Unmanned aerial vehicle obstacle avoidance method and device, computer equipment and storage medium

Abstract

The invention relates to an unmanned aerial vehicle obstacle avoidance method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining the formation speed of an unmanned aerial vehicle according to the flight course angle of the unmanned aerial vehicle; acquiring an obstacle avoidance strategy according to the distance between the unmanned aerial vehicle and the obstacle and the flight course angle of the unmanned aerial vehicle; obtaining the obstacle avoidance speed of the unmanned aerial vehicle; obtaining the original obstacle avoidance speed of the unmanned aerial vehicle group according to the formation speed of the unmanned aerial vehicles, the obstacle avoidance speed of the unmanned aerial vehicles and the willingness adjustment coefficient; optimizing the original obstacle avoidance speed of the unmanned aerial vehicle group according to an attraction speed constraint and a rejection speed constraint to obtain an optimized obstacle avoidance speed of the unmanned aerial vehicle group; wherein when the unmanned aerial vehicles avoid obstacles, the obstacle avoidance strategy and the unmanned aerial vehicle group are applied to optimize the obstacle avoidance speed. The overall safety of the unmanned aerial vehicle group can be improved.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicles (UAVs), and more particularly to a UAV obstacle avoidance method, apparatus, computer equipment, and storage medium. Background Technology

[0002] With the development of information technology and the internet, drones are being used more and more widely. Obstacle avoidance is one of the most fundamental and important technologies for drones. Drones possess high decision-making capabilities and are therefore also referred to as multi-agent drones.

[0003] One of the research focuses in the field of UAV obstacle avoidance is the artificial potential field method, which is renowned for its local path planning capabilities and simplicity and efficiency in real-time obstacle avoidance. This method performs well in small to medium-sized multi-agent systems using asynchronous spatial allocation protocols, but its trajectory planning algorithm has high computational resource requirements, which may lead to decision delays and compromise system security.

[0004] It is evident that existing drone obstacle avoidance methods are insufficient to guarantee system safety and meet the needs of drone obstacle avoidance. Summary of the Invention

[0005] In order to solve the above-mentioned technical problems, or at least partially solve the above-mentioned technical problems, the present invention provides an obstacle avoidance method, device, computer equipment and storage medium for unmanned aerial vehicles.

[0006] In a first aspect, the present invention provides an obstacle avoidance method for unmanned aerial vehicles (UAVs), the method being applied to a UAV swarm, the method comprising: The drone formation speed is obtained based on the drone's flight heading angle; Obstacle avoidance strategy is obtained based on the distance between the drone and the obstacle, and the drone's flight heading angle; Obtain the drone's obstacle avoidance speed; The original obstacle avoidance speed of the drone swarm is obtained based on the drone formation speed, the drone obstacle avoidance speed, and the intention adjustment coefficient. Based on the attraction velocity constraint and the repulsion velocity constraint, the original obstacle avoidance speed of the UAV swarm is optimized to obtain the optimized obstacle avoidance speed of the UAV swarm. When the drone avoids obstacles, the obstacle avoidance strategy and the drone swarm are used to optimize the obstacle avoidance speed.

[0007] Optionally, the drone formation speed is obtained based on the drone's flight heading angle in the following manner: For the first The flight heading angle of the drone. The neighbor matrix describes the neighbor relationships of drones. Sampling time, The time interval between two time steps. For the first A drone The heading angle at any moment, for The expected direction of real-time informed drones It is random noise. Used to indicate The first moment Was the drone operated by an individual with knowledge of its operation? Indicates the first The drones were informed drones. For drone formation speed; and They are mutually perpendicular unit vectors. This represents the constant absolute speed of the drone.

[0008] Optionally, obtaining the obstacle avoidance strategy based on the distance between the drone and the obstacle, and the drone's flight heading angle, includes: Obtain the obstacle area; Based on the obstacle area and the preset safety distance, the danger angle is obtained; Based on the danger angle and the flight heading angle of the UAV, a first obstacle avoidance strategy is obtained; The preset safety distance is: in, To establish a safe distance, The radius of the drone itself, For the safety speed coefficient, The constant absolute speed of the drone, This is the time interval between two time steps.

[0009] Optionally, the first obstacle avoidance strategy is: If the angle bisector of the danger angle is located counterclockwise from the UAV's heading angle, then the UAV turns clockwise. If the angle bisector of the danger angle is located clockwise from the flight heading angle of the UAV, then the UAV will turn counterclockwise. If the flight heading angle of the drone is not within the dangerous angle range, the drone will not turn; The obstacle avoidance strategy further includes a second obstacle avoidance strategy, which is: If the distance between the drone swarm and the obstacle area is greater than or equal to a preset obstacle avoidance distance, the drone swarm will maintain formation. If the distance between the drone swarm and the obstacle area is less than the preset obstacle avoidance distance, then the drone closest to the obstacle area has the highest obstacle avoidance priority.

