Cooperative route planning method for simultaneous arrival of multiple unmanned aerial vehicles in different directions

Abstract

The invention provides a cooperative flight path planning method for simultaneous arrival of multiple unmanned aerial vehicles in different directions, and relates to the field of cooperative planning and control of the multiple unmanned aerial vehicles, and the method comprises the specific steps: constructing a reference line flight guidance vector field of the unmanned aerial vehicles and a fixed-point circling vector field at a target position, and enabling the multiple unmanned aerial vehicles to perform cooperative flight path planning according to an instruction of flying to the target circling position; the unmanned aerial vehicle flies to the target hovering position from the respective initial positions at the same time, and real-time track adjustment of the unmanned aerial vehicle is achieved through a datum line flight guidance vector field and a fixed-point hovering vector field; the phase intervals of the multiple unmanned aerial vehicles are adjusted, so that the multiple unmanned aerial vehicles located at the target circling position fly above the target position at the same phase intervals in a circling mode; and an instruction for arriving at the target position is sent to the multiple unmanned aerial vehicles, and the multiple unmanned aerial vehicles fly to the target position from the target hovering position at the same time. According to the invention, based on the tau strategy, multi-unmanned-aerial-vehicle flight path planning is carried out, so that multi-unmanned-aerial-vehicle multi-state synchronization is realized, and the safety and reliability of task execution of the unmanned aerial vehicles are improved.

Description

Technical Field

[0001] The present invention relates to the field of collaborative planning and control of multiple unmanned aerial vehicles, and in particular to a collaborative trajectory planning method for multiple unmanned aerial vehicles to arrive at different locations simultaneously. Background Art

[0002] When multiple UAVs collaborate to complete flight missions, they usually need to reach the same or different target locations in a specified direction at the same time, such as multiple aircraft attacking one or more scattered targets at the same time, and multiple UAVs taking off from different airports gathering at a certain location to form a tight formation. In addition, the collaborative trajectory planning method for multiple UAVs to arrive at the same time in multiple directions also has important application value in the fields of disaster relief, data exchange, tracking detection, and reconnaissance and strike.

[0003] The multi-directional simultaneous arrival trajectory planning of multiple UAVs not only requires guiding the UAVs to fly to the designated target point in space, but also requires strict compliance with the time and entry direction constraints. Therefore, it is more difficult than traditional three-dimensional position trajectory planning and belongs to the 4D trajectory planning problem. Collaborative 4D trajectory planning has been widely studied and applied in the fields of airport approach and landing control and air traffic management in the civil aviation field, but in the field of UAVs, especially when considering the problem of simultaneous arrival constraints, the research results are still very limited. In recent years, some scholars have studied the problem of simultaneous arrival of drone clusters considering time constraints. For example, in patent CN115328206A, a time-coordinated guidance method based on speed regulation is proposed, which takes the speed and direction of the drone as the adjustment amount to dynamically adjust the attack time and angle of the drone. This patent is different from the trajectory planning guidance method adopted by the present invention, and it is impossible to reach and pass through the target position at a specified speed; in patent CN114237304B, the Dubins arc route is adopted to adjust the flight track length of multiple drones by adjusting the circling radius or inserting a circling waiting action, and indirectly adjust the arrival time of the drones to the assembly area. Unlike the trajectory planning method of the present invention, the planning accuracy is weak; in patent CN111273686B, a genetic algorithm is used to optimize the drone track to achieve the minimum time deviation distribution of the drone arriving at the same target point. Unlike the trajectory planning method of the present invention, the synchronization planning ability is weak. The present invention mainly aims at the trajectory planning and simultaneous arrival problems of drone clusters, and proposes a method based on the tau principle. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention provides a collaborative trajectory planning method for multiple UAVs to arrive at different directions at the same time. Through the tau guidance strategy, according to the parameters such as the positions, arrival times, flight speeds and flight directions of the multiple UAVs, the velocity models of the UAVs in the baseline coordinate system are obtained, so as to construct the baseline flight guidance vector field of the trajectory of the UAVs flying from an initial position to a target position and the fixed-point hovering vector field of the UAVs at the target position, and obtain the target motion trajectory of the UAVs. Therefore, when hovering instructions to fly to the target position are sent to the multiple UAVs at the same time, the multiple UAVs can hover above the target position at a safe confrontation distance, thereby realizing the synchronization of multiple states of the multiple UAVs, effectively reducing the uncertainty of the flight paths of the multiple UAVs, and ultimately improving the safety and reliability of the multiple UAVs in mission execution.

