state extreme >0, if any condition is not met, jump to step 2.2;

[0061] The time constraint is: the current time is greater than the sum of the time of the last drone launch and the time interval between drone launches, and the current time is less than the termination time t of the first-level constraint 2 .

[0062] Furthermore, the steps of the secondary constraint algorithm are:

[0063] 1) The current time is greater than the termination time t of the first-level constraint 2 and is less than or equal to the termination time t of the secondary constraint 3 When calculating the secondary judgment condition state δ_2 ;

[0064] When δ smooth >δ min_2 And δ smooth <0, the secondary judgment condition state δ_2 The value of is 1, when δ smooth >δ min_2 or δ smooth <0When any item is not satisfied, the secondary judgment condition state δ_2 The value of is 0;

[0065] 2) Find out whether the smoothed pitch angle meets the secondary extreme value judgment condition state extreme_2 ;

[0066] If the N / 2th frame in the previous N frames is an extreme point in all data, and the previous The frames show a monotonically increasing trend, and the current frame and the previous 1~N / 2 frames show a monotonically decreasing trend, then the secondary extreme value judgment condition state extreme_2 =1; otherwise the secondary extreme value judgment condition state extreme_2 =0;

[0067] 3) If the secondary judgment condition state δ_2 >0 and the secondary extreme value judgment condition state extreme_2 >0, and the time constraint is met, the sub-machine is allowed to be placed and the time of placing the sub-machine is recorded; if any of the above conditions is not met, jump to step 2.3.

[0068] The beneficial effects of the present invention are as follows: compared with other open-cabin delivery technologies, the stable aerial delivery and spreading technology of a drone swarm under high-speed and large-disturbance conditions proposed by the present invention can achieve rapid and stable delivery of drones under the dual constraints of altitude and time, and can ensure that the drones have a good posture when leaving the cabin. It has been applied in the drone swarm system for airdrop, and the effectiveness of the invention has been proved through experiments; multiple experimental data show that the use of this method can achieve a 100% delivery success rate, and the drone go-around rate can also reach more than 66%. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 It is a flowchart of the algorithm single frame processing;

[0070] Figure 2 It is the pitch angle and spreading time diagram of the spreading unit;

[0071] Figure 3 It is the pitch angular velocity and spreading time diagram of the spreading unit;

[0072] Figure 4 It is the diagram of the track angle and spreading time of the spreading unit;

[0073] Figure 5 is the yaw rate and spreading time diagram of the spreading unit;

[0074] Figure 6 It is the diagram of the rolling angle and spreading time of the spreading unit;

[0075] Figure 7 It is the diagram of the rolling angular velocity and spreading time of the spreading unit.

[0076] In the figure, the red circle represents the drone launched within the first or second level constraints; the green circle represents the drone launched under the third level constraints; DETAILED DESCRIPTION

[0077] The present invention discloses a method for stable airdrop distribution of a swarm of unmanned aerial vehicles under high-speed and large-disturbance conditions: based on the empirical conclusions drawn from the flight test data of a large number of distribution units and unmanned aerial vehicles, it is necessary to dynamically determine the polar relationship between the attitude angle and the angular velocity, and when the pitch angle monotonically changes, it is the best time to drop. At this time, the distribution unit has a negative pitch angular velocity and moves in a direction perpendicular to the ground. After the unmanned aerial vehicle completes the exit from the cabin, it is basically in a vertical downward posture. The direction of the fuselage is close to the speed direction, the angle of attack and the sideslip angle are small, and the tilt stability of the fuselage can be ensured by pulling up in any direction in the vertical downward posture, which is conducive to the completion of the unmanned aerial vehicle's go-around. In order to ensure that all unmanned aerial vehicles can be successfully launched, a fast and stable cabin opening distribution scheme with adaptive hierarchical processing of release condition judgment is proposed, in which a relatively strict criterion is used to constrain the pitch angle and angular velocity at the time of exiting the cabin in the first level state, and the constraints are relaxed in the second and third levels.