[0010] Optionally, obtaining the drone obstacle avoidance speed includes: Obtain the obstacle avoidance mechanism coefficient based on the preset safety distance; Obtain the obstacle avoidance angular acceleration based on the obstacle avoidance mechanism coefficients; Obtain the obstacle avoidance angular velocity based on the obstacle avoidance angular acceleration; Obtain the obstacle avoidance heading angle based on the obstacle avoidance heading angular velocity; The obstacle avoidance speed of the UAV is obtained based on the obstacle avoidance heading angle; The obstacle avoidance mechanism coefficient is obtained based on a preset safety distance in the following manner: The obstacle avoidance heading angular acceleration is obtained based on the obstacle avoidance mechanism coefficients in the following manner: The obstacle avoidance angular velocity is obtained based on the obstacle avoidance angular acceleration, in the following manner: The obstacle avoidance heading angle is obtained based on the obstacle avoidance heading angular velocity in the following manner: The obstacle avoidance speed of the UAV is obtained based on the obstacle avoidance heading angle in the following manner: in, For the first The obstacle avoidance mechanism coefficient of a drone. To establish a safe distance, for Time of the first The actual distance between the drone and the nearest obstacle. The radius of the obstacle itself. For the first The obstacle avoidance heading angular acceleration of a drone For the maximum obstacle avoidance heading angular acceleration, For the first The obstacle avoidance heading angular velocity of the drone. For the maximum obstacle avoidance heading angular velocity, Sampling time, The time interval between two time steps. For the first The obstacle avoidance heading angle of the drone. For the first The obstacle avoidance speed of a drone This represents the constant absolute speed of the drone.

[0011] Optionally, the initial obstacle avoidance speed of the drone swarm is obtained based on the drone formation speed, the drone obstacle avoidance speed, and the intention adjustment coefficient, in the following manner: in, For the first The initial obstacle avoidance speed of a drone swarm For the first The willingness adjustment coefficient for each drone For the first The obstacle avoidance speed of a drone For the first The speed of drone formations For the first The obstacle avoidance mechanism coefficient of a drone. For the first The first drone in the neighbor set The obstacle avoidance mechanism coefficient of each drone.

[0012] Optionally, the attraction velocity constraint is: The repulsion velocity constraint is: The optimization of the original obstacle avoidance speed of the UAV swarm based on attraction and repulsion speed constraints to obtain the optimized obstacle avoidance speed of the UAV swarm is carried out in the following manner: in, For the first Optimize obstacle avoidance speed for drone swarms For the first The initial obstacle avoidance speed of the drone swarm; This is the formation weighting coefficient, used to adjust the priority of "formation coordination" in the overall speed; The exclusion weighting coefficient is used to adjust the priority of "collision avoidance" in the overall speed. For the first The safe rejection speed of a drone For the attraction velocity vector, To attract weighting coefficients, For the first A drone at any time The neighbor repulsion velocity vector, For safe repulsion speed, For the first A drone at any time The actual flight velocity vector of t, The constant absolute speed of the drone, Indicates the distance between the drone and the nearest obstacle. To establish a safe distance, The positional relationship between the drones is represented by the first... The drone and the first The position difference vector of each drone For at any time Located in the The set of all neighboring drones within the repulsive force radius of a given drone. For at any time Located in the The set of all neighboring drones between the repulsive force radius and the attractive force radius of a given drone. For the radius of attraction, The radius represents the repulsive force.

[0013] Secondly, a drone obstacle avoidance device is provided, the device being applied to a drone swarm, the device comprising: The speed acquisition unit is used to acquire the formation speed of the drones based on their flight heading angle. The strategy acquisition unit is used to acquire an obstacle avoidance strategy based on the distance between the UAV and the obstacle and the flight heading angle of the UAV. The speed acquisition unit is also used to acquire the obstacle avoidance speed of the drone; The speed acquisition unit is also used to obtain the original obstacle avoidance speed of the drone swarm based on the drone formation speed, the drone obstacle avoidance speed, and the intention adjustment coefficient; An optimization unit is used to optimize the original obstacle avoidance speed of the UAV swarm based on the attraction speed constraint and the repulsion speed constraint, so as to obtain the optimized obstacle avoidance speed of the UAV swarm. When the drone avoids obstacles, the obstacle avoidance strategy and the drone swarm are used to optimize the obstacle avoidance speed.

[0014] Thirdly, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method as described in any of the preceding claims.

[0015] Fourthly, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method as described in any of the preceding claims.

