An unmanned aerial vehicle intelligent operation and maintenance system based on an internet of things

Abstract

The present application relates to the field of unmanned aerial vehicle operation and maintenance, and particularly relates to an unmanned aerial vehicle intelligent operation and maintenance system based on the Internet of Things. The present application is provided with a data storage module for storing the reaction characteristics of the unmanned aerial vehicle executing obstacle avoidance actions; a data acquisition module for acquiring environmental characteristics of the unmanned aerial vehicle within a predetermined spatial range; an environmental analysis module for calculating environmental interference representation coefficients for the unmanned aerial vehicle based on the environmental characteristics, to analyze the chaotic tendency category of the environmental interference; and a stable analysis module for adaptively operating and maintaining the stability of the unmanned aerial vehicle. The present application executes preset obstacle avoidance actions in advance when the obstacle distance is within a predetermined range, to determine whether the unmanned aerial vehicle can complete the avoidance operation stably and safely according to the current environmental conditions and the performance state of the unmanned aerial vehicle itself, and then corrects the obstacle avoidance actions of the unmanned aerial vehicle or adjusts the acquisition accuracy of the sensor, thereby improving the stability and safety of the unmanned aerial vehicle when executing obstacle avoidance actions under the premise of ensuring data reliability.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of unmanned aerial vehicle operation and maintenance, and particularly relates to an unmanned aerial vehicle intelligent operation and maintenance system based on the Internet of Things. BACKGROUND

[0002] During the flight of the unmanned aerial vehicle in various complex environments, obstacles such as buildings, high-voltage lines, and mountains may be encountered. In order to ensure the safe and stable operation of the unmanned aerial vehicle and avoid collision with obstacles and accidents, the unmanned aerial vehicle is often equipped with high-precision Internet of Things equipment to perceive the characteristics of the environment and obstacles, analyze relevant data, and perform obstacle avoidance actions. In actual situations, diversified application scenarios have higher requirements for unmanned aerial vehicle obstacle avoidance operation and maintenance technology and provide a broad space for its development.

[0003] Chinese Patent Publication No. CN115617077A discloses an automatic obstacle avoidance unmanned aerial vehicle and an automatic obstacle avoidance method. The unmanned aerial vehicle includes an unmanned aerial vehicle body, a radar, a camera body, a distance measuring sensor, and a controller. The radar, camera body, and distance measuring sensor monitor environmental data and upload the environmental data to the controller. The controller receives the environmental data and determines whether there is an obstacle in front of the unmanned aerial vehicle based on the environmental data. When an obstacle exists, the distance between the unmanned aerial vehicle and the obstacle is determined, and the unmanned aerial vehicle is controlled to avoid the obstacle when the distance is less than a preset threshold. Through the above technical solution, the unmanned aerial vehicle disclosed in the present application can automatically identify obstacles based on multiple environmental data and autonomously avoid obstacles based on the distance between the unmanned aerial vehicle and the obstacles, thereby avoiding the unmanned aerial vehicle from colliding with obstacles due to the negligence of the staff.

[0004] However, the prior art still has the following problems,

[0005] When the unmanned aerial vehicle avoids obstacles encountered during flight, in addition to considering the distance between the unmanned aerial vehicle and the obstacles, environmental factors that affect the effectiveness of the obstacle avoidance operation performed by the unmanned aerial vehicle also need to be considered. For example, if the interference of environmental factors is too strong, the state of the unmanned aerial vehicle may not be stable enough to perform the obstacle avoidance operation. At the same time, the data acquisition accuracy of the sensors arranged on the unmanned aerial vehicle may also affect the correct judgment of the unmanned aerial vehicle on the obstacles and the normal execution of the obstacle avoidance operation, which may result in the unmanned aerial vehicle not avoiding obstacles in time, reducing the stability and safety of the unmanned aerial vehicle when performing obstacle avoidance actions. SUMMARY

[0006] To this end, the present application provides an unmanned aerial vehicle intelligent operation and maintenance system based on Internet of Things, to overcome the problem in the prior art that when the unmanned aerial vehicle avoids obstacles encountered in the flight process, in addition to considering the distance between the unmanned aerial vehicle and the obstacles, the influence of environmental factors on the effect of the obstacle avoidance operation performed by the unmanned aerial vehicle also needs to be considered, for example, if the interference of environmental factors is too strong, it may cause the state of the unmanned aerial vehicle to be unable to stably perform the obstacle avoidance operation, at the same time, the data acquisition accuracy of the sensors arranged on the unmanned aerial vehicle may also affect the correct judgment of the unmanned aerial vehicle on the obstacles and the normal execution of the obstacle avoidance operation, and the unmanned aerial vehicle may not avoid obstacles in time near the obstacles, thereby reducing the stability and safety of the unmanned aerial vehicle when performing the obstacle avoidance action.

