An unmanned aerial vehicle formation obstacle avoidance control algorithm based on an improved artificial potential field method

Abstract

This invention discloses a drone swarm formation obstacle avoidance control method based on an improved artificial potential field method, comprising the following steps: Step 1, performing formation control of the drone swarm based on a virtual structure method; Step 2, for the i-th drone, during its movement towards the target point, determining whether the distance between the i-th drone and the obstacle is greater than the safe distance using the artificial potential field method. If the distance between the i-th drone and the obstacle is greater than the safe distance, it continues to move towards the target point; if the distance between the i-th drone and the obstacle is less than the safe distance, an improved artificial potential field method is introduced for obstacle avoidance until the target point is reached; the improved artificial potential field method for obstacle avoidance specifically involves: making F i ob With F i att Maintain orthogonality, when F i att With F i ob When the angle between them is 0, only F is retained. i ob China and F i att Orthogonal components F i obrep Remove F i att The parallel components make the attraction force dominate the overall motion trend, improving the efficiency of the drone in reaching the target point.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle (UAV) fleet cooperation, and particularly relates to a UAV formation obstacle avoidance control algorithm based on an improved artificial potential field method. BACKGROUND

[0002] With the further development of UAV technology, the research on multi-UAV formation flight has also attracted more and more attention. UAVs cooperate with each other to form a formation group, which can fully exert the advantages that a single UAV does not have, and can better perform work in complex and multi-task scenarios. UAV fleet formation control and obstacle avoidance is a typical problem in the research of UAV fleet cooperation technology, which can be applied to the process of UAV fleet performing various task scenarios, effectively avoiding obstacles and avoiding self-collision, reducing unnecessary losses while efficiently completing tasks. UAV fleet cooperative formation control needs to ensure the interconnection between the fleet on the basis of good communication, and relies on the communication interaction between the fleet to realize resource sharing in different scenarios. Obstacles in complex combat environments can pose a threat to UAV flight, and in severe cases can even lead to the failure of UAV combat tasks, so having efficient obstacle avoidance capability is an important guarantee for the safe completion of UAV flight tasks, and has certain research significance for improving the accuracy, success rate and timeliness of fleet cooperation to complete various tasks.

[0003] The leader-following method is an early proposed method in multi-robot formation control, and its basic idea is to set a "leader" robot, and the remaining robots follow the position and speed of the leader according to certain rules, so as to achieve the effect of formation control. The leader is usually responsible for setting the target, and the other followers maintain the formation shape through local control strategy, and the control is relatively simple, usually only the relative position with the leader needs to be calculated. However, the formation stability is poor, and if the leader fails, the entire formation may collapse, which is not suitable for the failure of the leader or dynamic changes in tasks.

[0004] The artificial potential field method is a path planning algorithm based on the concept of force field. It guides the UAV or robot to avoid obstacles and move towards the target position by applying attractive and repulsive forces to the target and obstacles. The attractive force (gravitational force) of the target point guides the robot to move towards the target, and the repulsive force of the obstacle prevents the robot from colliding with the obstacle. These forces are combined through a mathematical model to determine the direction of motion of the robot. The vector superposition of repulsive and attractive forces can result in zero total force at certain positions, and the robot can reach equilibrium at non-target positions, i.e. the gradient is zero, which causes the robot to be unable to continue moving forward. This is the local optimum problem. SUMMARY

[0005] The purpose of the present application is to solve the problem of local optimum of UAV in the prior art artificial potential field method, and provide a UAV formation obstacle avoidance control algorithm based on an improved artificial potential field method.

[0006] The technical solution adopted to achieve the purpose of this invention is:

[0007] A method for obstacle avoidance control in UAV swarm formation based on an improved artificial potential field method includes the following steps:

[0008] Step 1: Based on the virtual structure method, the drone swarm forms the desired formation within a specified time and determines the direction of movement based on the current position and the target position;

[0009] Step 2: For the i-th drone, during its journey toward the target point, determine whether the distance between the i-th drone and the obstacle is greater than the safe distance. If the distance between the i-th drone and the obstacle is greater than the safe distance, continue to move toward the target point; if the distance between the i-th drone and the obstacle is less than the safe distance, introduce an improved artificial potential field method for obstacle avoidance until the target point is reached.