[0016] This invention provides a method, apparatus, computer device, and storage medium for drone obstacle avoidance. The method includes: obtaining the drone formation speed based on the drone's flight heading angle; obtaining an obstacle avoidance strategy based on the distance between the drone and the obstacle, and the drone's flight heading angle; obtaining the drone obstacle avoidance speed; obtaining the drone swarm's original obstacle avoidance speed based on the drone formation speed, the drone obstacle avoidance speed, and a willingness adjustment coefficient; and optimizing the drone swarm's original obstacle avoidance speed based on attraction speed constraints and repulsion speed constraints to obtain an optimized obstacle avoidance speed for the drone swarm. In this method, obstacle avoidance based on the obstacle avoidance strategy and the optimized obstacle avoidance speed of the drone swarm improves the overall safety of the drone swarm. The attraction speed constraint allows the drone swarm to maintain its formation during obstacle avoidance, while the repulsion speed constraint further ensures the safety performance of the drone swarm. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 The diagram shown illustrates the application environment of the drone obstacle avoidance method according to an embodiment of the present invention. Figure 2 The diagram shown is a flowchart of the drone obstacle avoidance method according to an embodiment of the present invention. Figure 3 The diagram shown is a schematic representation of the obstacle area and danger angle according to an embodiment of the present invention; Figure 4 The diagram shown is a structural block diagram of the drone obstacle avoidance device according to an embodiment of the present invention. Figure 5 The diagram shown is an internal structural diagram of a computer device in an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Figure 1 The diagram shown illustrates the application environment of the drone obstacle avoidance method in this embodiment of the invention. (Refer to...) Figure 1 This drone obstacle avoidance method is applied to a drone obstacle avoidance system. The method includes a terminal 110 and / or a server 120. The terminal 110 and server 120 are connected via a network. The terminal 110 can be a desktop terminal or a mobile terminal; a mobile terminal can be at least one of a mobile phone, tablet, or laptop, and can be mounted on the drone. The server 120 can be a standalone server or a server cluster consisting of multiple servers. The server 120 can be mounted on the drone or can be set up independently.

[0022] The drone obstacle avoidance method of the present invention is applied to terminal 110 and / or server 120.

[0023] Figure 2 The diagram shows a flowchart of a drone obstacle avoidance method according to an embodiment of the present invention. The method is applied to a drone swarm and includes: Step 210: Obtain the drone formation speed based on the drone's flight heading angle; Step 220: Obtain an obstacle avoidance strategy based on the distance between the drone and the obstacle, and the drone's flight heading angle; Step 230: Obtain the drone's obstacle avoidance speed; Step 240: Obtain the original obstacle avoidance speed of the drone swarm based on the drone formation speed, the drone obstacle avoidance speed, and the intention adjustment coefficient; Step 250: Optimize the original obstacle avoidance speed of the drone swarm based on the attraction speed constraint and the repulsion speed constraint to obtain the optimized obstacle avoidance speed of the drone swarm. When the drone avoids obstacles, the obstacle avoidance strategy and the drone swarm are used to optimize the obstacle avoidance speed.

[0024] The method of this invention involves: obtaining the formation speed of the drones based on their flight heading angle; obtaining an obstacle avoidance strategy based on the distance between the drones and obstacles, and the flight heading angle of the drones; obtaining the obstacle avoidance speed of the drones; obtaining the original obstacle avoidance speed of the drone swarm based on the formation speed, the obstacle avoidance speed, and a willingness adjustment coefficient; and optimizing the original obstacle avoidance speed of the drone swarm based on attraction speed constraints and repulsion speed constraints to obtain an optimized obstacle avoidance speed for the drone swarm. In this method, obstacle avoidance based on the obstacle avoidance strategy and the optimized obstacle avoidance speed of the drone swarm improves the overall safety of the drone swarm. The attraction speed constraint allows the drone swarm to maintain its formation during obstacle avoidance, while the repulsion speed constraint further ensures the safety performance of the drone swarm. Furthermore, this invention employs a willingness control method when optimizing the obstacle avoidance speed of the drone swarm. This method not only ensures the overall safety of the drone system but also reduces the overall energy consumption of the drone swarm. This invention also provides a kinematic model for a drone, the drone motion model including: in, for The first moment The speed of the drone and They are mutually perpendicular unit vectors. The constant absolute speed of the drone, for The first moment The heading angle of the drone, for The first moment Location updates for individual drones. Sampling time, The time interval between two time steps. for The first moment A collection of drones' neighbors. This refers to the communication radius.

[0025] The significance of the above-mentioned drone motion model is that it allows us to calculate the speed of the drone based on its heading angle.

[0026] In this embodiment of the invention, step 210, obtaining the UAV formation speed based on the UAV's flight heading angle, is performed in the following manner: For the first The flight heading angle of the drone. The neighbor matrix describes the neighbor relationships of drones. Sampling time, The time interval between two time steps. For the first A drone The heading angle at any moment, for The expected direction of real-time informed drones It is random noise. Used to indicate The first moment Was the drone operated by an individual with knowledge of its operation? Indicates the first The drones were informed drones. For drone formation speed; and They are mutually perpendicular unit vectors. This represents the constant absolute speed of the drone.

[0027] When a drone swarm encounters an obstacle, it needs to avoid it. The obstacle avoidance methods include obstacle avoidance strategies and flight parameters when executing the obstacle avoidance strategy. Flight parameters may include heading angle, speed, etc., which will be explained below.