[0005] The present invention provides a collaborative trajectory planning method for multiple UAVs to arrive at different locations simultaneously, and the specific implementation steps include:

[0006] S1. Constructing a baseline flight guidance vector field for the UAV and a fixed-point circling vector field at the target position. In the process of multiple UAVs flying from their respective initial positions to the target circling position at the same time according to the instruction to fly to the target circling position, the UAVs use the baseline flight guidance vector field and the fixed-point circling vector field at the target point position to achieve real-time track adjustment, which specifically includes the following sub-steps:

[0007] S11. According to the current position, current motion state and target position of the drone, a drone motion model in the baseline coordinate system is established. The velocity model expression in the drone motion model is:

[0008]

[0009] The left side of the equation represents the three-axis velocities of l, v, and z in the baseline coordinate system, V d represents the speed when passing through the target position, T represents the expected time to reach the target position, t represents the current motion time, G0 is a variable parameter in the guided motion, G v represents the function related to the preset arrival time and the current movement time, D0 is the relevant parameter of the UAV movement, ε represents the distance from the baseline, Δh represents the deviation between the current height and the target height, k l , k v and k z are the coupling coefficients respectively;

[0010] S12. According to the velocity model of the UAV in the baseline coordinate system obtained in step S11, a baseline flight guidance vector field is established. The specific expression is:

[0011]

[0012] Among them, ψ d is the azimuth of the baseline in the baseline coordinate system; l, v and z are three coordinate axes in the baseline coordinate system;

[0013] S13. According to the real-time position state of the UAV, the target hovering position and the target hovering trajectory, the fixed-point hovering vector field of the UAV in the entire flight space is obtained. The expression of the fixed-point hovering guidance vector is:

[0014]

[0015] Among them, p r =[X r ,Y r ,Z r ] T represents the relative position vector from the target position to the drone, τ(p r ) is the contraction term, guiding p r Converge to the target circling trajectory within the expected time T, R(p r ) is a rotation term, which makes the UAV fly around the target position when the position converges to the target circle. Indicates the rate of change of the center position of the UAV's hovering circle, R t represents the target circling radius of the drone, r represents the distance between the drone and the target position, and v s represents the expected hovering flight speed of the UAV, η=±1 is used to select the hovering direction of the UAV, Δh represents the height difference between the current position of the UAV and the expected hovering trajectory, and k t , k z represents the coupling coefficient;

[0016] S2, multiple UAVs adjust the phase interval so that multiple UAVs located at the target hovering position hover above the target position with the same phase interval, specifically including the following sub-steps:

[0017] S21, set N respectively UAV Hovering Guidance Strategy for a UAV ni , expected phase interval φ tij (i,j=1...N UAV ), target hovering horizontal position (X T ,Y T ), the radius of the circling confrontation is R t and the height H from the target position t ;

[0018] S22, based on step S21, arbitrarily select the phase interval φ between the i-th UAV and the j-th UAV from multiple UAVs ij , and the expected phase interval φ is obtained tijDeviation Δφ ij =φ tij -φ ij ;

[0019] S23, by controlling the angular velocity of multiple drones, the deviation between the drones is Δφ ij tends to zero, so that multiple UAVs can hover over the target position with a desired phase interval;

[0020] S3. Sending instructions to the multiple drones hovering above the target position to arrive at the target position, so that the multiple drones fly to the target position from the target hovering position at the same time.

[0021] Preferably, in step S11, l, v and z are defined as three coordinate axes in the baseline coordinate system, with the coordinate axis l pointing to the target position along the baseline, the coordinate axis v being perpendicular to the baseline, and the coordinate axis z pointing vertically upward.

