CN113867402B

CN113867402B - Farmland unmanned aerial vehicle obstacle avoidance operation method and device based on reference surface

Info

Publication number: CN113867402B
Application number: CN202111268720.2A
Authority: CN
Inventors: 唐宇; 骆少明; 侯超钧; 庄家俊; 钟震宇; 郭琪伟; 苗爱敏; 陈再励; 雷欢; 李嘉豪; 杨捷鹏; 符伊晴; 赵晋飞; 张晓迪
Original assignee: Zhongkai University of Agriculture and Engineering; Guangdong Polytechnic Normal University; Institute of Intelligent Manufacturing of Guangdong Academy of Sciences
Current assignee: Zhongkai University of Agriculture and Engineering; Guangdong Polytechnic Normal University; Institute of Intelligent Manufacturing of Guangdong Academy of Sciences
Priority date: 2021-10-29
Filing date: 2021-10-29
Publication date: 2022-12-20
Anticipated expiration: 2041-10-29
Also published as: CN113867402A

Abstract

The application discloses a farmland unmanned aerial vehicle obstacle avoidance operation method based on a reference surface, wherein a first cable descending operation is executed at a first air position; obtaining a first tension numerical value sequence; calculating a first starting factor; if the first starting factor is smaller than the starting threshold value, executing a first moving operation; performing a second rope lowering operation; obtaining a second tension numerical sequence; calculating a second starting factor; if the second starting factor is smaller than the starting threshold, executing a second moving operation; obtaining a third tension numerical sequence, … and an nth tension numerical sequence; calculating a reference bottom surface, a reference top surface and a reference density surface; controlling the unmanned aerial vehicle to start operation at an initial position, and acquiring response data in front of an operation path of the unmanned aerial vehicle; and generating an obstacle avoidance flight strategy according to the reference bottom surface, the reference top surface, the reference density surface and the response data, and controlling the unmanned aerial vehicle to avoid the obstacle to fly according to the obstacle avoidance flight strategy, so that the purpose of improving the obstacle avoidance operation effect of the farmland unmanned aerial vehicle is achieved.

Description

Farmland unmanned aerial vehicle obstacle avoidance operation method and device based on reference surface

Technical Field

The application relates to the field of intelligent agriculture, in particular to a farmland unmanned aerial vehicle obstacle avoidance operation method and device based on a reference surface, computer equipment and a storage medium.

Background

Farmland unmanned aerial vehicle is through carrying out the operation when flying above the farmland crop. In order to guarantee safety, unmanned aerial vehicle need keep a take the altitude with the farmland when the operation apart from, but this and unmanned aerial vehicle will press close to the demand contradiction of farmland crop operation (because press close to the farmland crop and carry out the operation and can improve unmanned aerial vehicle's operation effect) and prior art lack and press close to the farmland crop, even invade the farmland crop scope and carry out the farmland unmanned aerial vehicle of operation and keep away the barrier operation scheme.

Disclosure of Invention

The application provides a farmland unmanned aerial vehicle obstacle avoidance operation method based on a reference surface, which comprises the following steps:

s1, an unmanned aerial vehicle terminal executes a first cable descending operation at a first aerial position so as to descend a rope preset on the lower surface of the unmanned aerial vehicle; in the process of descending the rope, sensing the tension of the rope in real time through a preset sensor to obtain a first tension numerical sequence; wherein the density of the rope ends is greater than the density of the rope elsewhere;

s2, according to a formula: calculating a first starting factor by using the first starting factor = | the numerical value of the last member of the first pull numerical sequence-the standard pull numerical value |, and judging whether the first starting factor is smaller than a preset starting threshold value or not; wherein the standard tension value is the reading of the sensor when the rope hangs down to the ground;

s3, if the first starting factor is smaller than a preset starting threshold value, executing a first moving operation to enable the unmanned aerial vehicle to move to a second air position; wherein the second aerial location has the same height as the first aerial location;

s4, performing a second rope descending operation at the second aerial position to descend the rope; in the process of descending the rope, the tension of the rope is sensed in real time through the sensor, and a second tension numerical sequence is obtained;

s5, according to a formula: calculating a second starting factor by the second starting factor = | the numerical value of the last member of the second pull force numerical sequence-the standard pull force numerical value |, and judging whether the second starting factor is smaller than a preset starting threshold value or not;

s6, if the second starting factor is smaller than a preset starting threshold value, executing a second moving operation to enable the unmanned aerial vehicle to move to a third air position; wherein the height of the third aerial location is the same as the height of the first aerial location;

s7, continuing the processes of n-2 cable lowering operations, obtaining n-2 tension numerical value sequences, calculating n-2 starting factors and executing n-2 moving operations, so as to obtain a third tension numerical value sequence, … and an nth tension numerical value sequence; wherein n is an integer greater than 3;

s8, calculating a reference bottom surface, a reference top surface and a reference density surface according to the first tension numerical sequence, the second tension numerical sequence, the third tension numerical sequence, … and the nth tension numerical sequence; wherein the reference bottom surface refers to a plane corresponding to the farmland ground; the reference top surface refers to the upper surface of the whole agricultural crop in the farmland; the reference density surface refers to a corresponding plane when the resistance of the rope on the whole crop is greater than a preset value in the descending process of the rope;

s9, controlling the unmanned aerial vehicle to start to operate at an initial position, and performing detection processing by adopting a preset obstacle detection tool in the operation process to obtain response data in front of an operation path of the unmanned aerial vehicle; wherein the obstacle detection means includes at least one of a millimeter wave radar, a laser radar, a camera, and an ultrasonic radar; the height of the initial position is equal to that of the reference top surface;

and S10, generating an obstacle avoidance flight strategy according to the reference bottom surface, the reference top surface, the reference density surface and the response data, and controlling the unmanned aerial vehicle to avoid the obstacle to fly according to the obstacle avoidance flight strategy.

