Unmanned aerial vehicle autonomous obstacle avoidance control system based on multiple sensors

Abstract

The invention relates to the technical field of unmanned aerial vehicle obstacle avoidance, in particular to an unmanned aerial vehicle autonomous obstacle avoidance control system based on multiple sensors, and the system comprises an information collection module which is used for collecting unmanned aerial vehicle obstacle avoidance feature information, comprising an air velocity detection array used for collecting air velocities of a plurality of velocity detection points around the unmanned aerial vehicle, a temperature detection array used for collecting heat of a plurality of heat detection points around the unmanned aerial vehicle, and an ultrasonic detection array used for collecting motion ultrasonic features of a plurality of positions of an object to be subjected to obstacle avoidance. The state recognition module is used for determining the hedging state of an obstacle avoidance area according to the obstacle avoidance feature information of the unmanned aerial vehicle; the obstacle avoidance control module is used for determining a corresponding obstacle avoidance mode according to the hedging type, including adjusting an obstacle avoidance deceleration speed until the phase locking value is unqualified, or optimizing an obstacle avoidance path of the unmanned aerial vehicle according to a corresponding position on the object to be subjected to obstacle avoidance; according to the invention, the safety and accuracy of obstacle avoidance are improved.

Description

Technical Field

[0001] This invention relates to the field of drone obstacle avoidance technology, and in particular to a multi-sensor-based autonomous obstacle avoidance control system for drones. Background Technology

[0002] While current drone obstacle avoidance systems have made some progress in obstacle avoidance technology for drones, they still suffer from problems such as insufficient environmental adaptability, failure in certain complex scenarios, and weak obstacle avoidance handling for dynamic objects.

[0003] Chinese Patent Publication No. CN112000123A discloses a rotorcraft drone obstacle avoidance control system and its control method, relating to the field of drone obstacle avoidance control technology. It includes five obstacle avoidance sub-modules and one control module. This invention combines a ToF depth sensor and a vision sensor to design an obstacle avoidance sub-module capable of high-precision obstacle location. By installing multiple of these sub-modules on the rotorcraft drone, high-precision location of obstacles around the drone can be achieved, and then a real-time obstacle avoidance algorithm based on an artificial potential field method can be used to quickly avoid obstacles. This system can effectively improve the drone's perception accuracy and avoidance speed regarding surrounding obstacles. However, the rotorcraft drone obstacle avoidance control system and its control method suffer from a problem: the heat generated by friction with the air during drone flight and the weakened air density due to air disturbance create a region where the drone's positional stability is weakened, making it difficult to accurately avoid dynamic objects. Summary of the Invention

[0004] To address this issue, the present invention provides an autonomous obstacle avoidance control system for unmanned aerial vehicles (UAVs) based on multiple sensors. This system overcomes the problem in the prior art where the UAV's positional stability is weakened due to heat generated by friction with the air during flight and air disturbance caused by air density reduction, making it difficult to accurately avoid obstacles when facing dynamic objects.

[0005] To achieve the above objectives, the present invention provides a multi-sensor-based autonomous obstacle avoidance control system for unmanned aerial vehicles (UAVs), comprising:

[0006] The information acquisition module is used to collect obstacle avoidance feature information of the UAV, including an air velocity detection array for collecting air velocity at several velocity detection points around the UAV, a temperature detection array for collecting heat at several heat detection points around the UAV, and an ultrasonic detection array for collecting the motion ultrasonic features of several locations of the obstacle to be avoided.

[0007] A status recognition module, connected to the information acquisition module, is used to determine the collision state of the obstacle avoidance area based on the obstacle avoidance feature information of the UAV. It includes an air density positioning component for determining the air density weakening area based on the air flow rate and the heat, and an obstacle avoidance area connected to the air density positioning component for determining the obstacle avoidance area based on the ratio of the wind collision angle between the air density weakening area and the UAV target forward area. It also includes a collision state determination component for determining the collision type in the obstacle avoidance area based on the duration of the qualified phase lock value at the corresponding position on the obstacle to be avoided in the obstacle avoidance area.