[0028] In this embodiment of the invention, step 220, obtaining an obstacle avoidance strategy based on the distance between the UAV and the obstacle and the flight heading angle of the UAV, includes: Obtain the obstacle area; Based on the obstacle area and the preset safety distance, the danger angle is obtained; Based on the danger angle and the flight heading angle of the UAV, a first obstacle avoidance strategy is obtained; The preset safety distance is: in, To establish a safe distance, The radius of the drone itself, For the safety speed coefficient, The constant absolute speed of the drone, This is the time interval between two time steps.

[0029] In this embodiment of the invention, the first obstacle avoidance strategy is: If the angle bisector of the danger angle is located counterclockwise from the UAV's heading angle, then the UAV turns clockwise. If the angle bisector of the danger angle is located clockwise from the flight heading angle of the UAV, then the UAV will turn counterclockwise. If the flight heading angle of the drone is not within the dangerous angle range, the drone will not turn; The obstacle avoidance strategy further includes a second obstacle avoidance strategy, which is: If the distance between the drone swarm and the obstacle area is greater than or equal to a preset obstacle avoidance distance, the drone swarm will maintain formation. If the distance between the drone swarm and the obstacle area is less than the preset obstacle avoidance distance, then the drone closest to the obstacle area has the highest obstacle avoidance priority.

[0030] In this embodiment of the invention, the first obstacle avoidance strategy is a turning strategy, and the second obstacle avoidance strategy is a formation strategy. When the drone swarm encounters an obstacle, it performs obstacle avoidance according to the above-mentioned obstacle avoidance strategies.

[0031] Figure 3 The diagram shown is a schematic representation of the obstacle area and danger angle according to an embodiment of the present invention. Figure 3 As shown, the gray area represents the obstacle area. To establish a preset safe distance, as shown in the light green area in the diagram, the area between the red lines... From a dangerous angle, the blue object is indicated by the black straight arrow pointing to the drone. This refers to the heading angle of the drone.

[0032] Figure 3 (a) and Figure 3 (d) The obstacle area is circular. The bisector of the danger angle between the UAV and the obstacle area is located counterclockwise from the UAV's flight heading angle. The UAV rotates clockwise, as shown below. Figure 3 (a) The arrowhead represents an arc shape.

[0033] Figure 3 (a) and Figure 3 (d) The difference lies in Figure 3 The danger angle in (d) is 180 degrees.

[0034] Figure 3 (b) and Figure 3 (e) The obstacle area is pentagonal in shape. The bisector of the danger angle between the UAV and the obstacle area is located clockwise from the UAV's flight heading angle. The UAV rotates counterclockwise, as shown below. Figure 3 (a) The arrowhead represents an arc shape.

[0035] Figure 3 (b) and Figure 3 (e) The difference lies in Figure 3 The danger angle in (e) is 180 degrees.

[0036] Figure 3 (c) and Figure 3 (f) The obstacle area is approximately quadrilateral, the flight heading angle is not within the dangerous angle range, and the UAV does not turn; Figure 3 (c) and Figure 3 (f) The difference lies in Figure 3 The danger angle in (f) is 180 degrees.

[0037] In this embodiment of the invention, obtaining the obstacle avoidance speed of the drone includes: Obtain the obstacle avoidance mechanism coefficient based on the preset safety distance; Obtain the obstacle avoidance angular acceleration based on the obstacle avoidance mechanism coefficients; Obtain the obstacle avoidance angular velocity based on the obstacle avoidance angular acceleration; Obtain the obstacle avoidance heading angle based on the obstacle avoidance heading angular velocity; The obstacle avoidance speed of the UAV is obtained based on the obstacle avoidance heading angle; The obstacle avoidance mechanism coefficient is obtained based on a preset safety distance in the following manner: The obstacle avoidance heading angular acceleration is obtained based on the obstacle avoidance mechanism coefficients in the following manner: The obstacle avoidance angular velocity is obtained based on the obstacle avoidance angular acceleration, in the following manner: The obstacle avoidance heading angle is obtained based on the obstacle avoidance heading angular velocity in the following manner: The obstacle avoidance speed of the UAV is obtained based on the obstacle avoidance heading angle in the following manner: in, For the first The obstacle avoidance mechanism coefficient of a drone. To establish a safe distance, for Time of the first The actual distance between the drone and the nearest obstacle. The radius of the obstacle itself. For the first The obstacle avoidance heading angular acceleration of a drone For the maximum obstacle avoidance heading angular acceleration, For the first The obstacle avoidance heading angular velocity of the drone. For the maximum obstacle avoidance heading angular velocity, Sampling time, The time interval between two time steps. For the first The obstacle avoidance heading angle of the drone. For the first The obstacle avoidance speed of a drone This represents the constant absolute speed of the drone.

[0038] The significance of the obstacle avoidance mechanism coefficient is as follows: If the drone swarm is far from the obstacle, meaning the mechanism coefficient of individual drones is relatively small, then individual drones prioritize maintaining formation. As the swarm approaches the obstacle, the mechanism coefficients of individual drones gradually increase, and the drones closest to the obstacle begin to prioritize obstacle avoidance. Initially, only a few drones prioritize obstacle avoidance, while those farther from the obstacle mainly maintain formation. As the number of drones prioritizing obstacle avoidance increases, even drones farther from the obstacle will begin obstacle avoidance earlier through interactions between individuals.