[0078] The technical solution adopted by the present invention to solve the technical problem is a method for stable airdrop distribution of drone swarms under high-speed and large-disturbance conditions, comprising the following steps:

[0079] Step 1: Navigation unit data filtering and smoothing;

[0080] The main control unit of the dispensing platform continuously obtains the current pitch angle, roll angle, yaw angle and pitch angle rate from the navigation unit, and smoothes the pitch angle data for the jump points in the used pitch angle data; the pitch angle in the obtained navigation data is continuously filtered and smoothed, mainly to filter out possible jump points, so that the data is relatively smooth and reliable, and will not affect subsequent logical judgments;

[0081] The steps of filtering and smoothing the pitch angle in the obtained navigation data are as follows:

[0082] Step 1-1: Data definition and initialization;

[0083] N smooth Maximum smoothing frames; N smooth =5;

[0084] f1_δ is the pitch angle of the first frame before the current frame; the initial value of the pitch angle of the first frame before the current frame is 0;

[0085] f2_δ is the pitch angle of the second frame before the current frame; the initial value of the pitch angle of the second frame before the current frame is 0;

[0086] f3_δ is the pitch angle of the third frame before the current frame; the initial value of the pitch angle of the third frame before the current frame is 0;

[0087] f4_δ is the pitch angle of the fourth frame before the current frame; the initial value of the pitch angle of the fourth frame before the current frame is 0;

[0088] count is the navigation unit update count; the initial value of count is 0; and count ≤ N smooth ;

[0089] δ is the pitch angle of the current frame;

[0090] ωz is the pitch angular velocity of the current frame;

[0091] sum δ is the cumulative sum of pitch angles;

[0092] δ smooth is the pitch angle after smoothing;

[0093] Step 1-2: Get the pitch angle δ and pitch angular velocity ωz of the navigation unit in the current frame, update the navigation unit update count, and increase the value of count by 1; if count is greater than or equal to N smooth , then let count = N smooth ; Otherwise, keep the value of count;

[0094] Step 1-3: updating the pitch angle of the first frame before the current frame, the pitch angle of the second frame before the current frame, the pitch angle of the third frame before the current frame, and the pitch angle of the fourth frame before the current frame;

[0095] Update the pitch angle of the first frame before the current frame, the pitch angle of the second frame before the current frame, the pitch angle of the third frame before the current frame, and the pitch angle of the fourth frame before the current frame. The calculation steps are:

[0096] f4_δ=f3_δ;

[0097] f3_δ=f2_δ;

[0098] f2_δ=f1_δ;

[0099] f1_δ=δ

[0100] Step 1-4: Get the smoothed pitch angle;

[0101] Sum the pitch angles of the current frame, the first frame before the current frame, the second frame before the current frame, the third frame before the current frame, and the fourth frame before the current frame;

[0102] sum δ =δ+f1_δ+f2_δ+f3_δ+f4_δ

[0103]

[0104] δ smooth is the pitch angle after smoothing;

[0105] Step 2: Compare and judge the pitch angle after smoothing of the current frame of the navigation unit with the pitch angle after smoothing of the recorded N consecutive frames of the navigation unit to determine the launch conditions;

[0106] Step 2.1: Determine the first-level constrained launch conditions;

[0107] When all the requirements of the first-level constraint launch conditions are met at the same time, the first-level constraint algorithm is used. If any item of the first-level constraint launch condition is not met, jump to step 2.2;

[0108] The first-level constrained launch conditions are:

[0109] a. The current time is greater than t 1 and less than or equal to t 2 ;

[0110] b. The smoothed pitch angle is greater than the first-level constraint threshold δ min ;

[0111] c. The pitch angle rate of the current frame obtained from the navigation unit is greater than the minimum pitch angle rate ωz min and is less than the maximum pitch angular rate ωz max , the minimum value of the pitch angular rate ωz min and the maximum value of the pitch angular rate ωz max is the default value;