[0008] An obstacle avoidance control module, which is connected to the information acquisition module and the status recognition module respectively, is used to determine the corresponding obstacle avoidance mode according to the collision type, including adjusting the obstacle avoidance deceleration speed until the phase lock value is unqualified, or optimizing the obstacle avoidance path of the UAV according to the corresponding position on the obstacle to be avoided.

[0009] Furthermore, the largest three-dimensional spatial region formed by the lines connecting the corresponding velocity detection points that meet the preset airflow velocity conditions is defined as the air disturbance region, wherein,

[0010] The preset air velocity condition is that the air velocity at a single velocity detection point is greater than the preset air velocity.

[0011] Furthermore, the largest three-dimensional spatial region formed by connecting the corresponding heat detection points that meet the preset heat conditions is defined as the heat disturbance region, wherein,

[0012] The preset heat condition is that the temperature at a single heat detection point is greater than a preset temperature.

[0013] Furthermore, the largest three-dimensional closed region formed by the corresponding unit regions satisfying the distribution density condition in the overlapping region of the air disturbance region and the heat disturbance region is defined as the air density weakening region, wherein,

[0014] The distribution density condition is that the distribution density of temperature detection points in each unit area of ​​the overlapping region is greater than the preset distribution density.

[0015] Furthermore, if the ratio of the wind collision angle between the air density weakening area and the drone target forward area is greater than a preset angle ratio, then the area in the drone target forward area where wind collision occurs is determined as the obstacle avoidance area.

[0016] Furthermore, the wind counter-angle ratio is the ratio of the flow angle of the wind force flowing from the obstacle to the drone in the drone's target forward region to the right angle.

[0017] Furthermore, if the duration is longer than the preset duration, the collision type within the obstacle avoidance area is determined to be a natural wind collision type; if the duration is shorter than the preset duration, the collision type within the obstacle avoidance area is determined to be a structurally consistent collision type.

[0018] Furthermore, in response to the natural wind counter-collision type, the obstacle avoidance path of the UAV is optimized according to the corresponding position on the obstacle to be avoided; in response to the structurally consistent counter-collision type, the obstacle avoidance deceleration speed is reduced until the phase lock value is unqualified.

[0019] Furthermore, the phase lock value is determined to be unqualified based on the fact that the phase lock value is less than the preset lock value.

[0020] Furthermore, a three-dimensional closed region formed by connecting the corresponding positions on the obstacle to be avoided with a duration longer than the preset duration is added to the obstacle avoidance forward region of the UAV to optimize the obstacle avoidance path.

[0021] Compared with the prior art, the beneficial effects of the present invention are as follows: The obstacle avoidance control system of the present invention, by setting up an information acquisition module, a status recognition module, and an obstacle avoidance control module, determines the air density weakening region based on the air disturbance region and the heat disturbance region. The disturbance range of the UAV on the airflow, combined with the heat generated by the UAV's friction with the air and its own vibration during flight, causes the air to expand, thus increasing the space volume occupied by gas molecules. Therefore, the air density distribution in the region where the air disturbance region and the heat disturbance region overlap decreases, resulting in a reduced support effect for the UAV in the air density weakening region. This leads to instability in the UAV's flight process. When the UAV enters the air density weakening region and encounters strong winds, the obstacle avoidance path becomes disordered, preventing the UAV from properly avoiding obstacles. Therefore, by determining the obstacle avoidance region, the main areas where obstacle avoidance path disorder occurs are identified. This reduces the impact of obstacle avoidance path errors on UAV obstacle avoidance. Furthermore, the specific collision type is determined based on the duration of the phase lock value at the corresponding position on the obstacle to be avoided within the obstacle avoidance area. When the collision type is natural wind collision, it indicates that the ability of natural wind to change the motion state of several points on the obstacle to be avoided is stronger than the ability of the obstacle's own structure to passively change the motion state between points. Moreover, the consistency of the motion state changes at various points on the obstacle to be avoided caused by natural wind can last for a period of time, but the synchronization of motion states caused by the structure of the obstacle itself is very short-lived. Therefore, by identifying the operating state of the obstacle to be avoided within the obstacle avoidance area and determining the collision type, the main factors causing the current motion state of the obstacle to be avoided are identified, resulting in a more accurate identification of airflow disturbances on one side of the obstacle to be avoided, thereby improving the accuracy and safety of the obstacle avoidance control system.