[0022] Preferably, in step S1, the speed of the coordinate axis l is obtained based on the intrinsic tau-G guidance strategy, and the speeds of the coordinate axis v and the coordinate axis z are obtained based on the improved tau-G guidance strategy.

[0023] Preferably, the intrinsic tau-G (tau gravity) guidance strategy obtains the expressions of the position, velocity and acceleration of the UAV along any axis in any coordinate system as follows:

[0024]

[0025] Among them, χ0 represents the initial position of the UAV, T is the expected arrival time, k χ represents the coupling coefficient.

[0026] Preferably, according to the improved tau-G (tau gravity) guidance strategy, the expressions of the position, velocity and acceleration of the UAV along any axis in any coordinate system are obtained as follows:

[0027]

[0028] Among them, X T represents the target position, G0 represents the initial distance to the target position, G v is a function related to the initial position and initial velocity of the UAV, ρ x0 is a function related to the initial position and target position of the UAV, k x represents the coupling coefficient.

[0029] Preferably, in step S23, the angular rate expression of the plurality of drones is:

[0030]

[0031] Preferably, in step S3, the motion of the multi-UAV in the horizontal direction tracks the speed instruction V in the baseline flight tau vector field. li and V vi , i=1, ..., N, the velocity instruction V in the tau vector field of the multi-UAV motion tracking baseline flight in the vertical direction zi , i=1,…,N.

[0032] Compared with the prior art, the present invention has the following advantages:

[0033] 1. The method of the present invention uses tau clues to introduce the target state achievement time into the UAV collaborative trajectory planning, which can guide the position, speed, and orientation of each UAV to converge to the target state smoothly at the same time, and can achieve the timed synchronous convergence of multiple UAVs and multiple motion states.

[0034] 2. The method of the present invention can provide a continuous description of the time-varying position and speed under the premise that the initial position, target position and arrival time of the UAV are given, without the need to decompose the workspace, and has higher planning efficiency.

[0035] 3. The present invention uses the time-space coordinated multi-UAV trajectory planning technology to enable the multi-UAV system to have dynamic planning and decision-making capabilities in tasks with strict time constraints, and can respond to combat tasks autonomously and quickly. This method plays an important role in improving the UAV collaborative combat capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a flow chart of the collaborative trajectory planning method for multiple UAVs to arrive at different locations simultaneously according to the present invention;

[0037] Figure 2 It is a baseline vector field diagram used in the collaborative trajectory planning method for multiple UAVs to arrive at different positions simultaneously in the present invention;

[0038] Figure 3 A coordinate system diagram of a baseline vector field in a collaborative trajectory planning method for multiple UAVs to arrive at different locations simultaneously according to the present invention;

[0039] Figure 4 The invention is used for the method of collaborative trajectory planning for multiple UAVs to arrive at different positions simultaneously, and the fixed-point hovering guidance vector field guides the UAVs to converge to a target circle with a variable center;

[0040] Figure 5 A three-dimensional mission trajectory diagram of the collaborative trajectory planning method for multiple UAVs to arrive at different locations simultaneously according to the present invention;

[0041] Figure 6It is a two-dimensional mission trajectory diagram of the collaborative trajectory planning method for the simultaneous arrival of multiple UAVs at different locations according to the present invention. DETAILED DESCRIPTION

[0042] In order to fully describe the technical content, objectives and effects of the present invention, the following will be described in detail with reference to the accompanying drawings.

[0043] like Figure 1 As shown in Figure 1, the collaborative trajectory planning method for multiple UAVs to arrive at different locations simultaneously is implemented as follows:

[0044] S1. Constructing a baseline flight guidance vector field for UAVs and a fixed-point circling vector field at a target position. Multiple UAVs simultaneously fly from their respective initial positions to the target circling position according to the instruction to fly to the target circling position. The UAVs use the baseline flight guidance vector field and the fixed-point circling vector field at the target position to adjust the track in real time.

[0045] S2. The multiple UAVs adjust their phase intervals so that the multiple UAVs located at the target hovering position hover over the target position with the same phase interval.

[0046] S3. Sending instructions to the multiple drones hovering above the target position to arrive at the target position, so that the multiple drones fly to the target position from the target hovering position at the same time.