[0010] The improved artificial potential field method for obstacle avoidance is as follows:

[0011] The i-th drone is subjected to an artificial potential force F as it moves toward the target point. i 'Including the attraction F of the target point to the i-th UAV' i att The resultant force F of the artificial potential repulsive force between the i-th unmanned aerial vehicles i rep The artificial potential field repulsive force F exerted by the obstacle on the i-th UAV i ob By improving the artificial potential field method for F i ob Make corrections to ensure that the artificial potential field repulsive force F exerted by the obstacle on the i-th UAV is... i ob The attraction F of the target point to the i-th UAV i att Maintain orthogonality, when F i att With F i ob The angle between At that time, only F is retained. i ob China and F i att Orthogonal components F i obrep Remove F i att Parallel components.

[0012] In the above technical solution, in step 2, the i-th UAV is attracted by the attraction F of the target point. i att The calculation formula is:

[0013]

[0014] F = k * |p i att is the attraction of the ith UAV to the target point, U i att is the gravitational potential field.

[0015] In the above technical solution, the gravitational potential field U i att is expressed as:

[0016]

[0017] is the attraction of the ith UAV to the target point. i att The calculation formula of F

[0018]

[0019] where k is an integral proportional gain coefficient, |p i -p gi is the Euclidean distance between the position p i of the ith UAV and the position p gi of the target point.

[0020] In the above technical solution, the calculation formula of the resultant force F i rep of the artificial repulsive potential field between the ith UAV and the jth UAV in step 2 is:

[0021]

[0022] where F i rep is the resultant force of the artificial repulsive potential field between the ith UAV and the jth UAV, is the artificial repulsive potential field between the ith UAV and the jth UAV, p ij =p i -p j is the displacement vector between the ith UAV and the jth UAV, and N is the number of UAVs.

[0023] In the above technical solution, the calculation formula of the artificial repulsive potential field F between the ith UAV and the jth UAV is:

[0024]

[0025] where is the repulsive potential field between the ith UAV and the jth UAV.

[0026] In the above technical solution, the repulsive potential field between the i-th UAV and the j-th UAV The function is represented as:

[0027]

[0028] In the formula, η is the repulsive force gain, and d ij Let be the relative safe distance between the i-th drone and the j-th drone;

[0029] Let the maximum range of the repulsive force be D. max Then the repulsive force between the i-th drone and the j-th drone Represented as:

[0030]

[0031] In the formula, D max This represents the maximum range within which the repulsive force can act.

[0032] In the above technical solution, in step 2, F i ob China and F i att Orthogonal components F i obrep The calculation formula is as follows:

[0033]

[0034] In the formula, F i ob The artificial potential field repulsive force exerted by the obstacle on the i-th UAV is... For F i att With F i ob The angle between them For use in improving F i ob coefficient, γ is the identity matrix. i As a regulating factor, F i att Let the attraction of the target point to the i-th drone be denoted as . Let be the matrix transpose of the attraction of the target point to the i-th UAV.

[0035] In the above technical solution, the artificial potential field repulsion force F exerted by the obstacle on the i-th UAV is... i ob The calculation formula is as follows:

[0036]

[0037] In the formula, Ui ob repulsive potential field between the obstacle and the ith unmanned aerial vehicle.

[0038] In the technical solution, the repulsive potential field U i ob between the obstacle and the ith unmanned aerial vehicle is calculated by the following formula:

[0039]

[0040] The calculation formula of the artificial potential repulsive force F i ob of the obstacle on the ith unmanned aerial vehicle is:

[0041]

[0042] In the formula, η is a repulsive force gain, d i is the distance between the ith unmanned aerial vehicle and the obstacle, p0=[x0, y0, z0] is the coordinate of the obstacle, and p i is the coordinate position of the ith unmanned aerial vehicle.

[0043] In the technical solution, the calculation formula of the artificial potential attractive force F i ' on the ith unmanned aerial vehicle is:

[0044] F i ' = F i att + F i rep + F i obrep

[0045] In the formula, F i ' is the artificial potential attractive force on the ith unmanned aerial vehicle, F i att is the attractive force of the target point on the ith unmanned aerial vehicle, F i rep is the resultant force of the artificial potential repulsive force between the unmanned aerial vehicles, and F i ob is the component of F i att orthogonal to F i obrep .