[0022] Furthermore, the system of the present invention reduces the obstacle avoidance deceleration speed until the phase lock value fails. When the motion state of the object to be avoided is mainly influenced by the structural characteristics of the obstacle itself, the obstacle to be avoided...

[0023] As structural stress decays, the object's position gradually returns to its initial structural correlation. Therefore, the period from when the obstacle to be avoided generates a structural consistency-type response to when it returns to its initial structural correlation is the time during which the drone should slow down its speed during obstacle avoidance. By reducing the flight speed to avoid situations where the larger range of obstacles after the obstacle's structural state has recovered might affect the drone's flight safety, the drone can receive early warnings, avoiding collisions with moving obstacles and thus improving the drone's obstacle avoidance safety.

[0024] Furthermore, by adding a three-dimensional closed region formed by connecting the corresponding positions on the obstacle to be avoided with a duration longer than the preset duration to the obstacle avoidance forward region of the UAV, the present invention increases the range of the obstacle avoidance region of the UAV, thereby giving the UAV more operational space to adapt to more sudden situations, thus improving the obstacle avoidance accuracy and safety of the UAV. Attached Figure Description

[0025] Figure 1 This is an overall structural block diagram of the multi-sensor-based autonomous obstacle avoidance control system for unmanned aerial vehicles (UAVs) according to an embodiment of the present invention.

[0026] Figure 2 This is a schematic diagram illustrating the collision type identification of the multi-sensor-based autonomous obstacle avoidance control system for unmanned aerial vehicles (UAVs) according to an embodiment of the present invention.

[0027] Figure 3 This is a structural block diagram of the state recognition module of the multi-sensor-based UAV autonomous obstacle avoidance control system according to an embodiment of the present invention;

[0028] Figure 4 This is a detailed structural block diagram of the information acquisition module of the multi-sensor-based UAV autonomous obstacle avoidance control system according to an embodiment of the present invention;

[0029] Explanation of reference numerals in the attached diagram: 1-UAV body, 2-Obstacle to be avoided, 3-Ultrasonic detection array, 4-Air velocity detection array, 5-Temperature detection array, 6-Heat disturbance area, 7-Air density weakening area, 8-Air disturbance area, 9-Obstacle avoidance area, 10-UAV target movement area. Detailed Implementation

[0030] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0031] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art will understand that...

[0032] These embodiments are merely for explaining the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0033] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0034] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0035] Please see Figure 1 , Figure 2 , Figure 3 as well as Figure 4 The diagrams shown are, respectively, an overall structural block diagram of a multi-sensor-based autonomous obstacle avoidance control system for unmanned aerial vehicles (UAVs), a schematic diagram of collision type identification, a structural block diagram of a state identification module, and a specific structural block diagram of an information acquisition module, according to an embodiment of the present invention. An embodiment of the present invention provides an autonomous obstacle avoidance control system for unmanned aerial vehicles (UAVs) based on multiple sensors, comprising:

[0036] The information acquisition module is used to collect obstacle avoidance feature information of the UAV, including an air velocity detection array 4 for collecting air velocity at several velocity detection points around the UAV, a temperature detection array 5 for collecting heat at several heat detection points around the UAV, and an ultrasonic detection array 3 for collecting the motion ultrasonic features of several locations of the obstacle to be avoided 2.