[0007] To achieve the above-mentioned purpose, the present application provides an unmanned aerial vehicle intelligent operation and maintenance system based on Internet of Things, which comprises:

[0008] A data storage module is used to store the reaction characteristics of the unmanned aerial vehicle performing the obstacle avoidance action, and the reaction characteristics include the reaction time of the unmanned aerial vehicle performing the obstacle avoidance action and the required time for the body to be stable after completing the obstacle avoidance operation;

[0009] A data acquisition module is used to acquire environmental characteristics of the unmanned aerial vehicle in a predetermined spatial range, and the environmental characteristics include the number of obstacles, the distance between the unmanned aerial vehicle and the obstacles, and the air flow intensity;

[0010] An environment analysis module is connected with the data acquisition module and is used to obtain the environmental characteristics acquired by the data acquisition module, to calculate the environmental interference representation coefficient for the unmanned aerial vehicle based on the environmental characteristics, and to analyze the chaos tendency category of the environmental interference;

[0011] A stability analysis module is connected with the data acquisition module, the data storage module and the environment analysis module respectively, and is used to perform operation and maintenance on the stability of the unmanned aerial vehicle based on the analysis result of the environment analysis module, including,

[0012] determining whether to enter the verification opportunity based on the distance between the obstacles and the unmanned aerial vehicle, to perform obstacle avoidance verification, including controlling the unmanned aerial vehicle to perform a preset obstacle avoidance action in advance, obtaining the reaction characteristic of the unmanned aerial vehicle performing the obstacle avoidance operation, analyzing the obstacle avoidance reaction representation parameter of the unmanned aerial vehicle, to determine whether the obstacle avoidance operation performed by the unmanned aerial vehicle meets the timely obstacle avoidance standard;

[0013] Or, adjusting the gain and sampling rate of the sensor for obstacle avoidance in the unmanned aerial vehicle based on the environmental interference representation coefficient for the unmanned aerial vehicle.

[0014] Further, the environment analysis module is used to calculate the environmental interference representation coefficient for the unmanned aerial vehicle based on the environmental characteristics, including,

[0015] calculating a ratio of a number of obstacles present and a number threshold value and a ratio of a mean distance between the UAV and each of the obstacles and a mean threshold value and assigning a corresponding weight coefficient as a first environmental interference feature;

[0016] calculating a ratio of the airflow intensity and an airflow intensity threshold value and assigning a corresponding weight coefficient as a second environmental interference feature;

[0017] determining a sum of the first environmental interference feature and the second environmental interference feature as an environmental interference representation coefficient for the UAV.

[0018] Further, the environmental analysis module is configured to analyze a chaos tendency category of environmental interference, including,

[0019] if the environmental interference representation coefficient is greater than or equal to a preset environmental interference representation coefficient threshold value, determining that the environmental interference is of a high chaos tendency category;

[0020] if the environmental interference representation coefficient is less than the preset environmental interference representation coefficient threshold value, determining that the environmental interference is of a low chaos tendency category.

[0021] Further, the stability analysis module is configured to perform operation and maintenance on the stability of the UAV based on the analysis result of the environmental analysis module, including,

[0022] if the environmental interference is of the high chaos tendency category, determining whether to enter a verification opportunity based on the distance between the obstacles and the UAV to perform obstacle avoidance verification, including controlling the UAV to perform a preset obstacle avoidance action in advance, obtaining a reaction feature of the UAV performing the obstacle avoidance operation, analyzing an obstacle avoidance reaction representation parameter of the UAV to determine whether the obstacle avoidance operation performed by the UAV meets a timely obstacle avoidance standard;

[0023] if the environmental interference is of the low chaos tendency category, adjusting a gain and a sampling rate of a sensor for obstacle avoidance in the UAV based on the environmental interference representation coefficient for the UAV.

[0024] Further, the stability analysis module is configured to determine whether to enter a verification opportunity based on the distance between the obstacles and the UAV, including,

[0025] if the distance between the obstacles and the UAV is less than or equal to a distance threshold value, determining to enter the verification opportunity.

[0026] Further, the stability analysis module is configured to control the UAV to perform a preset obstacle avoidance action in advance, including,

[0027] turning by a predetermined radius, flipping the fuselage, and lifting the nose by a predetermined attitude.

[0028] Further, the stability analysis module is configured to analyze the obstacle avoidance reaction characteristic parameter of the UAV, including,

[0029] calculating a ratio of the reaction time of the UAV performing the obstacle avoidance action to a reaction time threshold value as a first obstacle avoidance reaction characteristic;

[0030] calculating a ratio of the required time for the UAV to stabilize after completing the obstacle avoidance operation to a required time threshold value as a second obstacle avoidance reaction characteristic;

[0031] determining a sum of the first obstacle avoidance reaction characteristic and the second obstacle avoidance reaction characteristic as the obstacle avoidance reaction characteristic parameter.

[0032] Further, the stability analysis module is configured to determine whether the obstacle avoidance operation performed by the UAV meets the timely obstacle avoidance standard, including,

[0033] if the obstacle avoidance reaction characteristic parameter is less than an obstacle avoidance reaction characteristic parameter threshold value, determining that the obstacle avoidance operation performed by the UAV meets the timely obstacle avoidance standard.