[0046] Compared with the prior art, the beneficial effects of the present application are:

[0047] 1. This invention employs a virtual structure method for formation control. By treating all drones as a whole through a virtual structure, the relative positions of all drones remain stable. All drones are controlled according to a predetermined virtual structure (rigid body or geometry). Each drone has an independent control strategy and does not rely on a single leader, which makes the entire control process more stable. All drones participate in formation control, reducing the risk of single point of failure. The entire formation is more adaptable to dynamic environments and fault recovery, and has stronger adaptability.

[0048] 2. This invention employs an improved artificial potential field method in F i att With F i ob The angle between The repulsive and attractive forces exerted by the obstacle on the i-th drone are orthogonal, maintaining the relationship with F. i att Orthogonal components, remove those with F i att Parallel component. This improvement reduces the suppression of attractive forces by repulsive forces, thereby reducing the occurrence of local minima and allowing attractive forces to dominate the overall motion trend, improving the efficiency of the UAV in reaching the target point. Attached Figure Description

[0049] Figure 1 The diagram shown is a flowchart of the obstacle avoidance process for a drone swarm using the control method of the present invention.

[0050] Figure 2 The diagram shown is a schematic of the virtual structure method in the control method of the present invention.

[0051] Figure 3 The diagram shown is a schematic representation of the formation under the relevant coordinate system and virtual structure in the control method of this invention.

[0052] Figure 4 The diagram shown illustrates obstacle avoidance in the improved artificial potential field method of the control method of this invention. Detailed Implementation

[0053] The present invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0054] Reference Figure 1 A method for obstacle avoidance control in UAV swarms based on an improved artificial potential field method includes the following steps:

[0055] Step 1: Based on the virtual structure method, the drone swarm forms the desired formation within a specified time and determines the direction of movement based on the current position and the target position.

[0056] Reference Figure 2Virtual structure method treats the entire UAV swarm as a virtual rigid structure, and the position of each UAV is regarded as a fixed point on the rigid structure. When the formation moves, the UAVs track the virtual structure points to achieve the purpose of cooperative control. This method makes the entire UAV swarm formation form a relatively stable geometric structure. The main focus of the virtual structure method is: 1) to clearly define the geometric formation of the formation; 2) the formation formation coordinates remain unchanged, and the path is planned according to the task.

[0057] Virtual structure establishment:

[0058] The core of the virtual structure method is to regard the entire UAV formation as a rigid whole (virtual structure), and the movement of the UAV is determined by the trajectory of the virtual structure and the relative position of the UAV in the virtual structure. The actual position of each UAV is the superposition of the virtual structure trajectory and its offset in the formation. The offset is the relative position of each UAV in the virtual structure, and its role is to maintain the distance between the UAVs and the shape of the formation. By adding different offsets to the virtual trajectory, it is ensured that the relative position of the UAVs in the three-dimensional space meets the formation requirements. (x1, y1, z1) is the virtual center point coordinates, then:

[0059] x = x1 + offsetX

[0060] y = y1 + offsetY

[0061] z = z1 + offsetZ

[0062] Referring to Figure 3 The virtual structure method requires that the UAVs maintain a fixed relative position to ensure the stability and consistency of the formation. Assuming that the calculation of the offset satisfies the predetermined geometric relationship (such as rectangle, diamond, etc.), the entire formation can maintain rigidity, and the distance between the UAVs is ensured to be constant through the offset (offsetX, offsetY, offsetZ). With the change of time t, the trajectory of the virtual structure center point changes dynamically, and the actual trajectory of the UAV formation also adjusts accordingly, but the relative position in the formation remains unchanged. Each UAV executes independent motion under its own number, while achieving the consistency of the formation through the offset and trajectory formula.

[0063] Step 2, for the ith UAV, during the process of advancing to the target point, it is judged whether the distance between the ith UAV and the obstacle is greater than the safety distance. If the distance between the ith UAV and the obstacle is greater than the safety distance, the ith UAV continues to advance to the target point; if the distance between the ith UAV and the obstacle is less than the safety distance, the improved artificial potential field method is introduced to avoid obstacles until the target point is reached.

[0064] The improved artificial potential field method for obstacle avoidance is as follows:

[0065] The i-th drone is subjected to an artificial potential force F as it moves toward the target point. i 'Including the attraction F of the target point to the i-th UAV' i att The resultant force F of the artificial potential repulsive force between the i-th unmanned aerial vehicles i rep The artificial potential field repulsive force F exerted by the obstacle on the i-th UAV i ob By improving the artificial potential field method for F i ob Make corrections to ensure that the artificial potential field repulsive force F exerted by the obstacle on the i-th UAV is... i ob The attraction F of the target point to the i-th UAV i att Maintain orthogonality, when F i att With F i ob The angle between At that time, only F is retained. i ob China and F i att Orthogonal components F i obrep Remove F i att Parallel components.