Further, the step S8 of calculating a reference bottom surface, a reference top surface and a reference density surface according to the first pulling force numerical sequence, the second pulling force numerical sequence, the third pulling force numerical sequence, … and the nth pulling force numerical sequence includes:

s801, according to a formula: | A _i -A _i+1 |≥p ₁ ；|A _i -A _i+1 |/|t _i -t _i+1 |≥p ₂ Screening out the mutation value A in the tension value sequence _i+1 Thus obtaining n sets of variation values respectively corresponding to the first tension numerical sequence, the second tension numerical sequence, the third tension numerical sequence, … and the nth tension numerical sequence; wherein each set of mutation values comprises at least two members; a. The _i Is the ith member of the tensile force number series, A _i+1 Is the (i + 1) th member in the tensile force value sequence, p ₁ Is a predetermined mutation value threshold, p ₂ Is a predetermined mutation rate threshold, t _i To correspond to A _i The value of (a) is collected at a time point, t _i+1 Is a pair ofShould be A _i+1 I is an integer which is greater than 1 and less than the number of members in the tension numerical sequence;

s802, respectively selecting the last sequenced last mutation numerical value from each mutation numerical value set, and acquiring a last acquisition time point corresponding to the last mutation numerical value;

s803, acquiring the last position rope descending length corresponding to all the last position acquisition time points according to the corresponding relation between the acquisition time points and the rope descending lengths; the rope descending length is detected by a length sensor preset on the unmanned aerial vehicle;

s804, carrying out mean value processing on all the tail position rope descending lengths to obtain a tail position mean value rope length, and subtracting the tail position mean value rope length from the height of the first aerial position to obtain the height of the reference bottom surface.

Further, the method comprises the following steps of:

|A _i -A _i+1 |≥p ₁ ；|A _i -A _i+1 |/|t _i -t _i+1 |≥p ₂ screening out the mutation value A in the tension value sequence _i+1 After the step S801 of obtaining n sets of variation values corresponding to the first pull force value sequence, the second pull force value sequence, the third pull force value sequence, …, and the nth pull force value sequence, the method includes:

s8011, respectively selecting the first mutation numerical value with the top ranking from each mutation numerical value set, and acquiring a first acquisition time point corresponding to the first mutation numerical value;

s8012, acquiring the first rope descending lengths corresponding to all the first acquisition time points according to the corresponding relation between the acquisition time points and the rope descending lengths; the rope descending length is detected by a length sensor preset on the unmanned aerial vehicle;

s8013, mean processing is performed on all head mean rope descending lengths to obtain a head mean rope length, and the height of the reference top surface is obtained by subtracting the head mean rope length from the height of the first aerial position.

Further, the tail end of the rope is further provided with a light intensity sensor and a wireless transmitter, and the wireless transmitter is used for transmitting light intensity data sensed by the light intensity sensor to the unmanned aerial vehicle terminal;

after the step S8013 of performing average processing on all leading-position rope descending lengths to obtain a leading-position average rope length, and subtracting the leading-position average rope length from the height of the first aerial position to obtain a height of a reference top surface, the method includes:

s80131, acquiring n light intensity data sequences sent by the wireless transmitter; wherein the n light intensity data sequences are obtained by the light intensity sensor through real-time sensing in n cable-down operations;

s80132, selecting appointed light intensity data with a first numerical value smaller than a preset light intensity threshold from each light intensity data sequence, and forming an appointed light intensity data set with n members;

s80133, acquiring a specified rope fall length set corresponding to the specified light intensity data set according to the corresponding relation between the light intensity data and the acquisition time and the corresponding relation between the acquisition time point and the rope fall length; wherein the set of specified rope fall lengths comprises n members;

s80134, mean processing is performed on all members in the specified rope descending length set to obtain a specified mean rope length, and the specified mean rope length is subtracted from the height of the first aerial position to obtain an initial height of a reference density plane;

s80135, calculating a first height difference between the height of the reference top surface and the height of the reference bottom surface, calculating a second height difference between the initial height of the reference density surface and the height of the reference bottom surface, and judging whether the second height difference is greater than a half of the first height difference;

s80136, if the second height difference is not larger than half of the first height difference, taking the initial height of the reference density surface as the final height of the reference density surface.