[0112] d. If the N / 2th frame of the pitch angle after smoothing of the first N frames is the extreme point of all data;

[0113] e. If before The pitch angle after frame smoothing shows a monotonically increasing trend;

[0114] f. The pitch angle after smoothing the current frame shows a monotonically decreasing trend compared with the pitch angle after smoothing the previous 1 to N / 2 frames;

[0115] g. The UAV launch time interval is t delay Second;

[0116] The specific steps of the first-level constraint algorithm are as follows:

[0117] 1) The current time is greater than the start time t of the first-level constraint 1 and is less than or equal to the termination time t of the first-level constraint 2 When the condition state is calculated δ and state ωz ;

[0118] When δ smooth >δ min And δ smooth <0, state δ The value of is 1, when δ smooth >δ min or δ smooth <0When any item is not satisfied, state δ The value of is 0;

[0119] When ωz ≥ ωz min When ωz≤0, state ωz The value of is 1; when ωz ≥ ωz min Or ωz≤0, if any of the above conditions is not satisfied, state ωz The value of is 0;

[0120] Where ωz is the pitch rate of the navigation unit; ωz min Minimum value of pitch rate;

[0121] 2) Find out whether the smoothed pitch angle meets the extreme value judgment condition state extreme ;

[0122] If the N / 2th frame in the previous N frames is an extreme point in all data, and the previous The frame shows a monotonically increasing trend, and the current frame and the previous 1~N / 2 frames show a monotonically decreasing trend; the current frame and the previous 1~N / 2 frames show a monotonically decreasing trend, then the extreme value judgment condition state extreme =1; otherwise, the extreme value judgment condition state extreme =0;

[0123] 3) If state δ >0 and state ωz >0 and state extreme>0, and the time constraint is met, the sub-machine is allowed to be placed, and the time of placing the sub-machine is recorded; if state δ >0 or state ωz >0 or state extreme >0, if any condition is not met, jump to step 2.2;

[0124] The time constraint is: the current time is greater than the sum of the time of the last drone launch and the time interval between drone launches, and the current time is less than the termination time t of the first-level constraint 2 ;

[0125] Step 2.2: Determine the secondary constraint launch conditions. If all the secondary constraint launch conditions are met at the same time, the secondary constraint algorithm is used; if any of the secondary constraint launch conditions is not met, jump to step 2.3;

[0126] The secondary constrained launch conditions are:

[0127] a. The current time is greater than t 2 and less than or equal to t 3 ;

[0128] b. When the smoothed pitch angle is greater than the secondary constraint threshold δ min_2 ;

[0129] c. No constraints are imposed on the pitch rate;

[0130] d. If the N / 2th frame of the pitch angle after smoothing of the first N frames is the extreme point of all data;

[0131] e. before The pitch angle after frame smoothing shows a monotonically increasing trend;

[0132] f. The pitch angle after smoothing the current frame shows a monotonically decreasing trend compared with the pitch angle after smoothing the previous 1 to N / 2 frames;

[0133] g. UAV launch time interval t delay Second;

[0134] The steps of the secondary constraint algorithm are:

[0135] 1) The current time is greater than the termination time t of the first-level constraint 2 and is less than or equal to the termination time t of the secondary constraint 3 When calculating the secondary judgment condition state δ_2 ;

[0136] When δ smooth >δ min_2 And δ smooth <0, the secondary judgment condition state δ_2 The value of is 1, when δsmooth >δ min_2 or δ smooth <0When any item is not satisfied, the secondary judgment condition state δ_2 The value of is 0;

[0137] 2) Find out whether the smoothed pitch angle meets the secondary extreme value judgment condition state extreme_2 ;

[0138] If the N / 2th frame in the previous N frames is an extreme point in all data, and the previous The frames show a monotonically increasing trend, and the current frame and the previous 1~N / 2 frames show a monotonically decreasing trend, then the secondary extreme value judgment condition state extreme_2 =1; otherwise the secondary extreme value judgment condition state extreme_2 =0;