[0047] The specific implementation steps are as follows:

[0048] S1. Constructing a baseline flight guidance vector field for UAVs and a fixed-point circling vector field at a target position. Multiple UAVs simultaneously fly from their respective initial positions to the target circling position according to the instruction to fly to the target circling position. The UAVs use the baseline flight guidance vector field and the fixed-point circling vector field at the target position to adjust the track in real time.

[0049] S11. According to the intrinsic tau-G (tau gravity) guidance strategy, the expressions for the position, velocity and acceleration of the UAV along any axis in any coordinate system are:

[0050]

[0051] Among them, χ0 represents the initial position of the UAV, T is the expected arrival time, k χ represents the coupling coefficient.

[0052] According to the improved tau-G (tau gravity) guidance strategy, the expressions of the position, velocity and acceleration of the UAV along any axis in any coordinate system are obtained as follows:

[0053]

[0054] Among them, X T represents the target position, G0 represents the initial distance to the target position, G v is a function related to the initial position and initial velocity of the UAV, ρ x0 is a function related to the initial position and target position of the UAV, k x represents the coupling coefficient.

[0055] Based on the above expressions of the position, velocity and acceleration of the UAV along any axis in any coordinate system obtained by the intrinsic tau-G (tau gravity) guidance strategy and the improved tau-G (tau gravity) guidance strategy, the UAV motion model in the baseline coordinate system is established according to the current position, current motion state and target position of the UAV. The velocity model expression in the UAV motion model is:

[0056]

[0057] Among them, V d represents the speed when passing through the target position, G0 is the variable parameter in the guided motion, G v represents the function related to the preset arrival time and the current movement time, D0 is the UAV movement related parameter, ε represents the distance from the baseline, Δh represents the deviation between the current height and the target position height, k l , k v and k z are the coupling coefficients respectively. Indicates the penetration speed V d The distance from the uniform motion to the target position and the deviation from the projection of the vector from the current position of the UAV to the target position on the baseline; the guidance goal of the UAV motion is that when the time approaches the target position time, the distance ε of the UAV from the baseline, the distance deviation D, and the height deviation Δh all approach 0, and the movement speed of the UAV approaches the penetration speed.

[0058] Specifically, if Figure 3 As shown in the figure, the dotted line represents the baseline, where M0 represents the starting point of the baseline, and M g It represents the focus of the baseline, and stipulates that l, v, and z are the three coordinate axes in the baseline coordinate system. Coordinate axis l points to the target position along the baseline, coordinate axis v is perpendicular to the baseline, and coordinate axis z is vertically upward; the speed of coordinate axis l is obtained based on the intrinsic tau-G strategy. The classic tau-G strategy provides guidance with the position converged to the baseline and the height direction. The speeds of coordinate axis v and coordinate axis z are obtained based on the improved tau-G strategy. The improved tau-G guidance strategy provides guidance along the baseline direction to guide the UAV to pass through the target position at the expected time and at the expected speed.

[0059] S12, such as Figure 2 As shown, according to the velocity model of the UAV in the baseline coordinate system obtained in step S11, the baseline flight guidance vector field is established, and the specific expression is:

[0060]

[0061] Among them, ψ d is the azimuth of the baseline in the baseline coordinate system; l, v and z are the three coordinate axes in the baseline coordinate system.

[0062] S13. According to the real-time position state of the UAV, the target hovering position and the target hovering trajectory, the fixed-point hovering vector field of the UAV in the entire flight space is obtained. The expression of the fixed-point hovering guidance vector is:

[0063]

[0064] Among them, p r =[X r ,Y r ,Z r ] T represents the relative position vector from the target position to the drone, τ(p r ) is the contraction term, the direction points to the target position, and the guide p r Converge to the target circling trajectory within the expected time T, S(p r ) is a rotation term, located in the limit cycle plane, and its direction is perpendicular to the plane where the circling trajectory is located, so that the UAV position converges to the target circle and flies around the target. The unit vector in the direction of S(pr) is defined as Where r = || p rt ||, Yes r The component in the target hovering plane; X r With Y r They are p rt The X and Y axis coordinates; Indicates the rate of change of the center position of the UAV's hovering circle, R t represents the target circling radius of the drone, r represents the distance between the drone and the target position, and v s It indicates the expected hovering flight speed of the UAV. η=±1 is used to select the hovering direction of the UAV. When η=1, the hovering direction is counterclockwise, otherwise it is clockwise.