[0034] Further, the stability analysis module is configured to adjust the gain and sampling rate of the sensor for obstacle avoidance in the UAV, including,

[0035] increasing the gain, and the gain increase amount is positively correlated with the environmental interference characteristic coefficient;

[0036] increasing the sampling rate, and the sampling rate increase amount is positively correlated with the environmental interference characteristic coefficient.

[0037] Further, the stability analysis module is further configured to issue a warning signal, including,

[0038] if the obstacle avoidance operation performed by the UAV does not meet the timely obstacle avoidance standard, issuing a warning signal.

[0039] Compared with the prior art, the present application sets a data storage module to store the reaction characteristics of the UAV performing the obstacle avoidance action; a data acquisition module to acquire the environmental characteristics of the UAV within a predetermined spatial range; an environmental analysis module to calculate an environmental interference characteristic coefficient for the UAV based on the environmental characteristics, to analyze the chaos tendency category of the environmental interference; and a stability analysis module to adaptively operate and maintain the stability of the UAV. The present application performs a preset obstacle avoidance action on the obstacle in advance when the obstacle is within a predetermined range, determines whether the UAV can stably and safely complete the avoidance operation according to the current environmental conditions and the performance state of the UAV itself, and then corrects the obstacle avoidance action of the UAV or adjusts the collection accuracy of the sensor, thereby improving the stability and safety of the UAV in performing the obstacle avoidance action on the premise of ensuring data reliability.

[0040] Especially, the application calculates the environmental interference representation coefficient for the unmanned aerial vehicle through environmental characteristics, in actual cases, environmental factors will affect the normal flight of the unmanned aerial vehicle, for example, strong airflow may cause the unmanned aerial vehicle body to sway abnormally, unable to fly normally and smoothly, and even may deviate from the planned flight path, at the same time, the related influencing factors of the obstacles observed by the sensor will also affect whether the unmanned aerial vehicle can timely execute the obstacle avoidance operation and the effect of executing the obstacle avoidance operation, for example, too many obstacles existing in the predetermined spatial range, or the distance between the unmanned aerial vehicle and the obstacles is too close, all of which may affect the correct judgment of the unmanned aerial vehicle on the obstacles, the timeliness of executing the obstacle avoidance operation and the normal execution of the obstacle avoidance operation, therefore, the application calculates the environmental interference representation coefficient for the unmanned aerial vehicle by combining the number of obstacles existing in the predetermined spatial range and the distance between the unmanned aerial vehicle and the obstacles with the airflow intensity, to represent the interference degree of environmental factors on the stable and safe flight of the unmanned aerial vehicle, to provide data support for subsequent analysis of the chaos tendency category of environmental interference, and then adaptively maintain the stability of the unmanned aerial vehicle.

[0041] Especially, in the case that the environmental interference is in the high chaos tendency category, since the influence of environmental factors on the flight of the unmanned aerial vehicle is too strong, the verification opportunity is determined according to the distance between the unmanned aerial vehicle and the obstacles, on the premise of ensuring that the unmanned aerial vehicle and the obstacles are in a safe distance, the unmanned aerial vehicle is controlled to pre-execute the preset obstacle avoidance action in advance, including adjusting the attitude of the unmanned aerial vehicle and smoothly executing the turning action to change the flight direction of the unmanned aerial vehicle, at the same time, the flight speed of the unmanned aerial vehicle is controlled to ensure the stability and safety of the unmanned aerial vehicle executing the preset obstacle avoidance action, through the effect of the unmanned aerial vehicle executing the preset obstacle avoidance action, whether the current performance state of the unmanned aerial vehicle can complete the obstacle avoidance operation is observed in advance before reaching the obstacle, to avoid the situation that the unmanned aerial vehicle cannot avoid obstacles in time, therefore, the application calculates the obstacle avoidance reaction representation parameter through the reaction characteristics of the unmanned aerial vehicle when executing the preset obstacle avoidance action, to represent the execution effect of the unmanned aerial vehicle, and then determine whether the execution of the unmanned aerial vehicle meets the timely obstacle avoidance standard, since the preset obstacle avoidance action pre-executed by the unmanned aerial vehicle and the obstacle to be actually executed by the subsequent obstacle avoidance operation are the same target, the preset obstacle avoidance action for the same target obstacle is corrected in time, to ensure that the unmanned aerial vehicle can stably and safely complete the actual obstacle avoidance operation.