[0139] 3) If the secondary judgment condition state δ_2 >0 and the secondary extreme value judgment condition state extreme_2 >0, and the time constraint is met, the sub-machine is allowed to be placed and the time of placing the sub-machine is recorded; if any of the above conditions is not met, jump to step 2.3;

[0140] Step 2.3: Determine the three-level constraint launch conditions;

[0141] If the current time is greater than the termination time t of the secondary constraint 3 and the current time is less than the termination time t of the three-level constraint 4 When t delay The UAV is launched at a period of seconds to ensure that all sub-machines can leave the cabin safely; if the current time is less than or equal to the termination time t of the secondary constraint 3 or the current time is greater than or equal to the termination time t of the third-level constraint 4 , the current frame processing is completed, jump to step 1-2, and start processing the next frame.

[0142] The ground coordinate system is defined as follows: the origin A is the position of the center of mass of the vehicle body at the moment of launch, the Ax axis points to the north in the horizontal plane, and the direction is positive; the Az axis is located in the horizontal plane and is perpendicular to the Ax axis, and points to the east as positive, and the Ay axis is perpendicular to the plane formed by Axz, forming a right-handed coordinate system;

[0143] The coordinate system of the aircraft is located as follows: the origin O is taken at the instantaneous inertial center of the UAV, Ox 1 The axis is consistent with the longitudinal axis of the drone, and the positive direction is the direction of the head; Oy 1 The axis is in the longitudinal symmetry plane of the drone, perpendicular to Ox 1 The axis pointing upward is positive; Oz 1 Axis perpendicular to x 1 Oy1 plane, forming a right-handed coordinate system. 1 The angle between the axis and the Axz plane is the pitch angle δ, and the longitudinal axis of the drone is positive when it is above the horizontal plane; the angle between the projection of the longitudinal axis of the drone in the horizontal plane and the Ax axis is the yaw angle ψ, and the left deviation is positive; 1 The angle between the axis and the plumb plane containing the longitudinal axis of the drone is the roll angle γ, with right roll being positive.

[0144] In order to make the purpose, content, and advantages of the present invention more clear, the specific implementation methods of the present invention are further described in detail below in conjunction with the accompanying drawings and examples.

[0145] A stable airdrop spreading technology of drone swarm under high speed and large disturbance conditions is implemented in the following steps:

[0146] 1: Start, set the start time and end time of the three constraint states, as well as the pitch angle and pitch angle velocity thresholds under the three constraint states;

[0147] 2: Continuously read the attitude angle and attitude angular velocity data given by the scattering unit navigation, perform model calculations and give instructions for opening the cabin and scattering.

[0148] Compared with other open-cabin delivery technologies, the stable airdrop and spreading technology of drone swarms under high-speed and large-disturbance conditions proposed in the present invention can achieve rapid and stable delivery of drones under the dual constraints of height and time, and can ensure that the drones have a good posture when leaving the cabin. It has been applied in the drone swarm system for airdrop, and the effectiveness of the invention has been proved through experiments. Taking a drone swarm project as an example, a total of 5 delivery tests were carried out. The method can achieve a 100% delivery success rate, and the drone go-around rate can reach more than 66%.

[0149] Table 1 is a statistical table of the release and go-around success rate of a certain drone swarm airdrop test;

[0150] Table 1 Statistics of the release and go-around success rate of a certain UAV swarm airdrop test

[0151]

[0152]