[0037] A status recognition module, connected to the information acquisition module, is used to determine the collision state of the obstacle avoidance area 9 based on the obstacle avoidance feature information of the UAV. It includes an air density positioning component for determining the air density weakening area 7 based on the air flow rate and the heat, and an obstacle avoidance area 9 connected to the air density positioning component for determining the obstacle avoidance area 9 based on the ratio of the wind collision angle between the air density weakening area 7 and the UAV target forward area 10. It also includes a collision state determination component for determining the collision type in the obstacle avoidance area 9 based on the duration of the qualified phase lock value at the corresponding position on the obstacle to be avoided 2 in the obstacle avoidance area 9.

[0038] An obstacle avoidance control module, which is connected to the information acquisition module and the status recognition module respectively, is used to determine the corresponding obstacle avoidance mode according to the collision type, including adjusting the obstacle avoidance deceleration speed until the phase lock value is unqualified, or optimizing the obstacle avoidance path of the UAV according to the corresponding position on the obstacle to be avoided 2.

[0039] Specifically, the obstacle avoidance characteristic information of the drone includes the airflow at several velocity detection points around the drone.

[0040] The speed, heat at several heat detection points around the drone, and the motion ultrasonic characteristics of several locations of the obstacle to be avoided 2.

[0041] Specifically, motion ultrasound features include motion velocity and motion acceleration per unit monitoring cycle at each location, motion trajectory, and three-dimensional coordinates of the motion location.

[0042] Those skilled in the art will understand that both the air density positioning component and the hedging state determination component are software components that perform data processing tasks. In essence, they are basic data processing software with corresponding functions, consisting of several program codes. The specific code programs of the air density positioning component and the hedging state determination component will not be described in detail here.

[0043] Specifically, the airflow velocity detection array 4 is a real-time monitoring system for the three-dimensional spatial flow field using multiple wind speed sensors and a synchronous acquisition module.

[0044] Specifically, the temperature detection array 5 and the ultrasonic detection array 3 are conventional detection devices well known to those skilled in the art, and their specific operating principles will not be elaborated here.

[0045] In implementation, the obstacle avoidance control system of this invention, by setting up an information acquisition module, a status recognition module, and an obstacle avoidance control module, determines the air density weakening region 7 based on the air disturbance region 8 and the heat disturbance region 6. The disturbance range of the UAV on the airflow, combined with the heat generated by the UAV's friction with the air and its own vibration during flight, causes the air to expand, thus increasing the space volume occupied by gas molecules. Therefore, the air density distribution in the area where the air disturbance region 8 overlaps with the heat disturbance region 6 decreases. This reduces the support provided by the air density weakening region 7 for the UAV, leading to instability during flight. If strong winds encounter the UAV when it enters the air density weakening region 7, the obstacle avoidance path may become disordered, preventing the UAV from properly avoiding obstacles. Therefore, by determining the obstacle avoidance region 9, the main area where the obstacle avoidance path becomes disordered is identified, reducing the risk of this disruption. The impact of obstacle avoidance path disorder on UAV obstacle avoidance is discussed. Furthermore, the specific collision type is determined based on the duration of the phase lock value at the corresponding position on the obstacle to be avoided (2) within obstacle avoidance zone 9. When the collision type is natural wind collision, it indicates that the ability of natural wind to change the motion state of several points on the obstacle to be avoided (2) is stronger than the ability of the obstacle's own structure to passively change the motion state between its points. Moreover, the consistency of the motion state changes at various points on the obstacle caused by natural wind can last for a period of time, but the synchronization of motion states caused by the structure of the obstacle itself is very short. Therefore, by identifying the operating state of the obstacle to be avoided (2) within obstacle avoidance zone 9 and determining the collision type, the main factors causing the current motion state of the obstacle to be avoided (2) are identified. This allows for a more accurate identification of airflow disturbances on one side of the obstacle to be avoided (2), thereby improving the accuracy and safety of the obstacle avoidance control system.

[0046] This includes determining an air disturbance region 8 for the drone based on the air velocity at several velocity detection points around the drone, determining a heat disturbance region 6 around the drone based on the heat at several heat detection points, determining an air density weakening region 7 based on the air disturbance region 8 and the heat disturbance region 6, determining an obstacle avoidance region 9 based on the wind force collision angle ratio between the air density weakening region 7 and the drone target forward region 10, and determining the collision type within the obstacle avoidance region 9 based on the duration of the qualified phase lock value at the corresponding position on the obstacle to be avoided 2 within the obstacle avoidance region 9.