[0042] Especially, in the case that the environmental interference is in the low chaos tendency category, the precision coefficient of the sensor used for obstacle avoidance in the unmanned aerial vehicle is adjusted, to ensure that the unmanned aerial vehicle can correctly judge the obstacles and smoothly execute the obstacle avoidance operation when being adjacent to the obstacles, to ensure the effect of executing the obstacle avoidance operation, and then, under the premise of ensuring the reliability and high precision of the data, the stability and safety of the unmanned aerial vehicle when executing the obstacle avoidance action are improved. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 a function module diagram of the unmanned aerial vehicle intelligent operation and maintenance system based on the Internet of Things according to an embodiment of the present application;

[0044] Figure 2 a logic decision diagram for analyzing the chaos tendency category of environmental interference according to an embodiment of the present application;

[0045] Figure 3 a logic decision diagram for determining whether to enter a verification opportunity according to an embodiment of the present application;

[0046] Figure 4 a logic decision diagram for determining whether the obstacle avoidance operation performed by the unmanned aerial vehicle meets the obstacle avoidance standard according to an embodiment of the present application. DETAILED DESCRIPTION

[0047] In order to make the objects and advantages of the present application clearer, the present application will be further described below in conjunction with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application.

[0048] The preferred embodiments of the present application will be described below with reference to the accompanying drawings. It should be understood by those skilled in the art that the embodiments are only used to explain the technical principles of the present application and are not used to limit the protection scope of the present application.

[0049] In addition, it should be further noted that, in the description of the present application, unless otherwise explicitly specified and limited, the term "connection" should be understood broadly, for example, it can be fixed connection, or detachable connection, or integral connection; it can be mechanical connection, or electrical connection. Those skilled in the art can understand the specific meaning of the above-mentioned term in the present application according to the specific circumstances.

[0050] Please refer to Figures 1 to 4 as shown, Figure 1 a function module diagram of the unmanned aerial vehicle intelligent operation and maintenance system based on the Internet of Things according to an embodiment of the present application, Figure 2 a logic decision diagram for analyzing the chaos tendency category of environmental interference according to an embodiment of the present application, Figure 3 a logic decision diagram for determining whether to enter a verification opportunity according to an embodiment of the present application, Figure 4 a logic decision diagram for determining whether the obstacle avoidance operation performed by the unmanned aerial vehicle meets the obstacle avoidance standard according to an embodiment of the present application. The unmanned aerial vehicle intelligent operation and maintenance system based on the Internet of Things according to an embodiment of the present application comprises:

[0051] a data storage module, configured to store reaction characteristics of the unmanned aerial vehicle performing obstacle avoidance actions, wherein the reaction characteristics comprise reaction time of the unmanned aerial vehicle performing obstacle avoidance actions and required time for stabilizing the unmanned aerial vehicle body after completing the obstacle avoidance operation;

[0052] The data acquisition module is configured to acquire environmental characteristics of the UAV within a predetermined spatial range, wherein the environmental characteristics include a number of obstacles, a distance between the UAV and the obstacles, and an air flow intensity.

[0053] The environmental analysis module is connected to the data acquisition module and configured to acquire the environmental characteristics acquired by the data acquisition module, to calculate an environmental interference representation coefficient for the UAV based on the environmental characteristics, and to analyze a chaotic tendency category of the environmental interference.

[0054] The stability analysis module is connected to the data acquisition module, the data storage module, and the environmental analysis module, and is configured to perform operation and maintenance on the stability of the UAV based on the analysis result of the environmental analysis module, including,

[0055] determining whether to enter a verification opportunity based on the distance between the obstacles and the UAV, to perform obstacle avoidance verification, including controlling the UAV to perform a preset obstacle avoidance action in advance, acquiring a reaction characteristic of the UAV performing the obstacle avoidance operation, analyzing an obstacle avoidance reaction representation parameter of the UAV, and determining whether the obstacle avoidance operation performed by the UAV meets a timely obstacle avoidance standard.

[0056] Alternatively, the gain and sampling rate of the sensor for obstacle avoidance in the UAV are adjusted based on the environmental interference representation coefficient for the UAV.

[0057] It can be understood that the reaction time of the UAV performing the obstacle avoidance action refers to the time from the output of the control instruction by the UAV flight controller to the start of the UAV performing the obstacle avoidance action. In addition, the UAV will perform multiple obstacle avoidance actions to avoid obstacles, such as adjusting the flight attitude and changing the flight direction. Therefore, the time required for the UAV body to stabilize after completing the obstacle avoidance operation refers to the time from the completion of the UAV obstacle avoidance action to the start of the UAV body stabilizing and flying smoothly, which will not be described again.

[0058] Specifically, the device for acquiring the environmental characteristics of the UAV within the predetermined spatial range is not limited, and the number of obstacles and the distance between the UAV and the obstacles within the predetermined spatial range can be detected by the UAV carrying a laser radar, the air flow intensity within the predetermined spatial range can be detected by the UAV carrying an anemometer, and other forms can also be used, which will not be described again.

[0059] It can be understood that the predetermined spatial range refers to a spatial range in which the UAV maintains a safe flight distance from other obstacles, and a person skilled in the art can determine it according to the flight speed and maneuverability of the UAV, which can be set within the interval [30m, 50m], which will not be described again.

[0060] Specifically, the specific structure of the data storage module, the environment analysis module and the stability analysis module is not limited, and each unit thereof can be composed of a logic component or a combination of logic components, including a field programmable processor, a computer or a microprocessor in a computer.