Claims

1. A method for stable airdrop distribution of drone swarms under high-speed and large-disturbance conditions, characterized in that: The steps include: Step 1: Navigation unit data filtering and smoothing; The main control unit of the dispensing platform continuously obtains the current pitch angle, roll angle, yaw angle and pitch angle rate from the navigation unit, and smoothes the pitch angle data for the jump points in the used pitch angle data; Step 2: Compare and judge the pitch angle after smoothing of the current frame of the navigation unit with the pitch angle after smoothing of the recorded N consecutive frames of the navigation unit to determine the launch conditions; Step 2.1: Determine the first-level constrained launch conditions; When all the requirements of the first-level constraint launch conditions are met at the same time, the first-level constraint algorithm is used. If any item of the first-level constraint launch condition is not met, jump to step 2.2; The first-level constrained launch conditions are: a. The current time is greater than the start time t1 of the first-level constraint and less than or equal to the end time t2 of the first-level constraint; b. The smoothed pitch angle is greater than the first-level constraint threshold δ min ; c. The pitch angle rate of the current frame obtained from the navigation unit is greater than the minimum pitch angle rate ωz min and is less than the maximum pitch angular rate ωz max , the minimum value of the pitch angular rate ωz min and the maximum value of the pitch angular rate ωz max is the default value; d. If the N / 2th frame of the pitch angle after smoothing of the first N frames is the extreme point of all data; e. If before The pitch angle after frame smoothing shows a monotonically increasing trend; f. The pitch angle after smoothing the current frame shows a monotonically decreasing trend compared with the pitch angle after smoothing the previous 1 to N / 2 frames; g. The UAV launch time interval is t delay Second; Step 2.2: Determine the secondary constraint launch conditions. If all the secondary constraint launch conditions are met at the same time, the secondary constraint algorithm is used; if any of the secondary constraint launch conditions is not met, jump to step 2.3; The secondary constrained launch conditions are: a. The current time is greater than the termination time t2 of the first-level constraint and less than or equal to the termination time t3 of the second-level constraint; b. When the smoothed pitch angle is greater than the secondary constraint threshold δ min_2 ; c. No constraints are imposed on the pitch rate; d. If the N / 2th frame of the pitch angle after smoothing of the first N frames is the extreme point of all data; e. before The pitch angle after frame smoothing shows a monotonically increasing trend; f. The pitch angle after smoothing the current frame shows a monotonically decreasing trend compared with the pitch angle after smoothing the previous 1 to N / 2 frames; g. UAV launch time interval t delay Second; Step 2.3: Determine the three-level constraint launch conditions; If the current time is greater than the termination time t3 of the second-level constraint and the current time is less than the termination time t4 of the third-level constraint, then the constraint is forced to be executed according to t delay The drone is launched in a cycle of seconds; If the current time is less than or equal to the termination time t3 of the second-level constraint or the current time is greater than or equal to the termination time t4 of the third-level constraint, the processing of the current frame ends, and the process jumps to step 1 to start processing the next frame.

2. The method for stable aerial delivery of drone swarms under high-speed and large-disturbance conditions according to claim 1 is characterized in that: The steps of filtering and smoothing the pitch angle in the obtained navigation data are as follows: Step 1-1: Data definition and initialization; N smooth Maximum smoothing frames; N smooth =5; f1_δ is the pitch angle of the first frame before the current frame; the initial value of the pitch angle of the first frame before the current frame is 0; f2_δ is the pitch angle of the second frame before the current frame; the initial value of the pitch angle of the second frame before the current frame is 0; f3_δ is the pitch angle of the third frame before the current frame; the initial value of the pitch angle of the third frame before the current frame is 0; f4_δ is the pitch angle of the fourth frame before the current frame; the initial value of the pitch angle of the fourth frame before the current frame is 0; count is the navigation unit update count; the initial value of count is 0; and count ≤ N smooth ; δ is the pitch angle of the current frame; ωz is the pitch angular velocity of the current frame; sum δ is the accumulated sum of pitch angles; δ smooth is the pitch angle after smoothing; Step 1-2: Get the pitch angle δ and pitch angular velocity ωz of the navigation unit in the current frame, update the navigation unit update count, and increase the value of count by 1; if count is greater than or equal to N smooth , then let count = N smooth ; Otherwise, keep the value of count; Step 1-3: updating the pitch angle of the first frame before the current frame, the pitch angle of the second frame before the current frame, the pitch angle of the third frame before the current frame, and the pitch angle of the fourth frame before the current frame; The calculation steps for updating the pitch angle of the first frame before the current frame, the pitch angle of the second frame before the current frame, the pitch angle of the third frame before the current frame, and the pitch angle of the fourth frame before the current frame are as follows: f4_δ=f3_δ; f3_δ=f2_δ; f2_δ=f1_δ; f1_δ=δ; Step 1-4: Get the smoothed pitch angle; Sum the pitch angles of the current frame, the first frame before the current frame, the second frame before the current frame, the third frame before the current frame, and the fourth frame before the current frame; sum δ =δ+f1_δ+f2_δ+f3_δ+f4_δ δ smooth This is the pitch angle after smoothing.