[0047] Specifically, the largest three-dimensional spatial region formed by connecting the corresponding velocity detection points that meet the preset airflow velocity conditions is defined as the air disturbance region 8.

[0048] The preset air velocity condition is that the air velocity at a single velocity detection point is greater than the preset air velocity.

[0049] Optionally, the preset airflow velocity can be selected within the range of [1.2m / s, 1.5m / s].

[0050] Preferably, the preset airflow velocity is 1.3 m / s in the preferred embodiment.

[0051] Those skilled in the art will understand that the preset air velocity is greater than the natural wind speed in the environment where the drone is located, such as a forest. When the air velocity at the velocity detection point around the drone exceeds the preset air velocity, it is determined that the drone has disturbed the surrounding air, thereby determining the air disturbance area 8. The air disturbance area 8 means the maximum disturbance range of the drone to the surrounding air environment.

[0052] Specifically, the largest three-dimensional spatial region formed by connecting the corresponding heat detection points that meet the preset heat conditions is defined as the heat disturbance region 6, wherein,

[0053] The preset heat condition is that the temperature at a single heat detection point is greater than a preset temperature.

[0054] Optionally, when the ambient temperature of the environment where the drone is located is 28°C, the preset temperature selection range is:

[0055] [30℃, 35℃]; the preferred embodiment of the preset temperature is 32℃.

[0056] Specifically, the largest three-dimensional closed region formed by the corresponding unit regions satisfying the distribution density condition in the overlapping regions of the air disturbance region 8 and the heat disturbance region 6 is defined as the air density weakening region 7.

[0057] The distribution density condition is that the distribution density of temperature detection points in each unit area of ​​the overlapping region is greater than the preset distribution density.

[0058] Specifically, a unit region is a unit region divided into overlapping regions based on the same volume, and the volume of each unit region is the same or approximately the same. When the difference between the volume of a unit region and the individual volume of another unit region does not exceed one-fifth of the individual volume, they are considered to be approximately the same. Those skilled in the art will understand that the criteria for determining approximately the same can be adaptively adjusted according to the actual size of the overlapping region and are not limited thereto. One-fifth is just a preferred implementation method.

[0059] Specifically, the distribution density of temperature detection points in each unit area is the ratio of the number of all temperature detection points in each unit area to the volume of a single unit area.

[0060] Optionally, the number of temperature detection points in a single unit area is 6, and the volume of a single unit area is 1m³. 3 Under these conditions, the selectable range for the distribution density of temperature detection points in each unit area of ​​the overlapping region is [2 points / m²]. 3 4 per m 3 The preferred embodiment is 3 units / m 3 .

[0061] Specifically, if the wind collision angle ratio between the air density weakening region 7 and the UAV target forward region 10 is greater than the preset angle ratio, then the region in the UAV target forward region 10 where wind collision occurs is determined as the obstacle avoidance region 9.

[0062] Optionally, the preset angle percentage can be selected within the range of [0.4, 1]; the preferred embodiment of the preset angle percentage is 0.5.

[0063] Specifically, the wind counter-angle ratio is the ratio of the flow angle of the wind force flowing from the obstacle to be avoided 2 towards the drone in the drone target advance area 10 to the right angle.

[0064] Specifically, the angle of the wind force flowing from the obstacle to be avoided 2 toward the drone is the angle between the wind force and the horizontal vertical line of the drone's direction of travel.

[0065] Specifically, if the duration is longer than the preset duration, the collision type in the obstacle avoidance area 9 is determined to be natural wind collision type; if the duration is shorter than the preset duration, the collision type in the obstacle avoidance area 9 is determined to be structurally consistent collision type.