[0039] In this embodiment of the invention, step 240, obtaining the original obstacle avoidance speed of the drone swarm based on the drone formation speed, the drone obstacle avoidance speed, and the intention adjustment coefficient, is performed in the following manner: in, For the first The initial obstacle avoidance speed of a drone swarm For the first The willingness adjustment coefficient for each drone For the first The obstacle avoidance speed of a drone For the first The speed of drone formations For the first The obstacle avoidance mechanism coefficient of a drone. For the first The first drone in the neighbor set The obstacle avoidance mechanism coefficient of each drone.

[0040] In this embodiment of the invention, in step 250, the attraction velocity constraint is: in, For the first The initial obstacle avoidance speed of a drone swarm For the first The willingness adjustment coefficient for each drone For the first The obstacle avoidance speed of a drone For the first The speed of drone formations For the first The obstacle avoidance mechanism coefficient of a drone. For the first The first drone in the neighbor set The obstacle avoidance mechanism coefficient of each drone.

[0041] In this embodiment of the invention, the attraction velocity constraint is: The repulsion velocity constraint is: The optimization of the original obstacle avoidance speed of the UAV swarm based on attraction and repulsion speed constraints to obtain the optimized obstacle avoidance speed of the UAV swarm is carried out in the following manner: in, For the first Optimize obstacle avoidance speed for drone swarms For the first The initial obstacle avoidance speed of the drone swarm; This is the formation weighting coefficient, used to adjust the priority of "formation coordination" in the overall speed; The exclusion weighting coefficient is used to adjust the priority of "collision avoidance" in the overall speed. For the first The safe rejection speed of a drone For the attraction velocity vector, To attract weighting coefficients, For the first A drone at any time The neighbor repulsion velocity vector, For safe repulsion speed, For the first A drone at any time The actual flight velocity vector of t, The constant absolute speed of the drone, Indicates the distance between the drone and the nearest obstacle. To establish a safe distance, The positional relationship between the drones is represented by the first... The drone and the first The position difference vector of each drone For at any time Located in the The set of all neighboring drones within the repulsive force radius of a given drone. For at any time Located in the The set of all neighboring drones between the repulsive force radius and the attractive force radius of a given drone. For the radius of attraction, The radius represents the repulsive force.

[0042] In this embodiment of the invention, As an attraction velocity vector, when the distance between adjacent drones is between the "repulsive force radius" and the "attraction force radius", the attraction velocity vector is the velocity component that generates the movement towards the neighbor, thus preventing the cluster from disintegrating due to the neighbor's obstacle avoidance action being too far away.

[0043] In this embodiment of the invention, an informed drone is also proposed. The informed drone is characterized by: knowing the coordinates of the target area and being able to design a flight path that coordinates with the collective will of the drone swarm's expected trajectory; the movement trajectory of the informed drone is clear and influenced by neighbor repulsion. In this embodiment of the invention, the server 120 can be mounted on the informed drone.

[0044] The speed of the informed drone is: When the distance between the informed drone and the obstacle is less than At that time, the speed of the informed drone was: To lead the speed of drones, For the speed of the informed drone, This represents the distance between the leader and the nearest obstacle. When the informed UAV detects an obstacle, it performs obstacle avoidance according to the obstacle avoidance method of the present invention. At this time, according to the kinematic model equation of the UAV, the velocity of the informed UAV is... Otherwise, the expected speed of the drone is the speed towards the target area. .

[0045] In this embodiment of the invention, the setting of informed drones can eliminate the need for uninformed drones to acquire additional information or perform excessive calculations, thereby reducing the overall information collection and calculation workload of the drone swarm and reducing the overall resource consumption of the drone swarm.

[0046] like Figure 4 As shown, the present invention also provides a drone obstacle avoidance device, which is applied to a drone swarm, and the device includes: The speed acquisition unit 410 is used to acquire the formation speed of the UAVs based on the UAVs' flight heading angle; The strategy acquisition unit 420 is used to acquire an obstacle avoidance strategy based on the distance between the UAV and the obstacle and the flight heading angle of the UAV. The speed acquisition unit 410 is also used to acquire the obstacle avoidance speed of the drone; The speed acquisition unit 410 is also used to obtain the original obstacle avoidance speed of the drone swarm based on the drone formation speed, the drone obstacle avoidance speed and the intention adjustment coefficient; The optimization unit 430 is used to optimize the original obstacle avoidance speed of the UAV swarm based on the attraction speed constraint and the repulsion speed constraint, so as to obtain the optimized obstacle avoidance speed of the UAV swarm. When the drone avoids obstacles, the obstacle avoidance strategy and the drone swarm are used to optimize the obstacle avoidance speed.