[0061] Specifically, the environment analysis module is used to calculate the environmental interference representation coefficient of the UAV based on the environmental characteristics, including,

[0062] calculating the ratio of the number of obstacles to the number threshold value and the sum of the ratio of the average distance between the UAV and each obstacle to the average distance threshold value, and assigning a corresponding weight coefficient as the first environmental interference feature;

[0063] calculating the ratio of the air flow intensity to the air flow intensity threshold value and assigning a corresponding weight coefficient as the second environmental interference feature, and multiplying the numerical value by the weight coefficient to assign the weight coefficient;

[0064] calculating the sum of the first environmental interference feature and the second environmental interference feature as the environmental interference representation coefficient of the UAV.

[0065] In this embodiment, the weight corresponding to the first environmental interference feature is set to 0.45 when performing weighted summation, and the weight corresponding to the second environmental interference feature is set to 0.55;

[0066] The number threshold of obstacles, the distance average threshold between the UAV and each obstacle, and the air flow intensity threshold are obtained by pre-measuring the number of obstacles, the average distance between obstacles, and the air flow intensity detected by the UAV at different times during flight for several times, solving the number average and the air flow intensity average, setting the number threshold of obstacles to be between 1.15 and 1.23 times the number average, the distance average threshold between the UAV and each obstacle to be between 1.12 and 1.24 times the average distance between the UAV and each obstacle, and the air flow intensity threshold to be between 1.25 and 1.35 times the air flow intensity average.

[0067] The average distance between each obstacle is the average distance between each obstacle and the nearest obstacle.

[0068] The application calculates the environmental interference representation coefficient for the unmanned aerial vehicle through environmental characteristics. In actual situations, environmental factors will affect the normal flight of the unmanned aerial vehicle. For example, strong airflow may cause the unmanned aerial vehicle body to sway abnormally, unable to fly normally and smoothly, and may even deviate from the planned flight path. At the same time, the relevant influencing factors of the obstacles observed by the sensor will also affect whether the unmanned aerial vehicle can timely execute the obstacle avoidance operation and the effect of the obstacle avoidance operation. For example, too many obstacles existing in the predetermined spatial range or too close distance between the unmanned aerial vehicle and the obstacles may affect the correct judgment of the unmanned aerial vehicle on the obstacles, the timeliness of the execution of the obstacle avoidance operation and the normal execution of the obstacle avoidance operation. Therefore, the application calculates the environmental interference representation coefficient for the unmanned aerial vehicle by combining the number of obstacles existing in the predetermined spatial range and the distance between the unmanned aerial vehicle and the obstacles with the airflow intensity, so as to represent the interference degree of environmental factors on the stable and safe flight of the unmanned aerial vehicle, provide data support for subsequent analysis of the chaos tendency category of environmental interference, and then adaptively maintain the stability of the unmanned aerial vehicle.

[0069] Specifically, the environment analysis module is used to analyze the chaos tendency category of environmental interference, including,

[0070] If the environmental interference representation coefficient is greater than or equal to a preset environmental interference representation coefficient threshold, it is determined that the environmental interference is of a high chaos tendency category.

[0071] If the environmental interference representation coefficient is less than the preset environmental interference representation coefficient threshold, it is determined that the environmental interference is of a low chaos tendency category.

[0072] The environmental interference representation coefficient H0 is selected in the interval [1.55, 1.67].

[0073] Specifically, the stability analysis module is used to maintain the stability of the unmanned aerial vehicle based on the analysis result of the environment analysis module, including,

[0074] If the environmental interference is of a high chaos tendency category, it is determined whether to enter a verification opportunity based on the distance between the obstacle and the unmanned aerial vehicle, so as to perform obstacle avoidance verification, including controlling the unmanned aerial vehicle to preform a preset obstacle avoidance action, obtaining the reaction feature of the unmanned aerial vehicle performing the obstacle avoidance operation, analyzing the obstacle avoidance reaction representation parameter of the unmanned aerial vehicle, and determining whether the obstacle avoidance operation performed by the unmanned aerial vehicle meets the timely obstacle avoidance standard.

[0075] If the environmental interference is of a low chaos tendency category, the gain and sampling rate of the sensor for obstacle avoidance in the unmanned aerial vehicle are adjusted based on the environmental interference representation coefficient for the unmanned aerial vehicle.

[0076] Specifically, the stability analysis module is used to determine whether to enter a verification opportunity based on the distance between the obstacle and the unmanned aerial vehicle, including,

[0077] If the distance between the obstacle and the UAV is less than or equal to the distance threshold, it is determined that the verification opportunity is entered;

[0078] If the distance between the obstacle and the UAV is greater than the distance threshold, it is determined that the verification opportunity is not entered.

[0079] Specifically, the distance threshold can be set according to a predetermined spatial range, and is set to between 1.5 times and 2 times the predetermined spatial range.

[0080] Specifically, the stability analysis module is used to control the UAV to perform a preset obstacle avoidance action in advance, including,

[0081] A predetermined radius turning, a body flipping, and a predetermined attitude lifting a nose.