[0065] S2. The multiple UAVs adjust their phase intervals so that the multiple UAVs located at the target hovering position hover over the target position with the same phase interval.

[0066] S21, set N respectively UAV Hovering Guidance Strategy for a UAV ni, expected phase interval φ tij (i,j=1...N UAV ), target hovering horizontal position (X T ,Y T ), circling confrontation radius R t and the height H from the target position t .

[0067] like Figure 4 As shown in the figure, the arrows in the figure represent the guidance vector field established according to the tau guidance strategy in the UAV flight space. When the UAV is at different positions in the space, the corresponding guidance vector is called. The solid line in the figure represents the flight trajectory of the single-price UAV moving towards the target trajectory under the guidance of the vector field. UAV The drones start from different starting positions (X ni ,Y ni ,Z ni )(i=1...N UAV ) starts from the guidance strategy U ni Under the action of tij (i,j=1...N UAV ) are evenly distributed at the target horizontal position (X T ,Y T ) is the center of the circle, and the opposing radius is R t , the height from the target is H t The aircraft will circle the target circle at the target flight speed, waiting for the mission window to fly to the target position from multiple directions at the same time.

[0068] S22, based on step S21, arbitrarily select the phase interval φ between the i-th UAV and the j-th UAV from multiple UAVs ij , and the expected phase interval φ is obtained tij Deviation Δφ ij =φ tij -φ ij .

[0069] S23, by controlling the angular velocity of multiple drones, the deviation between the drones is Δφ ij tends to zero, so that multiple UAVs can hover above the target position at the desired phase interval. The angular rate expression of multiple UAVs is:

[0070]

[0071] S3. Sending instructions to the multiple drones hovering above the target position to arrive at the target position, so that the multiple drones fly to the target position from the target hovering position at the same time.

[0072] Each drone uses the baseline flight vector field obtained in step S1 as a guide, so that multiple drones fly to the target along the baseline from different directions under the action of the baseline flight vector field until they reach the target position. Furthermore, in order for multiple drones to reach the target position at the same time, the horizontal movement of multiple drones is required to track the speed instruction V of the baseline flight vector field. li and V vi (i=1,…,N), the velocity command V of the vertical tracking baseline flight vector field of multiple UAVs zi (i=1,…,N).

[0073] The following is a further description of a collaborative trajectory planning method for multiple UAVs to arrive at different locations simultaneously according to the present invention in conjunction with an embodiment:

[0074] In this specific embodiment, three UAVs are used to confront and track the target position at the same altitude. The multiple UAVs start from the initial position with an initial velocity V0, fly along the baseline flight guidance vector field, pass through the airspace where obstacles may exist, and arrive at the target position at a speed V0 according to the arrival time T. d Passing through the target position P d =[xd,yd,zd] T The specific steps are as follows:

[0075] S1. Construct the baseline flight guidance vector field and the fixed-point circling vector field at the target position of the three UAVs respectively. The three UAVs fly to the target circling position from their respective initial positions at the same time according to the command to fly to the target circling position. The three UAVs use the baseline flight guidance vector field and the fixed-point circling vector field at the target position to achieve real-time track adjustment. The three-dimensional mission trajectory diagram is shown in FIG. Figure 5 As shown in the figure, the pink, black and green dotted lines represent the flight trajectories of the three drones. The three drones start from different positions and fly in a circling trajectory towards the target. The drone trajectories gradually converge to the vicinity of the target trajectory and begin to circle. When the simultaneous arrival command is issued, the three drones fly to the target point at the same time from different positions of the circling trajectory and arrive at the mission target point at the same time. The two-dimensional mission trajectory diagram is shown in Figure 6 As shown in the figure, pink, green and black represent the planar projections of different UAV flight trajectories. After the UAV takes off, the flight trajectory gradually converges to a circling trajectory and finally reaches the mission target position at the same time.