[0066] The gravitational potential field is primarily related to the distance between the drone and the target point. When the drone is far from the target point, the gravitational potential field is larger; conversely, when the drone is closer to the target point, the gravitational potential field is smaller. Therefore, the gravitational potential field U of the target point on the i-th drone... i att The function is represented as:

[0067]

[0068] In the formula, k is the integer proportional gain coefficient, |p i -p gi |For the robot's position p i and target point position p gi Euclidean distance between ||p i -p gi The direction of the gravitational potential field is from the position of the i-th UAV to the position of the target point. The corresponding negative gradient of the gravitational potential field is the attraction F of the target point on the i-th UAV. i att It can be represented as:

[0069]

[0070] In the formula, Fi att U is the attractive force of the target point for the ith UAV, U i att U is the attractive force of the target point for the ith UAV, U i -p gi | is the Euclidean distance between the position p i of the ith UAV and the position p gi of the target point.

[0071] The traditional artificial potential field method is used for inter-UAV obstacle avoidance, and then the resultant force F i rep .

[0072] The artificial potential field method realizes conflict avoidance among the formation individuals by using the repulsive potential between the UAVs, and realizes avoidance of external obstacles by the repulsive potential of the UAVs to the obstacles. In this method, the force generated by the artificial potential field method is converted into a desired position, and the desired position calculated from the position of the UAVs in the formation is vector superimposed, thereby forming a new desired position, so that the UAVs in the formation are affected by the attractive potential field. In space, the equilibrium point of the attractive potential field and the repulsive potential field is the key condition for the UAV formation to reach a stable state. In the dynamic path planning process, the overall artificial potential field of the UAV formation is superimposed by the artificial potential fields generated by all the UAVs in the formation, wherein the artificial potential field U ij function is represented as:

[0073] U ij = U ij (|p ij |)

[0074] In the formula, U ij is the artificial potential field generated by the jth UAV at the position of the ith UAV; |p ij | is the displacement vector between the position p i of the ith UAV and the position p j of the jth UAV, defined as p ij = p i -p j . U ij satisfies the following conditions: when |p ij |→D min+ , U ij →+∞, U ij (|p ij |) has a unique minimum value J min (D) in the interval (D ij , +∞). The total potential field value U i of the ith UAV can be represented as the superposition result of the artificial potential fields of multiple points to the ith UAV, that is:

[0075]

[0076] In the formula, U ij (p ij |) represents the artificial potential field of the i-th drone at a certain point in the environment, and N represents the number of drones.

[0077] In UAV swarm formation control based on the virtual structure method, the desired position calculated from the target point's location exerts an attractive force on the UAVs. Therefore, the artificial potential field function between the UAVs no longer needs to consider the attractive force, but only the repulsive force. This simplifies the method's complexity and improves computational performance. (Repulsive potential field) Designed as an inverse proportional function, that is:

[0078]

[0079] In the formula, Let η be the repulsive potential field between the i-th and j-th drones, and d be the repulsive gain. ij Let |p be the relative safe distance between the i-th drone and the j-th drone. ij | is the position p of the i-th drone i The position p of the j-th drone j The displacement vector between them is defined as p ij =p i -p j .

[0080] The repulsive force between the i-th drone and the j-th drone for:

[0081]

[0082] It can be seen that if the safe distance d between the i-th drone and the j-th drone... ij The larger the potential field, the greater the repulsive force and the stronger the repulsive effect. In summary, considering that the addition of the artificial potential field method will change the desired position of the UAVs, thus reducing the control accuracy of the formation, the range of the repulsive force is limited to minimize its significant impact on accuracy. When the UAV formation enters a steady state, and the distance between each pair of UAVs participating in the formation is large, the formation control can ensure the control accuracy of the formation as much as possible. Let the maximum range of the repulsive force be D. max Then the repulsive force between the i-th drone and the j-th drone Represented as:

[0083]

[0084] Therefore, the resultant force F of the artificial potential field repulsion between drones experienced by the i-th drone is...i rep is:

[0085]

[0086] The effect of the artificial potential field method depends on the design of the potential field. A reasonable potential field can avoid local minimum point problems and improve the efficiency of path planning. By designing a suitable potential field function, the configuration of the vector field can be controlled, thereby optimizing path planning and obstacle avoidance performance.