[0066] Optionally, if the obstacle to be avoided 2 is a tree in a forest, and the length of the continuous straight line connecting the corresponding position on the trunk or branch structure of the obstacle to be avoided 2 is 1m, the preset duration can be selected within the range of [1.5 seconds, 3 seconds]; the preferred embodiment of the preset duration is 2 seconds.

[0067] Those skilled in the art will understand that the above-mentioned optional range and preferred embodiment of the preset duration are optional ranges and preferred embodiments under the condition of a length of 1m. Those skilled in the art can adaptively adjust the preset duration according to the natural wind speed, the type of drone and the type of obstacle 2 to be avoided during implementation.

[0068] Specifically, in response to the natural wind counter-collision type, the obstacle avoidance path of the UAV is optimized according to the corresponding position on the obstacle to be avoided 2; in response to the structurally consistent counter-collision type, the obstacle avoidance deceleration speed is reduced until the phase lock value is unqualified.

[0069] Specifically, the obstacle avoidance deceleration speed is positively correlated with the duration of the obstacle avoidance deceleration. The obstacle avoidance deceleration speed means the acceleration during the deceleration process. During the reduction of the obstacle avoidance deceleration speed, the straight-line distance between the air density weakening area 7 of the drone and the obstacle avoidance area 9 must also be considered. The ultimate goal is to reduce the speed of the drone in the original forward direction to zero before the drone reaches the position of the obstacle avoidance area 9 and the phase lock value becomes unqualified.

[0070] In implementation, the system of the present invention reduces the obstacle avoidance deceleration speed until the phase lock value is unqualified. Since the motion state of the obstacle to be avoided is mainly affected by the structural correlation of the obstacle to be avoided 2 itself, the motion position of the obstacle to be avoided 2 will gradually recover to the initial structural correlation level as the structural stress decays. Therefore, the period from the generation of the structural consistency counteraction type response of the obstacle to be avoided 2 to the recovery to the initial structural correlation level is the period during which the speed of the UAV should be slowed down during the obstacle avoidance process. By reducing the flight speed of obstacle avoidance to avoid situations where the larger range of the obstacle to be avoided 2 after the structural state of the obstacle to be avoided 2 recovers may affect the flight safety of the UAV, the UAV can receive early warning and avoid the problem of collision between the UAV and the moving obstacle to be avoided 2, thereby improving the safety of UAV obstacle avoidance.

[0071] Specifically, the phase lock value is determined to be unqualified if it is less than the preset lock value.

[0072] Specifically, the qualified phase lock value of the corresponding position on the obstacle to be avoided 2 is the phase lock value of a portion of the corresponding positions on the obstacle to be avoided 2 that meet the qualified phase lock value.

[0073] As will be understood by those skilled in the art, the phase lock value is an indicator that quantifies the phase synchronization between signals and is used to determine the consistency of the motion states of multiple points. It belongs to the prior art, so the calculation process of the phase lock value will not be described in detail here.

[0074] Optionally, the preset locking value can be selected from a range of [0.4, 0.6]; the preferred embodiment of the preset locking value is 0.5.

[0075] Specifically, a three-dimensional closed region formed by connecting the corresponding positions on the obstacle to be avoided 2 with a duration longer than the preset duration is added to the obstacle avoidance forward region of the UAV to optimize the obstacle avoidance path.

[0076] In practice, this invention adds a three-dimensional closed region formed by connecting the corresponding positions on the obstacle to be avoided 2 with a duration longer than the preset duration to the obstacle avoidance forward region of the UAV, thereby increasing the range of the obstacle avoidance region 9 of the UAV, thus giving the UAV more operational space to adapt to more sudden situations, and thus improving the obstacle avoidance accuracy and safety of the UAV.