[0047] In this embodiment of the invention, the speed acquisition unit 410 is further configured to acquire the formation speed of the UAVs based on the UAVs' flight heading angle in the following manner: For the first The flight heading angle of the drone. The neighbor matrix describes the neighbor relationships of drones. Sampling time, The time interval between two time steps. For the first A drone The heading angle at any moment, for The expected direction of real-time informed drones It is random noise. Used to indicate The first moment Was the drone operated by an individual with knowledge of its operation? Indicates the first The drones were informed drones. For drone formation speed; and They are mutually perpendicular unit vectors. This represents the constant absolute speed of the drone.

[0048] In this embodiment of the invention, the strategy acquisition unit 420 is further configured to: Obtain the obstacle area; Based on the obstacle area and the preset safety distance, the danger angle is obtained; Based on the danger angle and the flight heading angle of the UAV, a first obstacle avoidance strategy is obtained; The preset safety distance is: in, To establish a safe distance, The radius of the drone itself, For the safety speed coefficient, The constant absolute speed of the drone, This is the time interval between two time steps.

[0049] In this embodiment of the invention, the first obstacle avoidance strategy is: If the angle bisector of the danger angle is located counterclockwise from the UAV's heading angle, then the UAV turns clockwise. If the angle bisector of the danger angle is located clockwise from the flight heading angle of the UAV, then the UAV will turn counterclockwise. If the flight heading angle of the drone is not within the dangerous angle range, the drone will not turn; The obstacle avoidance strategy further includes a second obstacle avoidance strategy, which is: If the distance between the drone swarm and the obstacle area is greater than or equal to a preset obstacle avoidance distance, the drone swarm will maintain formation. If the distance between the drone swarm and the obstacle area is less than the preset obstacle avoidance distance, then the drone closest to the obstacle area has the highest obstacle avoidance priority.

[0050] In this embodiment of the invention, the speed acquisition unit 410 is further configured to: Obtain the obstacle avoidance mechanism coefficient based on the preset safety distance; Obtain the obstacle avoidance angular acceleration based on the obstacle avoidance mechanism coefficients; Obtain the obstacle avoidance angular velocity based on the obstacle avoidance angular acceleration; Obtain the obstacle avoidance heading angle based on the obstacle avoidance heading angular velocity; The obstacle avoidance speed of the UAV is obtained based on the obstacle avoidance heading angle; The speed acquisition unit 410 is further configured to acquire the obstacle avoidance mechanism coefficient based on a preset safety distance in the following manner: The speed acquisition unit 410 is further configured to acquire the obstacle avoidance heading angular acceleration based on the obstacle avoidance mechanism coefficient in the following manner: The speed acquisition unit 410 is further configured to acquire the obstacle avoidance angular velocity based on the obstacle avoidance angular acceleration in the following manner: The speed acquisition unit 410 is further configured to acquire the obstacle avoidance heading angle based on the obstacle avoidance heading angular velocity in the following manner: The speed acquisition unit 410 is further configured to acquire the obstacle avoidance speed based on the obstacle avoidance heading angle in the following manner: in, For the first The obstacle avoidance mechanism coefficient of a drone. To establish a safe distance, for Time of the first The actual distance between the drone and the nearest obstacle. The radius of the obstacle itself. For the first The obstacle avoidance heading angular acceleration of a drone For the maximum obstacle avoidance heading angular acceleration, For the first The obstacle avoidance heading angular velocity of the drone. For the maximum obstacle avoidance heading angular velocity, Sampling time, The time interval between two time steps. For the first The obstacle avoidance heading angle of the drone. For the first The obstacle avoidance speed of a drone This represents the constant absolute speed of the drone.

[0051] In this embodiment of the invention, the speed acquisition unit 410 is further configured to obtain the original obstacle avoidance speed of the drone swarm based on the drone formation speed, the drone obstacle avoidance speed, and the intention adjustment coefficient in the following manner: in, For the first The initial obstacle avoidance speed of a drone swarm For the first The willingness adjustment coefficient for each drone For the first The obstacle avoidance speed of a drone For the first The speed of drone formations For the first The obstacle avoidance mechanism coefficient of a drone. For the first The first drone in the neighbor set The obstacle avoidance mechanism coefficient of each drone.

[0052] In this embodiment of the invention, the attraction velocity constraint is: The repulsion velocity constraint is: The optimization of the original obstacle avoidance speed of the UAV swarm based on attraction and repulsion speed constraints to obtain the optimized obstacle avoidance speed of the UAV swarm is carried out in the following manner: in, For the first Optimize obstacle avoidance speed for drone swarms For the first The initial obstacle avoidance speed of the drone swarm; This is the formation weighting coefficient, used to adjust the priority of "formation coordination" in the overall speed; The exclusion weighting coefficient is used to adjust the priority of "collision avoidance" in the overall speed. For the first The safe rejection speed of a drone For the attraction velocity vector, To attract weighting coefficients, For the first A drone at any time The neighbor repulsion velocity vector, For safe repulsion speed, For the first A drone at any time The actual flight velocity vector of t, The constant absolute speed of the drone, Indicates the distance between the drone and the nearest obstacle. To establish a safe distance, The positional relationship between the drones is represented by the first... The drone and the first The position difference vector of each drone For at any time Located in the The set of all neighboring drones within the repulsive force radius of a given drone. For at any time Located in the The set of all neighboring drones between the repulsive force radius and the attractive force radius of a given drone. For the radius of attraction, The radius represents the repulsive force.