[0076] S11. According to the current position, current motion state and target position of the UAV, a UAV motion model in the baseline coordinate system is established to obtain a velocity model in the UAV motion model.

[0077] S12, according to the velocity model of the UAV in the baseline coordinate system obtained in step S11, establish the baseline flight guidance vector field, as follows: Figure 2As shown in the figure, M0 is the starting point of the baseline of the UAV, Mg is the end point of the baseline of the UAV, and all points throughout the flight space are arrows of the baseline flight guidance vector field; the actual flight track of the UAV obtains the expected speed according to the guidance vector as the velocity vector and the relative position relationship of the UAV, and then adjusts to the optimal expected speed, and then continuously adjusts, and finally realizes that the actual flight track of the UAV coincides with the end point of the baseline at the end point Mg of the baseline of the UAV.

[0078] S13. According to the real-time position state of the UAV, the target hovering position and the target hovering trajectory, a fixed-point hovering vector field of the UAV in the entire flight space is obtained.

[0079] S2. The multiple UAVs adjust their phase intervals so that the multiple UAVs located at the target hovering position hover over the target position with the same phase interval.

[0080] S21. Set the initial position of the first UAV to (-400, -400, 100), the initial position of the second UAV to (400, -400, 100), the initial position of the third UAV to (400, 400, 100), the mission target position to (0, 0, 100), and the confrontation hovering radius R t =300 meters, standoff height H t = 100 meters, circling confrontation phase interval φ t =120°.

[0081] The three drones started from different initial positions and flew along Figure 4 The direction of the circle converges to the confrontation circle radius R with the mission target as the center t =300m confrontation circle and at a confrontation height H t =100 meters to keep tracking the mission target.

[0082] S22: Based on step S21, randomly select the phase interval φ between the i-th UAV and the j-th UAV from the three UAVs. ij , and the expected phase interval φ is obtained tij Deviation Δφ ij =φ tij -φ ij .

[0083] S23, by controlling the angular velocity of the three UAVs, the deviation between the UAVs is Δφ ij tends to zero, so that the three UAVs fly in a circle above the target position with the desired phase interval.

[0084] S3, send a command to the three drones hovering above the target position to arrive at the target position, then the three drones fly to the target position from the target hovering position at the same time, such as Figure 6 shown.

[0085] Specifically, in this step, the three UAVs use the baseline flight vector field obtained in step S1 as a guide, and fly to the target along the baseline from different directions under the action of the baseline flight vector field until they reach the target position. The horizontal motion of the three UAVs tracks the speed instruction V of the baseline flight vector field li and V vi (i=1,…,N), the velocity instructions V of the vertical tracking baseline flight vector field of the three UAVs zi (i=1,…,N).