Further, the step S10 of generating an obstacle avoidance flight strategy according to the reference bottom surface, the reference top surface, the reference density surface and the response data, and controlling the unmanned aerial vehicle to fly in an obstacle avoidance manner according to the obstacle avoidance flight strategy includes:

s101, performing first screening processing on the response data to obtain screened data; wherein the first screening process excludes data below the reference density level;

s102, constructing an environment three-dimensional model by adopting a preset three-dimensional model construction tool and taking the screening data as a basis;

s103, acquiring motion parameters and body shape parameters of the unmanned aerial vehicle, and processing by using an obstacle avoidance flight track generation model established corresponding to the environment three-dimensional model to output a plurality of predicted flight tracks; the motion parameters comprise unmanned aerial vehicle position parameters, and the obstacle avoidance flight track generation model is formed based on a genetic algorithm;

s104, screening the plurality of predicted flight trajectories according to a first rule that the first rule is not lower than the reference bottom surface and the reference density surface and a second rule that the flight duration below the height of the reference top surface is not higher than a preset duration threshold value to obtain a final flight trajectory;

and S105, controlling the unmanned aerial vehicle to fly along the final flight track.

The application provides a barrier operation device is kept away to unmanned aerial vehicle in farmland based on reference surface includes:

the first cable descending unit is used for indicating the unmanned aerial vehicle terminal to execute first cable descending operation at a first air position so as to descend a rope preset on the lower surface of the unmanned aerial vehicle; in the process of descending the rope, sensing the tension of the rope in real time through a preset sensor to obtain a first tension numerical sequence; wherein the density of the rope ends is greater than the density of the rope elsewhere;

a first initiation factor calculation unit for calculating, according to the formula: calculating a first starting factor by using the first starting factor = | the numerical value of the last member of the first pull numerical sequence-the standard pull numerical value |, and judging whether the first starting factor is smaller than a preset starting threshold value or not; wherein the standard tension value is the reading of the sensor when the rope hangs down to the ground;

the first mobile unit is used for executing a first mobile operation if the first starting factor is smaller than a preset starting threshold value so as to enable the unmanned aerial vehicle to move to a second air position; wherein the second aerial location has the same height as the first aerial location;

a second rope lowering unit for performing a second rope lowering operation at the second airborne position to lower the rope; in the process of descending the rope, the tension of the rope is sensed in real time through the sensor, and a second tension numerical sequence is obtained;

a second initiation factor calculation unit for calculating, according to the formula: the second starting factor = | the numerical value of the last member of the second pull force numerical sequence-the standard pull force numerical value |, the second starting factor is calculated, and whether the second starting factor is smaller than a preset starting threshold value or not is judged;

the second moving unit is used for executing a second moving operation if the second starting factor is smaller than a preset starting threshold value so as to enable the unmanned aerial vehicle to move to a third air position; wherein the height of the third aerial location is the same as the height of the first aerial location;

the tension numerical sequence acquisition unit is used for continuing the processes of n-2 cable descending operations, acquiring n-2 tension numerical sequences, calculating n-2 starting factors and executing n-2 moving operations, so that a third tension numerical sequence, a … and an nth tension numerical sequence are obtained; wherein n is an integer greater than 3;

the reference bottom surface calculation unit is used for calculating a reference bottom surface, a reference top surface and a reference density surface according to the first tension numerical value sequence, the second tension numerical value sequence, the third tension numerical value sequence, … and the nth tension numerical value sequence; wherein the reference bottom surface refers to a plane corresponding to the farmland ground; the reference top surface refers to the upper surface of the whole agricultural crop in the farmland; the reference density surface refers to a corresponding plane when the resistance of the rope on the whole crop is greater than a preset value in the descending process of the rope;

the response data acquisition unit is used for controlling the unmanned aerial vehicle to start working at an initial position and carrying out detection processing by adopting a preset obstacle detection tool in the working process so as to acquire response data in front of a working path of the unmanned aerial vehicle; wherein the obstacle detection means includes at least one of a millimeter wave radar, a laser radar, a camera, and an ultrasonic radar; the height of the initial position is equal to that of the reference top surface;

and the obstacle avoidance flight unit is used for generating an obstacle avoidance flight strategy according to the reference bottom surface, the reference top surface, the reference density surface and the response data, and controlling the unmanned aerial vehicle to avoid the obstacle to fly according to the obstacle avoidance flight strategy.

The present application provides a computer device comprising a memory storing a computer program and a processor implementing the steps of any of the above methods when the processor executes the computer program.

The present application provides a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method of any of the above.

The application relates to a method and a device for obstacle avoidance operation of a farmland unmanned aerial vehicle based on a reference surface, computer equipment and a storage medium, wherein a first rope descending operation is executed at a first air position so as to descend a rope preset on the lower surface of the unmanned aerial vehicle; obtaining a first tension numerical value sequence; calculating a first starting factor; if the first starting factor is smaller than a preset starting threshold value, executing a first moving operation; performing a second rope lowering operation to lower the rope; obtaining a second tension numerical sequence; calculating a second starting factor; if the second starting factor is smaller than a preset starting threshold value, executing a second moving operation; continuing the processes of n-2 times of cable lowering operation, obtaining n-2 times of tension numerical value sequence, calculating n-2 times of starting factor and executing n-2 times of moving operation, thereby obtaining a third tension numerical value sequence, … and an nth tension numerical value sequence; calculating a reference bottom surface, a reference top surface and a reference density surface; controlling the unmanned aerial vehicle to start to operate at an initial position, and performing detection processing by adopting a preset obstacle detection tool in the operation process to acquire response data in front of an operation path of the unmanned aerial vehicle; and generating an obstacle avoidance flight strategy according to the reference bottom surface, the reference top surface, the reference density surface and the response data, and controlling the unmanned aerial vehicle to avoid the obstacle to fly according to the obstacle avoidance flight strategy, so that the purpose of improving the obstacle avoidance operation effect of the unmanned aerial vehicle in the farmland is achieved.