[0082] It can be understood that the preset obstacle avoidance action can be set by a person skilled in the art, and the purpose is to verify the effectiveness of the UAV in performing the obstacle avoidance action under environmental interference. For example, common obstacle avoidance actions such as a predetermined radius turning, a body flipping, and a predetermined attitude lifting a nose can be set, and this will not be repeated.

[0083] The predetermined radius is related to the size of the UAV, and can be set by a person skilled in the art;

[0084] The predetermined attitude can be embodied in different pitch angles, which can be set by a person skilled in the art, and this will not be repeated.

[0085] Specifically, the stability analysis module is used to analyze the obstacle avoidance reaction characteristic parameter of the UAV, including,

[0086] The ratio of the reaction time of the UAV in performing the obstacle avoidance action to the reaction time threshold is used as a first obstacle avoidance reaction feature;

[0087] The ratio of the required time for the UAV to stabilize after completing the obstacle avoidance operation to the required time threshold is used as a second obstacle avoidance reaction feature;

[0088] The sum of the first obstacle avoidance reaction feature and the second obstacle avoidance reaction feature is used to determine the obstacle avoidance reaction characteristic parameter.

[0089] The threshold of the reaction time of the UAV executing the obstacle avoidance action and the required time threshold of the UAV body stabilization after completing the obstacle avoidance operation are obtained by pre-determination, related data of the UAV encountering obstacles during flight and completing flight tasks are obtained for several times, the reaction time of the UAV executing the obstacle avoidance action and the required time of the UAV body stabilization after completing the obstacle avoidance operation are called, the mean value of the reaction time of the UAV executing the obstacle avoidance action and the mean value of the required time of the UAV body stabilization after completing the obstacle avoidance operation are solved, the threshold of the reaction time of the UAV executing the obstacle avoidance action is set to 1.03 to 1.11 times of the mean value of the reaction time of the UAV executing the obstacle avoidance action, and the required time threshold of the UAV body stabilization after completing the obstacle avoidance operation is 1.09 to 1.21 times of the mean value of the required time of the UAV body stabilization after completing the obstacle avoidance operation.

[0090] Specifically, the stable analysis module is used to determine whether the obstacle avoidance operation executed by the UAV meets the timely obstacle avoidance standard, including,

[0091] If the obstacle avoidance reaction characteristic parameter is less than the obstacle avoidance reaction characteristic parameter threshold, it is determined that the obstacle avoidance operation executed by the UAV meets the timely obstacle avoidance standard.

[0092] If the obstacle avoidance reaction characteristic parameter is greater than or equal to the obstacle avoidance reaction characteristic parameter threshold, it is determined that the obstacle avoidance operation executed by the UAV does not meet the timely obstacle avoidance standard.

[0093] The obstacle avoidance reaction characteristic parameter is selected in the interval [1.64, 1.78].

[0094] In the case of high chaotic tendency category of environmental intervention, the influence of environmental factors on the flight of the UAV is too strong, therefore, the verification opportunity is determined according to the distance between the UAV and the obstacle, on the premise that the UAV and the obstacle are in a safe distance, the UAV is controlled to execute the preset obstacle avoidance action in advance, including adjusting the attitude of the UAV and smoothly executing the steering action to change the flight direction of the UAV, at the same time, the flight speed of the UAV is controlled to ensure the stability and safety of the UAV executing the preset obstacle avoidance action, through the effect of the UAV executing the preset obstacle avoidance action, it is observed in advance whether the current performance state of the UAV can complete the obstacle avoidance operation before reaching the obstacle, so as to avoid the situation that the UAV avoids not in time near the obstacle, therefore, the application calculates the obstacle avoidance reaction characteristic parameter by the reaction characteristics of the UAV executing the preset obstacle avoidance action, to represent the execution effect of the UAV, and then determines whether the execution of the UAV meets the timely obstacle avoidance standard, since the preset obstacle avoidance action executed by the UAV in advance and the obstacle to be actually executed for the obstacle avoidance operation are the same target, the preset obstacle avoidance action for the same target obstacle is corrected in time, so as to ensure that the UAV can stably and safely complete the actual obstacle avoidance operation.

[0095] Specifically, the stable analysis module is configured to adjust the gain and sampling rate of the sensor for obstacle avoidance in the UAV, comprising,

[0096] increasing the gain, and the gain increase amount is positively correlated with the environmental interference characteristic coefficient;

[0097] increasing the sampling rate, and the sampling rate increase amount is positively correlated with the environmental interference characteristic coefficient.