[0053] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the following method: obtaining the formation speed of the UAVs based on their flight heading angle; obtaining an obstacle avoidance strategy based on the distance between the UAVs and obstacles, and the flight heading angle of the UAVs; obtaining the obstacle avoidance speed of the UAVs; obtaining the original obstacle avoidance speed of the UAV swarm based on the formation speed, the obstacle avoidance speed, and a willingness adjustment coefficient; optimizing the original obstacle avoidance speed of the UAV swarm based on attraction speed constraints and repulsion speed constraints to obtain an optimized obstacle avoidance speed for the UAV swarm; wherein, when the UAVs avoid obstacles, the obstacle avoidance strategy and the optimized obstacle avoidance speed of the UAV swarm are applied.

[0054] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the following method: obtaining the formation speed of the UAVs based on their flight heading angle; obtaining an obstacle avoidance strategy based on the distance between the UAVs and obstacles, and the flight heading angle of the UAVs; obtaining the obstacle avoidance speed of the UAVs; obtaining the original obstacle avoidance speed of the UAV swarm based on the formation speed, the obstacle avoidance speed, and the intention adjustment coefficient; optimizing the original obstacle avoidance speed of the UAV swarm based on attraction speed constraints and repulsion speed constraints to obtain the optimized obstacle avoidance speed of the UAV swarm; wherein, when the UAVs avoid obstacles, the obstacle avoidance strategy and the optimized obstacle avoidance speed of the UAV swarm are applied.

[0055] The aforementioned drone obstacle avoidance method achieves the beneficial effect of solving the technical problems mentioned in the background art.

[0056] Figure 2 This is a flowchart illustrating an obstacle avoidance method for a drone in one embodiment. It should be understood that, although... Figure 2 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 2 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0057] Figure 5 An internal structural diagram of a computer device in one embodiment is shown. Specifically, this computer device may be... Figure 1Server 120 in the middle. For example... Figure 5 As shown, the computer device includes a processor, memory, network interface, input device, and display screen connected via a system bus. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and may also store computer programs. When executed by the processor, these programs enable the processor to implement an obstacle avoidance method for the drone. The internal memory may also store computer programs, which, when executed by the processor, enable the processor to implement the drone obstacle avoidance method. The display screen can be an LCD screen or an e-ink screen. The input device can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the device's casing, or an external keyboard, touchpad, or mouse.

[0058] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device to which the present invention is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0059] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0060] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0061] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for obstacle avoidance by unmanned aerial vehicles (UAVs), characterized in that, The method is applied to a drone swarm, and the method includes: The drone formation speed is obtained based on the drone's flight heading angle; Obstacle avoidance strategy is obtained based on the distance between the drone and the obstacle, and the drone's flight heading angle; Obtain the drone's obstacle avoidance speed; The original obstacle avoidance speed of the drone swarm is obtained based on the drone formation speed, the drone obstacle avoidance speed, and the intention adjustment coefficient. Based on the attraction velocity constraint and the repulsion velocity constraint, the original obstacle avoidance speed of the UAV swarm is optimized to obtain the optimized obstacle avoidance speed of the UAV swarm. When the drone avoids obstacles, the obstacle avoidance strategy and the drone swarm are used to optimize the obstacle avoidance speed.

2. The method according to claim 1, characterized in that, The formation speed of the drones is obtained based on their flight heading angle, in the following manner: For the first The flight heading angle of the drone. The neighbor matrix describes the neighbor relationships of drones. Sampling time, The time interval between two time steps. For the first A drone The heading angle at any moment, for The expected direction of real-time informed drones It is random noise. Used to indicate The first moment Was the drone operated by an individual with knowledge of its operation? Indicates the first The drones were informed drones. For drone formation speed; and They are mutually perpendicular unit vectors. This represents the constant absolute speed of the drone.

3. The method according to claim 1, characterized in that, The step of obtaining an obstacle avoidance strategy based on the distance between the drone and the obstacle, and the drone's flight heading angle, includes: Obtain the obstacle area; Based on the obstacle area and the preset safety distance, the danger angle is obtained; Based on the danger angle and the flight heading angle of the UAV, a first obstacle avoidance strategy is obtained; The preset safety distance is: in, To establish a safe distance, The radius of the drone itself, For the safety speed coefficient, The constant absolute speed of the drone, This is the time interval between two time steps.