Drawings

Fig. 1 is a schematic flow chart of a method for obstacle avoidance operation of a farmland unmanned aerial vehicle based on a reference plane according to an embodiment of the present application;

fig. 2 is a block diagram illustrating a structure of a computer device according to an embodiment of the present application.

The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

Referring to fig. 1, an embodiment of the present application provides a method for obstacle avoidance operation of a farmland unmanned aerial vehicle based on a reference plane, including the following steps:

s8, calculating a reference bottom surface, a reference top surface and a reference density surface according to the first tension numerical sequence, the second tension numerical sequence, the third tension numerical sequence, … and the nth tension numerical sequence; the reference bottom surface refers to a plane corresponding to the farmland ground; the reference top surface refers to the upper surface of the whole agricultural crop in the farmland; the reference density surface refers to a corresponding plane when the resistance of the rope on the whole crop is greater than a preset value in the descending process of the rope;

This application has utilized for three reference surface, benchmark bottom surface, benchmark top surface, benchmark density face promptly (of course, the use is bigger be benchmark top surface and benchmark density face) for unmanned aerial vehicle in farmland keeps away the barrier operation scheme and changes in the realization, and make unmanned aerial vehicle can realize pressing close to the farmland crop flight, can invade the farmland crop flight even. And when invading the farmland crop flight, because only the short time course to the farmland crop is mostly herbaceous plant, and its top is soft tissue more, consequently can not cause the injury to unmanned aerial vehicle (or can not cause big injury, and unmanned aerial vehicle's paddle can set up in the roof this moment, thereby reduce the possibility and the time that relevant structure of flight and farmland crop touched), and to the whole of farmland crop constitution, also can not receive too much injury.

The reference bottom surface, the reference top surface and the reference density surface are detected by means of a special mode, and the method is also a great characteristic of the application. In particular, the rope for rope descent adopted by the application is taken as a sensor with a new concept, and the tension numerical sequence can be obtained through sensing. In the cable descending process, only when an object (such as crops) is touched, the tension of the cable changes, so that the top surface of the crops (farmlands are generally treated simultaneously, crops generally have similar growth vigor and are consistent in height), the bottom surface of the crops (farmlands are generally flat ground, and are consistent in ground height), and the reference density surface (a most prosperous plane for the whole crops; the closer to the ground, the more prosperous the whole tissues of the crops are because the crops grow from low to high, and the percentage of the height of the crops can be used as the basis for determining the reference density surface according to the difference of the types and the growth time of the crops).

Because the reference bottom surface, the reference top surface and the reference density surface are added and used as analysis basis for obstacle avoidance flight of the unmanned aerial vehicle, the unmanned aerial vehicle can consider a flight scheme invading into a farmland crop range in the process of space modeling and obstacle avoidance track generation, and therefore the operation effect is improved.

The field of the present application may be any feasible field, such as a sorghum field. Moreover, the method and the device are applied to farmland scenes with the same flat ground, and in fact, most farmlands are all located on the same flat ground.

The application also can be called as a sensing data acquisition method for the obstacle avoidance operation of the farmland unmanned aerial vehicle, and the method comprises all the contents in the steps S1-S8. This description is intended to illustrate that steps S9-S10 can be implemented using any available prior art, and, of course, can be implemented using the teachings of the present application hereinafter.

As described in the above steps S1-S3, the terminal of the unmanned aerial vehicle performs a first cable lowering operation at a first aerial position, so as to lower a cable preset on the lower surface of the unmanned aerial vehicle; in the process of descending the rope, sensing the tension of the rope in real time through a preset sensor to obtain a first tension numerical sequence; wherein the density of the rope ends is greater than the density of the rope elsewhere; according to the formula: calculating a first starting factor by using the first starting factor = | the numerical value of the last member of the first pull numerical sequence-the standard pull numerical value |, and judging whether the first starting factor is smaller than a preset starting threshold value or not; wherein the standard tension value is the reading of the sensor when the rope hangs down to the ground; if the first starting factor is smaller than a preset starting threshold value, executing a first moving operation to enable the unmanned aerial vehicle to move to a second air position; wherein the second aerial location has a height that is the same as the height of the first aerial location.

The first aerial position is not the flying height position of the unmanned aerial vehicle during formal operation, and actually, the height corresponding to the first aerial position is higher, so that the reliability of data detection can be ensured. And the type of unmanned aerial vehicle operation can be any feasible type, such as pesticide spraying operation and the like. The process of rope descending can be the process of free fall descending. The tension of the rope is sensed in real time by the sensor, so that when the rope encounters resistance, the tension sensed by the sensor is reduced, and when the tension sensed for the first time is reduced, the rope is lowered to the top surface of the crop; when the tension of the rope is reduced to the lowest, the rope is lowered to the ground; when the tension changes continuously, the ropes touch more crop tissues, and when the tension reaches a certain degree, the ropes are considered to be lowered to a reference density surface. In addition, the density of the rope end is greater than the density of the rope at other positions, which indicates that the rope end is tied with a heavy object to facilitate rope descending.