[0098] In this embodiment, optionally,

[0099] comparing the environmental interference characteristic coefficient with the first environmental interference characteristic coefficient comparison threshold and the second environmental interference characteristic coefficient comparison threshold,

[0100] when the environmental interference characteristic coefficient is greater than or equal to the second environmental interference characteristic coefficient comparison threshold, determining that the gain increase amount is the first gain increase amount, and setting the first gain increase amount to be 0.48 times the reference gain;

[0101] when the environmental interference characteristic coefficient is greater than the first environmental interference characteristic coefficient comparison threshold and less than the second environmental interference characteristic coefficient comparison threshold, determining that the gain increase amount is the second gain increase amount, and setting the second gain increase amount to be 0.36 times the reference gain;

[0102] when the environmental interference characteristic coefficient is less than or equal to the first environmental interference characteristic coefficient comparison threshold, determining that the gain increase amount is the third gain increase amount, and setting the third gain increase amount to be 0.27 times the reference gain;

[0103] wherein the first environmental interference characteristic coefficient comparison threshold is 1.2 times the environmental interference characteristic coefficient threshold, and the second environmental interference characteristic coefficient comparison threshold is 1.4 times the environmental interference characteristic coefficient threshold.

[0104] It can be understood that, for the determination of the reference gain, the default gain setting of the UAV system can be used.

[0105] The way of increasing the gain is not limited, and the gain of the sensor can be increased by the flight control system to improve the response sensitivity of the sensor to obstacles, which will not be repeated here.

[0106] comparing the environmental interference characteristic coefficient with the first environmental interference characteristic coefficient comparison threshold and the second environmental interference characteristic coefficient comparison threshold,

[0107] when the environmental interference characteristic coefficient is greater than or equal to the second environmental interference characteristic coefficient comparison threshold, determining that the sampling rate increase amount is the first sampling rate increase amount, and setting the first sampling rate increase amount to be 0.57 times the initial sampling rate b0;

[0108] When the environmental interference characteristic coefficient is greater than the first environmental interference characteristic coefficient contrast threshold and less than the second environmental interference characteristic coefficient contrast threshold, the sampling rate increase amount is determined as the second sampling rate increase amount, and the second sampling rate increase amount is set as 0.45 times of the initial sampling rate.

[0109] When the environmental interference characteristic coefficient is less than or equal to the first environmental interference characteristic coefficient contrast threshold, the sampling rate increase amount is determined as the third sampling rate increase amount, and the third sampling rate increase amount is set as 0.34 times of the initial sampling rate.

[0110] The first environmental interference characteristic coefficient contrast threshold is 1.2 times of the environmental interference characteristic coefficient threshold, and the second environmental interference characteristic coefficient contrast threshold is 1.4 times of the environmental interference characteristic coefficient threshold.

[0111] The method for increasing the sampling rate of the sensor for obstacle avoidance in the unmanned aerial vehicle is not limited, and the sampling frequency can be increased by the flight control system to quickly respond to the operation of the obstacle, which will not be repeated.

[0112] Specifically, the stable analysis module is also used to issue a warning signal, including,

[0113] If the obstacle avoidance operation performed by the unmanned aerial vehicle does not meet the timely obstacle avoidance standard, a warning signal is issued.

[0114] Specifically, in some possible implementations, the warning signal can be sent to a remote user end for confirmation, and whether the unmanned aerial vehicle continues to fly is confirmed, which will not be repeated.

[0115] In the case of low chaos tendency category of environmental interference, the precision coefficient of the sensor used for obstacle avoidance in the unmanned aerial vehicle is adjusted to ensure that the unmanned aerial vehicle can correctly judge the obstacle and smoothly perform the obstacle avoidance operation when the unmanned aerial vehicle is adjacent to the obstacle, and the effect of the obstacle avoidance operation is ensured. Further, under the premise of ensuring data reliability and high precision, the stability and safety of the unmanned aerial vehicle in performing the obstacle avoidance operation are improved.

[0116] So far, the technical solutions of the present application have been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to related technical features without departing from the principles of the present application, and the technical solutions after the changes or replacements will fall within the protection scope of the present application.