3. The method for stable aerial delivery of drone swarms under high-speed and large-disturbance conditions according to claim 1 is characterized in that: The specific steps of the first-level constraint algorithm are as follows: 1) When the current time is greater than the start time t1 of the first-level constraint and less than or equal to the end time t2 of the first-level constraint, calculate the judgment condition state δ and state ωz ; When δ smooth >δ min And δ smooth <0, state δ The value of is 1, when δ smooth >δ min or δ smooth <0When any item is not satisfied, state δ The value of is 0; When ωz ≥ ωz min When ωz≤0, state ωz The value of is 1; when ωz ≥ ωz min Or ωz≤0, if any of the above conditions is not satisfied, state ωz The value of is 0; Where ωz is the pitch rate of the navigation unit; ωz min Minimum value of pitch rate; 2) Find out whether the smoothed pitch angle meets the extreme value judgment condition state extreme ; If the N / 2th frame in the previous N frames is an extreme point in all data, and the previous The frame shows a monotonically increasing trend, and the current frame and the previous 1~N / 2 frames show a monotonically decreasing trend; the current frame and the previous 1~N / 2 frames show a monotonically decreasing trend, then the extreme value judgment condition state extreme =1; Otherwise, the extreme value judgment condition state extreme =0; 3) If state δ >0 and state ωz >0 and state extreme >0, and the time constraint is met, the sub-machine is allowed to be placed, and the time of placing the sub-machine is recorded; if state δ >0 or state ωz >0 or state extreme >0, if any condition is not met, jump to step 2.2; The time constraint is: the current time is greater than the sum of the time of the last drone launch and the drone launch time interval, and the current time is less than the termination time t2 of the first-level constraint.

4. The method for stable aerial delivery of drone swarms under high-speed and high-disturbance conditions according to claim 1 is characterized in that: The steps of the secondary constraint algorithm are: 1) When the current time is greater than the termination time t2 of the first-level constraint and less than or equal to the termination time t3 of the second-level constraint, calculate the second-level judgment condition state δ_2 ; When δ smooth >δ min_2 And δ smooth <0, the secondary judgment condition state δ_2 The value of is 1, when δ smooth >δ min_2 or δ smooth <0When any item is not satisfied, the secondary judgment condition state δ_2 The value of is 0; 2) Find out whether the smoothed pitch angle meets the secondary extreme value judgment condition state extreme_2 ; If the N / 2th frame in the previous N frames is an extreme point in all data, and the previous The frames show a monotonically increasing trend, and the current frame and the previous 1~N / 2 frames show a monotonically decreasing trend, then the secondary extreme value judgment condition state extreme_2 =1; otherwise the secondary extreme value judgment condition state extreme_2 =0; 3) If the secondary judgment condition state δ_2 >0 and the secondary extreme value judgment condition state extreme_2 >0, and the time constraint is met, the sub-machine is allowed to be placed and the time of placing the sub-machine is recorded; if any of the above conditions is not met, jump to step 2.

3.

5. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed, a method for stable aerial delivery and dispersion of a swarm of unmanned aerial vehicles under high-speed and large-disturbance conditions as described in any one of claims 1 to 4 is implemented.

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