Then according to the formula: the first starting factor = | the numerical value of the last member of the first pull force numerical sequence-the standard pull force numerical value |, the first starting factor is calculated, and whether the first starting factor is smaller than a preset starting threshold value or not is judged; wherein the standard tension value is a reading of the sensor when the rope falls vertically to the ground. The first initiation factor is designed to ensure that the rope has been lowered to the ground, and thus that the first sequence of tension values is sufficiently datan. If the first starting factor is smaller than a preset starting threshold value, executing a first moving operation to enable the unmanned aerial vehicle to move to a second air position; wherein the second aerial location has a height that is the same as the height of the first aerial location. The purpose of moving in the air is to perform cable descent and data acquisition processing. In the present application, the reliability of a single tensile force value sequence is insufficient, so that the acquisition of the tensile force value sequence needs to be performed at multiple places so as to determine the heights of three datum planes of a target farmland. Accordingly, after moving in the air, the heights must be ensured to be the same, otherwise, the two tension value sequences cannot be corresponded.

Performing a second rope lowering operation at the second airborne location to lower the rope, as described in steps S4-S7 above; in the process of descending the rope, the tension of the rope is sensed in real time through the sensor, so that a second tension numerical sequence is obtained; according to the formula: calculating a second starting factor by the second starting factor = | the numerical value of the last member of the second pull force numerical sequence-the standard pull force numerical value |, and judging whether the second starting factor is smaller than a preset starting threshold value or not; if the second starting factor is smaller than a preset starting threshold value, executing a second moving operation to enable the unmanned aerial vehicle to move to a third air position; wherein the height of the third aerial location is the same as the height of the first aerial location; continuing the processes of n-2 times of cable lowering operation, obtaining n-2 times of tension numerical value sequence, calculating n-2 times of starting factor and executing n-2 times of moving operation, thereby obtaining a third tension numerical value sequence, … and an nth tension numerical value sequence; wherein i is an integer of 3 or more and n or less, and n is an integer of 3 or more.

The above-mentioned several times of cable drop, the acquisition of the pulling force numerical sequence, the calculation of the starting factor, several times of moving operations are all repeatedly executed, and the moved positions are preferably uniformly distributed over the target farmland, and the heights should be the same. After the n series of tensile force values have been acquired, the calculation of the three reference surfaces is made possible.

As described in the above steps S8-S10, calculating a reference bottom surface, a reference top surface, and a reference density surface according to the first pull numerical sequence, the second pull numerical sequence, the third pull numerical sequence, …, and the nth pull numerical sequence; wherein the reference bottom surface refers to a plane corresponding to the farmland ground; the reference top surface refers to the upper surface of the whole agricultural crop in the farmland; the reference density surface refers to a corresponding plane when the resistance of the rope on the whole crop is greater than a preset value in the descending process of the rope; controlling the unmanned aerial vehicle to start to operate at an initial position, and performing detection processing by adopting a preset obstacle detection tool in the operation process to acquire response data in front of an operation path of the unmanned aerial vehicle; wherein the obstacle detection means includes at least one of a millimeter wave radar, a laser radar, a camera, and an ultrasonic radar; the height of the initial position is equal to that of the reference top surface; and generating an obstacle avoidance flight strategy according to the reference bottom surface, the reference top surface, the reference density surface and the response data, and controlling the unmanned aerial vehicle to avoid the obstacle to fly according to the obstacle avoidance flight strategy.

Since the tension applied to the rope has characteristics in the reference bottom surface (i.e., the bottom surface of the entire crop), the reference top surface (i.e., the top surface of the entire crop), and the reference density surface, the reference bottom surface, the reference top surface, and the reference density surface can be calculated from the n tension value sequences.

Specifically, the process of calculating the reference bottom surface may adopt any feasible method, for example, the step S8 of calculating the reference bottom surface, the reference top surface and the reference density surface according to the first tensile force numerical sequence, the second tensile force numerical sequence, the third tensile force numerical sequence, … and the nth tensile force numerical sequence includes:

s801, according to a formula:

|A _i -A _i+1 |≥p ₁ ；|A _i -A _i+1 |/|t _i -t _i+1 |≥p ₂ screening out the mutation value A in the tension value sequence _i+1 Thus obtaining n sets of variation values respectively corresponding to the first tension numerical sequence, the second tension numerical sequence, the third tension numerical sequence, … and the nth tension numerical sequence; wherein each set of mutation values comprises at least two members; a. The _i Is the ith member of the tensile force number series, A _i+1 Is the (i + 1) th member in the tensile force value sequence, p ₁ Is a predetermined mutation value threshold, p ₂ Is a predetermined mutation rate threshold, t _i To correspond to A _i The value of (a) is collected at a time point, t _i+1 To correspond to A _i+1 I is an integer greater than 1 and less than the number of members in the tension numerical sequence;

s802, respectively selecting the last sorted last mutation numerical value from each mutation numerical value set, and acquiring a last acquisition time point corresponding to the last mutation numerical value;