Claims

1. An unmanned aerial vehicle intelligent operation and maintenance system based on an Internet of Things, characterized in that, The method comprises the following steps: a data storage module is configured to store reaction characteristics of the UAV performing obstacle avoidance actions, wherein the reaction characteristics comprise reaction time of the UAV performing obstacle avoidance actions and required time for the UAV body to stabilize after completing the obstacle avoidance operation; a data acquisition module is configured to acquire environmental characteristics of the UAV in a predetermined spatial range, wherein the environmental characteristics comprise the number of obstacles, the distance between the UAV and the obstacles, and the air flow intensity; an environmental analysis module is connected to the data acquisition module and configured to obtain the environmental characteristics acquired by the data acquisition module, calculate the environmental interference characteristic coefficient of the UAV based on the environmental characteristics, and analyze the chaos tendency category of the environmental interference; a stability analysis module is connected to the data acquisition module, the data storage module, and the environmental analysis module, and is configured to perform operation and maintenance on the stability of the UAV based on the analysis result of the environmental analysis module, including: determining whether to enter a verification opportunity based on the distance between the obstacles and the UAV to perform obstacle avoidance verification, including controlling the UAV to perform a preset obstacle avoidance action in advance, obtaining reaction characteristics of the UAV performing the obstacle avoidance operation, analyzing the obstacle avoidance reaction characteristic parameters of the UAV, and determining whether the obstacle avoidance operation performed by the UAV meets the timely obstacle avoidance standard; or, adjusting the gain and sampling rate of the sensor for obstacle avoidance in the UAV based on the environmental interference characteristic coefficient of the UAV. 2.The Internet of Things based unmanned aerial vehicle intelligent operation and maintenance system according to claim 1, characterized in that, The environmental analysis module is configured to calculate the environmental interference characteristic coefficient of the UAV based on the environmental characteristics, including: calculating the ratio of the number of obstacles to the number threshold and the sum of the ratio of the average distance between the UAV and each obstacle to the average threshold, and assigning a corresponding weight coefficient as the first environmental interference characteristic; calculating the ratio of the air flow intensity to the air flow intensity threshold and assigning a corresponding weight coefficient as the second environmental interference characteristic; determining the sum of the first environmental interference characteristic and the second environmental interference characteristic as the environmental interference characteristic coefficient of the UAV. 3.The Internet-of-Things based unmanned aerial vehicle intelligent operation and maintenance system according to claim 1, characterized in that, The environmental analysis module is configured to analyze the chaos tendency category of the environmental interference, including: if the environmental interference characteristic coefficient is greater than or equal to a preset environmental interference characteristic coefficient threshold, the environmental interference is determined to be of a high chaos tendency category; if the environmental interference characteristic coefficient is less than the preset environmental interference characteristic coefficient threshold, the environmental interference is determined to be of a low chaos tendency category. 4.The Internet-of-Things based unmanned aerial vehicle intelligent operation and maintenance system according to claim 1, characterized in that, The stability analysis module is configured to perform operation and maintenance on the stability of the UAV based on the analysis result of the environmental analysis module, including: if the environmental interference is of a high chaos tendency category, determining whether to enter a verification opportunity based on the distance between the obstacles and the UAV to perform obstacle avoidance verification, including controlling the UAV to perform a preset obstacle avoidance action in advance, obtaining reaction characteristics of the UAV performing the obstacle avoidance operation, analyzing the obstacle avoidance reaction characteristic parameters of the UAV, and determining whether the obstacle avoidance operation performed by the UAV meets the timely obstacle avoidance standard; if the environmental interference is of a low chaos tendency category, adjusting the gain and sampling rate of the sensor for obstacle avoidance in the UAV based on the environmental interference characteristic coefficient of the UAV. 5.The Internet-of-Things based unmanned aerial vehicle intelligent operation and maintenance system according to claim 1, characterized in that, The stability analysis module is configured to determine whether to enter a verification opportunity based on a distance between the obstacle and the UAV, comprising, if the distance between the obstacle and the UAV is less than or equal to a distance threshold, determining to enter the verification opportunity. 6.The Internet-of-Things based unmanned aerial vehicle intelligent operation and maintenance system according to claim 1, characterized in that, The stability analysis module is configured to control the UAV to perform a preset obstacle avoidance action in advance, comprising, a predetermined radius turn, a body roll, and a predetermined attitude lift head. 7.The Internet-of-Things based unmanned aerial vehicle intelligent operation and maintenance system according to claim 1, characterized in that, The stability analysis module is configured to analyze an obstacle avoidance reaction characteristic parameter of the UAV, comprising, calculating a ratio of a reaction time of the UAV performing the obstacle avoidance action to a reaction time threshold as a first obstacle avoidance reaction characteristic; calculating a ratio of a required time of the UAV stabilizing the body after completing the obstacle avoidance operation to a required time threshold as a second obstacle avoidance reaction characteristic; determining a sum of the first obstacle avoidance reaction characteristic and the second obstacle avoidance reaction characteristic as the obstacle avoidance reaction characteristic parameter. 8.The Internet-of-Things based unmanned aerial vehicle intelligent operation and maintenance system according to claim 1, characterized in that, The stability analysis module is configured to determine whether the obstacle avoidance operation performed by the UAV meets a timely obstacle avoidance standard, comprising, if the obstacle avoidance reaction characteristic parameter is less than an obstacle avoidance reaction characteristic parameter threshold, determining that the obstacle avoidance operation performed by the UAV meets the timely obstacle avoidance standard. 9.The Internet-of-Things based unmanned aerial vehicle intelligent operation and maintenance system according to claim 1, characterized in that, The stability analysis module is configured to adjust a gain and a sampling rate of a sensor for obstacle avoidance in the UAV, comprising, increasing the gain, and a gain increase amount is positively correlated with the environmental interference characteristic coefficient; increasing the sampling rate, and a sampling rate increase amount is positively correlated with the environmental interference characteristic coefficient. 10.The Internet-of-Things based unmanned aerial vehicle intelligent operation and maintenance system according to claim 1, characterized in that, The stability analysis module is further configured to issue a warning signal, comprising, if the obstacle avoidance operation performed by the UAV does not meet the timely obstacle avoidance standard, issuing the warning signal.

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