4. The method according to claim 3, characterized in that, The first obstacle avoidance strategy is: If the angle bisector of the danger angle is located counterclockwise from the UAV's heading angle, then the UAV turns clockwise. If the angle bisector of the danger angle is located clockwise from the flight heading angle of the UAV, then the UAV will turn counterclockwise. If the flight heading angle of the drone is not within the dangerous angle range, the drone will not turn; The obstacle avoidance strategy further includes a second obstacle avoidance strategy, which is: If the distance between the drone swarm and the obstacle area is greater than or equal to a preset obstacle avoidance distance, the drone swarm will maintain formation. If the distance between the drone swarm and the obstacle area is less than the preset obstacle avoidance distance, then the drone closest to the obstacle area has the highest obstacle avoidance priority.

5. The method according to claim 1, characterized in that, The acquisition of the drone obstacle avoidance speed includes: Obtain the obstacle avoidance mechanism coefficient based on the preset safety distance; Obtain the obstacle avoidance angular acceleration based on the obstacle avoidance mechanism coefficients; Obtain the obstacle avoidance angular velocity based on the obstacle avoidance angular acceleration; Obtain the obstacle avoidance heading angle based on the obstacle avoidance heading angular velocity; The obstacle avoidance speed of the UAV is obtained based on the obstacle avoidance heading angle; The obstacle avoidance mechanism coefficient is obtained based on a preset safety distance in the following manner: The obstacle avoidance heading angular acceleration is obtained based on the obstacle avoidance mechanism coefficients in the following manner: The obstacle avoidance angular velocity is obtained based on the obstacle avoidance angular acceleration, in the following manner: The obstacle avoidance heading angle is obtained based on the obstacle avoidance heading angular velocity in the following manner: The obstacle avoidance speed of the UAV is obtained based on the obstacle avoidance heading angle in the following manner: in, For the first The obstacle avoidance mechanism coefficient of a drone. To establish a safe distance, for Time of the first The actual distance between the drone and the nearest obstacle. The radius of the obstacle itself. For the first The obstacle avoidance heading angular acceleration of a drone For the maximum obstacle avoidance heading angular acceleration, For the first The obstacle avoidance heading angular velocity of the drone. For the maximum obstacle avoidance heading angular velocity, Sampling time, The time interval between two time steps. For the first The obstacle avoidance heading angle of the drone. For the first The obstacle avoidance speed of a drone This represents the constant absolute speed of the drone.

6. The method according to claim 1, characterized in that, The initial obstacle avoidance speed of the drone swarm is obtained based on the drone formation speed, the drone obstacle avoidance speed, and the intention adjustment coefficient, in the following manner: in, For the first The initial obstacle avoidance speed of a drone swarm For the first The willingness adjustment coefficient for each drone For the first The obstacle avoidance speed of a drone For the first The speed of drone formations For the first The obstacle avoidance mechanism coefficient of a drone. For the first The first drone in the neighbor set The obstacle avoidance mechanism coefficient of each drone.

7. The method according to claim 1, characterized in that, The attraction velocity constraint is: The repulsion velocity constraint is: The optimization of the original obstacle avoidance speed of the UAV swarm based on attraction and repulsion speed constraints to obtain the optimized obstacle avoidance speed of the UAV swarm is carried out in the following manner: in, For the first Optimize obstacle avoidance speed for drone swarms For the first The initial obstacle avoidance speed of the drone swarm; This is the formation weighting coefficient, used to adjust the priority of "formation coordination" in the overall speed; The exclusion weighting coefficient is used to adjust the priority of "collision avoidance" in the overall speed. For the first The safe rejection speed of a drone For the attraction velocity vector, To attract weighting coefficients, For the first A drone at any time The neighbor repulsion velocity vector, For safe repulsion speed, For the first A drone at any time The actual flight velocity vector of t, The constant absolute speed of the drone, Indicates the distance between the drone and the nearest obstacle. To establish a safe distance, The positional relationship between the drones is represented by the first... The drone and the first The position difference vector of each drone For at any time Located in the The set of all neighboring drones within the repulsive force radius of a given drone. For at any time Located in the The set of all neighboring drones between the repulsive force radius and the attractive force radius of a given drone. For the radius of attraction, The radius represents the repulsive force.

8. An obstacle avoidance device for unmanned aerial vehicles (UAVs), characterized in that, The device is used in a drone swarm, and the device includes: The speed acquisition unit is used to acquire the formation speed of the drones based on their flight heading angle. The strategy acquisition unit is used to acquire an obstacle avoidance strategy based on the distance between the UAV and the obstacle and the flight heading angle of the UAV. The speed acquisition unit is also used to acquire the obstacle avoidance speed of the drone; The speed acquisition unit is also used to obtain the original obstacle avoidance speed of the drone swarm based on the drone formation speed, the drone obstacle avoidance speed, and the intention adjustment coefficient; An optimization unit is used to optimize the original obstacle avoidance speed of the UAV swarm based on the attraction speed constraint and the repulsion speed constraint, so as to obtain the optimized obstacle avoidance speed of the UAV swarm. When the drone avoids obstacles, the obstacle avoidance strategy and the drone swarm are used to optimize the obstacle avoidance speed.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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