In order to ensure the accuracy of the calculation of the reference bottom surface, a special formula is adopted in the method, and the analysis is carried out on the numerical value and the change speed together, namely according to the formula:

|A _i -A _i+1 |≥p ₁ ；|A _i -A _i+1 |/|t _i -t _i+1 |≥p ₂ screening out the mutation value A in the tension value sequence _i+1 . The mutation value A thus selected _i+1 Indicating that it is subject to resistance from foreign objects (either from the ground or from the crop). And further analyzing the mutation values, and selecting the last mutation value in the sequence according to time, wherein the last mutation value corresponds to the value of the rope just descending to the ground, and the tension of the rope cannot continuously descend or cannot continuously and greatly descend due to the support of the ground after the rope descends to the ground. And then the cable descending length of the rope can be determined through the acquisition time point of the last mutation numerical value, and the height of the reference bottom surface can be calculated by combining the height of the first aerial position.

Further, the calculation process of the reference bottom surface is, for example: the method comprises the following steps of:

Thereby utilize the characteristics of no obstacle in the air, confirm to have the first time hindrance effect to the rope can only be crops, therefore first sudden change numerical value is that the peak of crops provides, reacquires corresponding data acquisition point, can learn rope descending length, combines unmanned aerial vehicle's height, can learn the height of benchmark top surface.

Wherein, this application is being held at the cable and is fallen the in-process, and unmanned aerial vehicle keeps hovering state to guarantee the credibility of data.

Further, the reference density surface can be determined in any feasible manner, for example, the tail end of the rope is further provided with a light intensity sensor and a wireless transmitter, and the wireless transmitter is used for transmitting light intensity data sensed by the light intensity sensor to the unmanned aerial vehicle terminal;

s80135 calculating a first height difference between the height of the reference top surface and the height of the reference bottom surface, calculating a second height difference between the initial height of the reference density surface and the height of the reference bottom surface, and judging whether the second height difference is larger than a half of the first height difference;

s80136, if the second height difference is not larger than half of the first height difference, taking the initial height of the reference density plane as the final height of the reference density plane.

Thereby utilizing the natural rule that the more flourishing plants have stronger light-shading property to determine the position of the reference density surface. The definition of the reference density plane may also be different for different types of plants, which may be achieved by presetting the light intensity threshold. And the reference top surface and the reference bottom surface are used as verification modes to ensure the accuracy of the reference density surface. Generally, the reference density surface of the crop should be relatively upper, and therefore, the position of the reference density surface is determined by calculating a first height difference between the reference top surface height and the reference bottom surface height, then calculating a second height difference between the initial height of the reference density surface and the reference bottom surface height, and determining whether the second height difference is greater than half of the first height difference.

Further, if the calculation amount is reduced and the requirement for accuracy is not high, a preset ratio of the height difference between the top surface of the reference and the bottom surface of the reference may be used as the height position of the reference density surface, and the preset ratio is, for example, 2/3. Of course, the predetermined ratio may be different for different crop types. Therefore, the reference bottom surface of the present application has a great role of assisting in determining the height of the reference density surface.

The height of the initial position is equal to the height of the reference top surface, indicating that the drone is beginning to operate against the top surface of the crop. At this moment, though unmanned aerial vehicle presses close to crops, probably there is touching, but this kind touches at most the flexibility of unmanned aerial vehicle fuselage and crops top surface tender leaf and touches, and the flight subassembly of unmanned aerial vehicle paddle class is located the unmanned aerial vehicle roof, consequently can not cause the injury to crops, and unmanned aerial vehicle also can not receive the injury equally.

The obstacle detection tool includes at least one of a millimeter wave radar, a laser radar, a camera, and an ultrasonic radar, and preferably includes all of the millimeter wave radar, the laser radar, the camera, and the ultrasonic radar. As known from the technical development of automatic driving, flight obstacle avoidance and the like, a single obstacle detection tool is insufficient in obstacle detection and space modeling, and therefore different types of detector tools are preferably adopted in the application.

And generating an obstacle avoidance flight strategy according to the reference bottom surface, the reference top surface, the reference density surface and the response data, and controlling the unmanned aerial vehicle to avoid the obstacle to fly according to the obstacle avoidance flight strategy. The specific implementation process can be any feasible process, for example, the spatial modeling is performed based on the reference bottom surface, the reference top surface, the reference density surface and the response data, although the spatial model can be established through the response data in the conventional technology, after the reference bottom surface, the reference top surface and the reference density surface are added, the spatial model is constructed more pertinently, the stereoscopic impression is stronger, and the generation of a better obstacle avoidance flight strategy is facilitated. And, owing to defined benchmark top surface and benchmark density face, consequently the unmanned aerial vehicle of this application keeps away barrier flight track and traditional unmanned aerial vehicle difference, and the unmanned aerial vehicle flight track of this application can be in the farmland crop of invading to a certain extent promptly, nevertheless need guarantee not to be less than benchmark density face to the time can not the overlength.