[0087] Unlike the anti-collision between the UAV and the unmanned aerial vehicle, the obstacle is fixed and immovable. During the process of the UAV avoiding the obstacle, only the UAV can be controlled to change the flight path to avoid the obstacle, and the obstacle cannot be controlled. Therefore, the artificial potential field between the UAV and the obstacle is only generated by the obstacle. Let the coordinates of an obstacle in the airspace be p0=[x0, y0, z0] T The artificial potential field U i ob is expressed as:

[0088]

[0089] In the formula, d i is the distance between the ith UAV and the obstacle, and the repulsive force F i ob experienced by the ith UAV is:

[0090]

[0091] In the formula, U i ob is the repulsive potential field between the obstacle and the ith UAV, η is the repulsive force gain, d i is the distance between the ith UAV and the obstacle, is the coordinates of the obstacle, and p i is the coordinates of the ith UAV.

[0092] The embodiment improves the traditional artificial potential field method (APF). The core improvement is to correct the repulsive force F i ob so that it maintains an orthogonal relationship with the attractive force F i att . In the case where the repulsive force F i ob has an inhibitory effect on the attractive force F i att , only the component F i ob orthogonal to F i att is retained.i obrep That is, when When, retain its orthogonal component F i obrep And will be with F i att The direct removal of parallel components effectively improves the computational efficiency of the algorithm. It also reduces interference between attractive and repulsive forces, lowering the probability of local minima. (See reference...) Figure 4 Define an orthogonal projection matrix from the repulsive force F i ob Remove from attraction F i att Parallel components, only retain orthogonal components F i obrep To ensure that the interference of repulsive forces on attractive forces is minimized, the efficiency of path planning is improved. i ob China and F i att Orthogonal components F i obrep The calculation formula is as follows:

[0093]

[0094] In the formula, For F i att With F i ob The angle between them For use in improving F i ob coefficient, γ is the identity matrix. i As a regulating factor, F i att Let the attraction of the target point to the i-th drone be denoted as . Let be the matrix transpose of the attraction of the target point to the i-th UAV.

[0095] Compared with the traditional artificial potential field method, the correction method proposed in this embodiment removes (I n -P ma,i )F i ob It is F i ob The component, and F i att The directions are opposite. Clearly, this improved strategy makes F... i att Taking up more space makes the robot more likely to reach the target point.

[0096] In summary, the artificial potential field force suffered by the ith UAV is:

[0097] F i i att F i rep F i obrep

[0098] F i F i att F i rep F i obrep F i ob F i att F i obrep .

[0099] The above merely describes the preferred embodiments of the present application, and it should be noted that for those skilled in the art, several improvements and refinements can be made without departing from the principles of the present application, and these improvements and refinements should also be considered within the protection scope of the present application.​

Claims

1. A method for controlling formation and obstacle avoidance of a UAV swarm based on an improved artificial potential field method, characterized in that, The method comprises the following steps: Step 1, the unmanned aerial vehicle group forms a desired formation at a specified time based on a virtual structure method, and the forward direction is determined according to the current position and the target position; Step 2, for the ith unmanned aerial vehicle, whether the distance between the ith unmanned aerial vehicle and the obstacle is greater than a safety distance is judged during the process of advancing to the target point, if the distance between the ith unmanned aerial vehicle and the obstacle is greater than the safety distance, the unmanned aerial vehicle continues to advance to the target point, if the distance between the ith unmanned aerial vehicle and the obstacle is less than the safety distance, an improved artificial potential field method is introduced to avoid the obstacle until the target point is reached; The improved artificial potential field method for obstacle avoidance is specifically as follows: The resultant force of artificial potential repulsion between the ith UAV and the obstacles i The resultant force of artificial potential attraction between the ith UAV and the target point The resultant force of artificial potential repulsion between the ith UAV and the obstacles The resultant force of artificial potential repulsion between the ith UAV and the obstacles The resultant force of artificial potential repulsion between the ith UAV and the obstacles The resultant force of artificial potential repulsion between the ith UAV and the obstacles The resultant force of artificial potential repulsion between the ith UAV and the obstacles The resultant force of artificial potential repulsion between the ith UAV and the obstacles The resultant force of artificial potential repulsion between the ith UAV and the obstacles The resultant force of artificial potential repulsion between the ith UAV and the obstacles The resultant force of artificial potential repulsion between the ith UAV and the obstacles The resultant force of artificial potential repulsion between the ith UAV and the obstacles The resultant force of artificial potential repulsion between the ith UAV and the obstacles The resultant force of artificial potential repulsion between the ith UAV and the obstacles ​ 2. The unmanned aerial vehicle group formation obstacle avoidance control method based on the improved artificial potential field method according to claim 1, wherein The attraction of the i-th drone in step 2 to the target point The formula for calculating the attraction is: In the formula, is the attraction of the i-th UAV to the target point, is the gravitational potential field.