[0077] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A multi-sensor-based autonomous obstacle avoidance control system for unmanned aerial vehicles (UAVs), characterized in that, include: The information acquisition module is used to collect obstacle avoidance feature information of the UAV, including an air velocity detection array for collecting air velocity at several velocity detection points around the UAV, a temperature detection array for collecting heat at several heat detection points around the UAV, and an ultrasonic detection array for collecting the motion ultrasonic features of several locations of the obstacle to be avoided. A status recognition module, connected to the information acquisition module, is used to determine the collision state of the obstacle avoidance area based on the obstacle avoidance feature information of the UAV. It includes an air density positioning component for determining the air density weakening area based on the air flow rate and the heat, and an obstacle avoidance area connected to the air density positioning component for determining the obstacle avoidance area based on the ratio of the wind collision angle between the air density weakening area and the UAV target forward area. It also includes a collision state determination component for determining the collision type in the obstacle avoidance area based on the duration of the qualified phase lock value at the corresponding position on the obstacle to be avoided in the obstacle avoidance area. An obstacle avoidance control module, which is connected to the information acquisition module and the status recognition module respectively, is used to determine the corresponding obstacle avoidance mode according to the collision type, including adjusting the obstacle avoidance deceleration speed until the phase lock value is unqualified, or optimizing the obstacle avoidance path of the UAV according to the corresponding position on the obstacle to be avoided.

2. The multi-sensor-based autonomous obstacle avoidance control system for unmanned aerial vehicles according to claim 1, characterized in that, The largest three-dimensional spatial region formed by connecting the corresponding velocity detection points that meet the preset airflow velocity conditions is defined as the air disturbance region. The preset air velocity condition is that the air velocity at a single velocity detection point is greater than the preset air velocity.

3. The multi-sensor-based autonomous obstacle avoidance control system for unmanned aerial vehicles according to claim 2, characterized in that, The largest three-dimensional spatial region formed by connecting the corresponding heat detection points that meet the preset heat conditions is defined as the heat disturbance region. The preset heat condition is that the temperature at a single heat detection point is greater than a preset temperature.

4. The multi-sensor-based autonomous obstacle avoidance control system for unmanned aerial vehicles according to claim 3, characterized in that, The largest three-dimensional closed region formed by the corresponding unit regions satisfying the distribution density condition in the overlapping region of the air disturbance region and the heat disturbance region is defined as the air density weakening region. The distribution density condition is that the distribution density of temperature detection points in each unit area of ​​the overlapping region is greater than the preset distribution density.

5. The multi-sensor-based autonomous obstacle avoidance control system for unmanned aerial vehicles according to claim 4, characterized in that, If the ratio of the wind collision angle between the air density weakening area and the drone target's forward movement area is greater than a preset angle ratio, then the area in the drone target's forward movement area where wind collision occurs is determined as the obstacle avoidance area.

6. The multi-sensor-based autonomous obstacle avoidance control system for unmanned aerial vehicles according to claim 5, characterized in that, The wind counter-angle ratio is the ratio of the flow angle of the wind force flowing from the obstacle to the drone in the drone's target forward region to the right angle.

7. The UAV autonomous obstacle avoidance control system based on multiple sensors according to claim 6, characterized in that, If the duration is longer than the preset duration, the collision type within the obstacle avoidance area is determined to be natural wind collision type; if the duration is shorter than the preset duration, the collision type within the obstacle avoidance area is determined to be structurally consistent collision type.

8. The multi-sensor-based autonomous obstacle avoidance control system for unmanned aerial vehicles according to claim 7, characterized in that, In response to the natural wind counter-collision type, the obstacle avoidance path of the UAV is optimized according to the corresponding position on the obstacle to be avoided; in response to the structurally consistent counter-collision type, the obstacle avoidance deceleration speed is reduced until the phase lock value is unqualified.

9. The multi-sensor-based autonomous obstacle avoidance control system for unmanned aerial vehicles according to claim 8, characterized in that, The phase lock value is deemed unqualified if it is less than the preset lock value.

10. The multi-sensor-based autonomous obstacle avoidance control system for unmanned aerial vehicles according to claim 9, characterized in that, The three-dimensional closed region formed by connecting the corresponding positions on the obstacle to be avoided with a duration longer than the preset duration is added to the obstacle avoidance forward region of the UAV to optimize the obstacle avoidance path.

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