Specifically, the step S10 of generating an obstacle avoidance flight strategy according to the reference bottom surface, the reference top surface, the reference density surface, and the response data, and controlling the unmanned aerial vehicle to avoid the obstacle flight according to the obstacle avoidance flight strategy includes:

s101, performing first screening processing on the response data to obtain screening data; wherein the first screening process excludes data below the reference density level;

s103, acquiring motion parameters and body shape parameters of the unmanned aerial vehicle, and processing by using an obstacle avoidance flight track generation model established corresponding to the environment three-dimensional model to output a plurality of predicted flight tracks; the motion parameters comprise unmanned aerial vehicle position parameters, and the obstacle avoidance flight track generation model is formed on the basis of a genetic algorithm;

Thereby realized more optimally that unmanned aerial vehicle keeps away the mesh of barrier flight, improved the effect of unmanned aerial vehicle operation. The three reference surfaces are calculated in advance, so that the response data can be processed in advance to reduce the amount of useless data during the construction of the three-dimensional model. The reason is that the present application cannot fly below the reference density plane, and therefore, the data below the reference density plane is useless data, and more accurate screening data can be obtained by excluding the useless data, thereby improving the overall efficiency of the present application. The genetic algorithm can be regarded as a trial and error algorithm, inherits the experience of the last flight failure simulation until a feasible obstacle avoidance flight path is finally obtained, and the constructed environment three-dimensional model is simpler and is suitable for the obstacle avoidance flight path generation model. Of course, the obstacle avoidance flight trajectory generation model of the present application may also adopt any other feasible method. According to first rule and second rule again to guarantee the relative position relation between unmanned aerial vehicle and the crops, finally at most with certain degree of loss as the cost, guarantee to keep away the effect of barrier flight.

According to the farmland unmanned aerial vehicle obstacle avoidance operation method based on the reference surface, a first rope descending operation is executed at a first air position, so that a rope preset on the lower surface of the unmanned aerial vehicle descends; obtaining a first tension numerical value sequence; calculating a first starting factor; if the first starting factor is smaller than a preset starting threshold value, executing a first moving operation; performing a second rope lowering operation to lower the rope; obtaining a second tension numerical sequence; calculating a second starting factor; if the second starting factor is smaller than a preset starting threshold, executing a second moving operation; continuing the processes of n-2 times of cable lowering operation, obtaining n-2 times of tension numerical value sequence, calculating n-2 times of starting factor and executing n-2 times of moving operation, thereby obtaining a third tension numerical value sequence, … and an nth tension numerical value sequence; calculating a reference bottom surface, a reference top surface and a reference density surface; controlling the unmanned aerial vehicle to start operation at an initial position, and performing detection processing by adopting a preset obstacle detection tool in the operation process so as to obtain response data in front of an operation path of the unmanned aerial vehicle; and generating an obstacle avoidance flight strategy according to the reference bottom surface, the reference top surface, the reference density surface and the response data, and controlling the unmanned aerial vehicle to avoid the obstacle to fly according to the obstacle avoidance flight strategy, so that the purpose of improving the obstacle avoidance operation effect of the unmanned aerial vehicle in the farmland is achieved.

The embodiment of the application provides a farmland unmanned aerial vehicle keeps away barrier operation device based on reference surface, includes:

a first initiation factor calculation unit for calculating, according to the formula: the first starting factor = | the numerical value of the last member of the first pull force numerical sequence-the standard pull force numerical value |, the first starting factor is calculated, and whether the first starting factor is smaller than a preset starting threshold value or not is judged; wherein the standard tension value is the reading of the sensor when the rope hangs down to the ground;

a second initiation factor calculation unit for calculating, according to the formula: calculating a second starting factor by the second starting factor = | the numerical value of the last member of the second pull force numerical sequence-the standard pull force numerical value |, and judging whether the second starting factor is smaller than a preset starting threshold value or not;

The operation that the above-mentioned units are used for carrying out respectively corresponds one-to-one with the steps of the farmland unmanned aerial vehicle obstacle avoidance operation method based on the reference surface of the aforementioned embodiment, and is not described herein again.

According to the farmland unmanned aerial vehicle obstacle avoidance operation device based on the reference surface, a first rope descending operation is executed at a first air position, so that a rope preset on the lower surface of the unmanned aerial vehicle descends; obtaining a first tension numerical value sequence; calculating a first starting factor; if the first starting factor is smaller than a preset starting threshold value, executing a first moving operation; performing a second rope lowering operation to lower the rope; obtaining a second tension numerical sequence; calculating a second starting factor; if the second starting factor is smaller than a preset starting threshold value, executing a second moving operation; continuing the processes of n-2 cable lowering operations, obtaining n-2 times of tension numerical value sequences, calculating n-2 times of starting factors and executing n-2 times of moving operations, thereby obtaining a third tension numerical value sequence, … and an nth tension numerical value sequence; calculating a reference bottom surface, a reference top surface and a reference density surface; controlling the unmanned aerial vehicle to start to operate at an initial position, and performing detection processing by adopting a preset obstacle detection tool in the operation process to acquire response data in front of an operation path of the unmanned aerial vehicle; and generating an obstacle avoidance flight strategy according to the reference bottom surface, the reference top surface, the reference density surface and the response data, and controlling the unmanned aerial vehicle to avoid the obstacle to fly according to the obstacle avoidance flight strategy, so that the purpose of improving the obstacle avoidance operation effect of the unmanned aerial vehicle in the farmland is achieved.