[0086] The above embodiments are only descriptions of the preferred implementation modes of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A collaborative trajectory planning method for multiple UAVs to arrive at different locations simultaneously, characterized in that: The specific implementation steps include: S1. Constructing a baseline flight guidance vector field for the UAV and a fixed-point circling vector field at the target position. In the process of multiple UAVs flying from their respective initial positions to the target circling position at the same time according to the instruction to fly to the target circling position, the UAVs use the baseline flight guidance vector field and the fixed-point circling vector field at the target point position to achieve real-time track adjustment, which specifically includes the following sub-steps: S11. According to the current position, current motion state and target position of the drone, a drone motion model in the baseline coordinate system is established. The velocity model expression in the drone motion model is: The left side of the equation represents the three-axis velocities of l, v, and z in the baseline coordinate system, V d represents the speed when passing through the target position, T represents the expected time to reach the target position, t represents the current motion time, G0 is a variable parameter in the guided motion, G v represents the function related to the preset arrival time and the current movement time, D0 is the relevant parameter of the UAV movement, ε represents the distance from the baseline, Δh represents the deviation between the current height and the target height, k l , k v and k z are the coupling coefficients respectively; S12. According to the velocity model of the UAV in the baseline coordinate system obtained in step S11, a baseline flight guidance vector field is established. The specific expression is: Among them, ψ d is the azimuth of the baseline in the baseline coordinate system; l, v and z are three coordinate axes in the baseline coordinate system; S13. According to the real-time position state of the UAV, the target hovering position and the target hovering trajectory, the fixed-point hovering vector field of the UAV in the entire flight space is obtained. The expression of the fixed-point hovering guidance vector is: Among them, p r =[X r ,Y r ,Z r ] T represents the relative position vector from the target position to the drone, τ(p r ) is the contraction term, guiding p r Converge to the target circling trajectory within the expected time T, R(p r ) is a rotation term, which makes the UAV fly around the target position when the position converges to the target circle. Indicates the rate of change of the center position of the UAV's hovering circle, R t represents the target circling radius of the drone, r represents the distance between the drone and the target position, and v s represents the expected hovering flight speed of the UAV, η=±1 is used to select the hovering direction of the UAV, Δh represents the height difference between the current position of the UAV and the expected hovering trajectory, and k t , k z represents the coupling coefficient; S2, multiple UAVs adjust the phase interval so that multiple UAVs located at the target hovering position hover above the target position with the same phase interval, specifically including the following sub-steps: S21, set N respectively UAV Hovering Guidance Strategy for a UAV ni , expected phase interval φ tij (i,j=1...N UAV ), target hovering horizontal position (X T ,Y T ), the radius of the circling confrontation is R t and the height H from the target position t ; S22: Based on step S21, randomly select the phase interval φ between the i-th UAV and the j-th UAV from multiple UAVs. ij , and the expected phase interval φ is obtained tij Deviation Δφ ij =φ tij -φ ij ; S23, by controlling the angular velocity of multiple drones, the deviation between the drones is Δφ ij tends to zero, so that multiple UAVs can hover over the target position with a desired phase interval; S3. Sending instructions to the multiple drones hovering above the target position to arrive at the target position, so that the multiple drones fly to the target position from the target hovering position at the same time.

2. The collaborative trajectory planning method for multiple UAVs to arrive at different locations simultaneously according to claim 1, characterized in that: In step S11, l, v and z are defined as three coordinate axes in the reference line coordinate system, wherein the coordinate axis l points to the target position along the reference line, the coordinate axis v is perpendicular to the reference line, and the coordinate axis z points vertically upward.

3. The collaborative trajectory planning method for multiple UAVs to arrive at different locations simultaneously according to claim 1 or 2, characterized in that: In step S1, the speed of the coordinate axis l is obtained based on the intrinsic tau-G guidance strategy, and the speeds of the coordinate axes v and z are obtained based on the improved tau-G guidance strategy.

4. The collaborative trajectory planning method for multiple UAVs to arrive at different locations simultaneously according to claim 1 or 2, characterized in that: According to the intrinsic tau-G guidance strategy, the expressions of the position, velocity and acceleration of the UAV along any axis in any coordinate system are obtained as follows: Among them, χ0 represents the initial position of the UAV, T is the expected arrival time, k χ represents the coupling coefficient.

5. The collaborative trajectory planning method for multiple UAVs to arrive at different locations simultaneously according to claim 1 or 2, characterized in that: According to the improved tau-G guidance strategy, the expressions of the position, velocity and acceleration of the UAV along any axis in any coordinate system are obtained as follows: Among them, X T represents the target position, G0 represents the initial distance to the target position, G v is a function related to the initial position and initial velocity of the UAV, ρ x0 is a function related to the initial position and target position of the UAV, k x represents the coupling coefficient.

6. The collaborative trajectory planning method for multiple UAVs to arrive at different locations simultaneously according to claim 1, characterized in that: In step S23, the angular rate expressions of the multiple drones are:

7. The collaborative trajectory planning method for multiple UAVs to arrive at different locations simultaneously according to claim 1, characterized in that: In step S3, the multi-UAV motion in the horizontal direction tracks the speed instruction V in the baseline flight vector field. li and V vi , i=1, ..., N, the velocity instruction V of the multi-UAV in the vertical motion tracking baseline flight vector field zi , i=1,…,N.

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