3. The UAV formation control method based on the improved artificial potential field method according to claim 2, wherein, gravitational potential field The function is represented as: The attraction of the ith drone to the target point The formula for calculating the attraction is: where k is an integral proportional gain coefficient, |p i -p gi is the Euclidean distance between the position p i of the i-th UAV and the position p gi of the target point.

4. The unmanned aerial vehicle group formation obstacle avoidance control method based on the improved artificial potential field method according to claim 1, wherein The resultant force of the artificial potential field repulsion between the ith UAV and the UAVs in step 2 The calculation formula is: In the formula, is the total force of artificial potential repulsion between the ith unmanned aerial vehicle and the jth unmanned aerial vehicle, is the total force of artificial potential repulsion between the ith unmanned aerial vehicle and the jth unmanned aerial vehicle, ij = p i -p j is the displacement vector between the ith unmanned aerial vehicle and the jth unmanned aerial vehicle, and N is the number of unmanned aerial vehicles.

5. The unmanned aerial vehicle group formation obstacle avoidance control method based on the improved artificial potential field method according to claim 1, wherein An artificial potential repulsive force between the ith UAV and the jth UAV The calculation formula is: In the formula, is the repulsive potential field between the ith UAV and the jth UAV.

6. The unmanned aerial vehicle group formation obstacle avoidance control method based on the improved artificial potential field method according to claim 5, wherein repulsive potential field between the ith drone and the jth drone The function is represented as: wherein η is the repulsive force gain, d ij is the relative safety distance between the ith unmanned aerial vehicle and the jth unmanned aerial vehicle; The maximum range of the repulsive force is D max repulsive force between the ith unmanned aerial vehicle and the jth unmanned aerial vehicle is is expressed as: In the formula, D max is the maximum range of repulsive force 7. The unmanned aerial vehicle group formation obstacle avoidance control method based on an improved artificial potential field method according to claim 1, characterized in that In other words, In step 2 In step 2 Orthogonal component The calculation formula is as follows: In the formula, The artificial potential field repulsive force exerted by the obstacle on the i-th UAV is... for and The angle between them For improvement coefficient, Let γi be the identity matrix and γi be the adjustment factor. Let the attraction of the target point to the i-th drone be denoted as . Let be the matrix transpose of the attraction of the target point to the i-th UAV. 8.The UAV formation control method based on the improved artificial potential field method according to claim 7, wherein, Obstacle artificial potential repulsion force for the ith unmanned aerial vehicle The calculation formula is as follows: In the formula, is the repulsive potential field between the obstacle and the ith UAV.

9. The UAV swarm formation obstacle avoidance control method based on the improved artificial potential field method as described in claim 7, characterized in that, repulsive potential field between the obstacle and the ith drone The calculation formula is: The calculation formula of the artificial potential field repulsion of the ith UAV to the obstacle is ​ In the formula, η is a repulsive force gain, di is the distance between the ith unmanned aerial vehicle and the obstacle, p0 = [x0, y0, z0] is the coordinates of the obstacle, and pi is the coordinate position of the ith unmanned aerial vehicle.

10. The unmanned aerial vehicle group formation obstacle avoidance control method based on the improved artificial potential field method according to claim 1, wherein The calculation formula of the artificial potential field resultant force F'i acting on the ith unmanned aerial vehicle is: In the formula, F i is the artificial potential field force on the ith UAV, is the attraction force of the target point on the ith UAV, is the resultant force of the artificial potential field repulsion between the ith UAV and the jth UAV, is the component of the force in the direction of is the component of the force orthogonal to

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