Referring to fig. 2, an embodiment of the present invention further provides a computer device, where the computer device may be a server, and an internal structure of the computer device may be as shown in the figure. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the computer designed processor is used to provide computational and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer equipment is used for storing data used by the farmland unmanned aerial vehicle obstacle avoidance operation method based on the reference surface. The network interface of the computer device is used for communicating with an external terminal through a network connection. When the computer program is executed by the processor, the obstacle avoidance operation method of the farmland unmanned aerial vehicle based on the reference surface is realized.

The processor executes the method for obstacle avoidance operation of the farmland unmanned aerial vehicle based on the reference surface, wherein the steps of the method correspond to the steps of the method for obstacle avoidance operation of the farmland unmanned aerial vehicle based on the reference surface in the embodiment one by one, and the steps are not described again.

It will be understood by those skilled in the art that the structures shown in the drawings are only block diagrams of some of the structures associated with the embodiments of the present application and do not constitute a limitation on the computer apparatus to which the embodiments of the present application may be applied.

The computer equipment executes a first cable descending operation at a first air position so as to descend a rope preset on the lower surface of the unmanned aerial vehicle; obtaining a first tension numerical value sequence; calculating a first starting factor; if the first starting factor is smaller than a preset starting threshold value, executing a first moving operation; performing a second rope lowering operation to lower the rope; obtaining a second tension numerical sequence; calculating a second starting factor; if the second starting factor is smaller than a preset starting threshold, executing a second moving operation; continuing the processes of n-2 times of cable lowering operation, obtaining n-2 times of tension numerical value sequence, calculating n-2 times of starting factor and executing n-2 times of moving operation, thereby obtaining a third tension numerical value sequence, … and an nth tension numerical value sequence; calculating a reference bottom surface, a reference top surface and a reference density surface; controlling the unmanned aerial vehicle to start to operate at an initial position, and performing detection processing by adopting a preset obstacle detection tool in the operation process to acquire response data in front of an operation path of the unmanned aerial vehicle; and generating an obstacle avoidance flight strategy according to the reference bottom surface, the reference top surface, the reference density surface and the response data, and controlling the unmanned aerial vehicle to avoid the obstacle to fly according to the obstacle avoidance flight strategy, so that the purpose of improving the obstacle avoidance operation effect of the unmanned aerial vehicle in the farmland is achieved.

An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored thereon, and when the computer program is executed by a processor, the method for obstacle avoidance of a farm unmanned aerial vehicle based on a reference plane is implemented, where steps included in the method correspond to steps of the method for obstacle avoidance of a farm unmanned aerial vehicle based on a reference plane in the foregoing embodiment one to one, and are not described herein again.

The computer-readable storage medium of the application, perform a first cable descending operation at a first aerial position to descend a cable preset on the lower surface of the unmanned aerial vehicle; obtaining a first tension numerical value sequence; calculating a first starting factor; if the first starting factor is smaller than a preset starting threshold value, executing a first moving operation; performing a second rope lowering operation to lower the rope; obtaining a second tension numerical sequence; calculating a second starting factor; if the second starting factor is smaller than a preset starting threshold, executing a second moving operation; continuing the processes of n-2 times of cable lowering operation, obtaining n-2 times of tension numerical value sequence, calculating n-2 times of starting factor and executing n-2 times of moving operation, thereby obtaining a third tension numerical value sequence, … and an nth tension numerical value sequence; calculating a reference bottom surface, a reference top surface and a reference density surface; controlling the unmanned aerial vehicle to start to operate at an initial position, and performing detection processing by adopting a preset obstacle detection tool in the operation process to acquire response data in front of an operation path of the unmanned aerial vehicle; and generating an obstacle avoidance flight strategy according to the reference bottom surface, the reference top surface, the reference density surface and the response data, and controlling the unmanned aerial vehicle to avoid the obstacle to fly according to the obstacle avoidance flight strategy, so that the purpose of improving the obstacle avoidance operation effect of the unmanned aerial vehicle in the farmland is achieved.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware associated with a computer program or instructions, the computer program can be stored in a non-volatile computer-readable storage medium, and the computer program can include the processes of the embodiments of the methods described above when executed. Any reference to memory, storage, database, or other medium provided herein and used in the examples may 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 a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRDRAM), enhanced SDRAM (ESDRAM), synchronous Link (Synchlink) DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct bused dynamic RAM (DRDRAM), and bused dynamic RAM (RDRAM).

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, apparatus, article, or method that comprises the element.

The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are also included in the scope of the present application.

Claims

1. A farmland unmanned aerial vehicle obstacle avoidance operation method based on a reference surface is characterized by comprising the following steps:

s1, an unmanned aerial vehicle terminal executes a first cable descending operation at a first aerial position so as to descend a rope preset on the lower surface of the unmanned aerial vehicle; in the descending process of the rope, sensing the tension of the rope in real time through a preset sensor so as to obtain a first tension numerical sequence; wherein the density of the rope ends is greater than the density of the rope elsewhere;

s4, performing a second rope descending operation at the second aerial position to descend the rope; in the process of descending the rope, the tension of the rope is sensed in real time through the sensor, so that a second tension numerical sequence is obtained;

s5, according to a formula: the second starting factor = | the numerical value of the last member of the second pull force numerical sequence-the standard pull force numerical value |, the second starting factor is calculated, and whether the second starting factor is smaller than a preset starting threshold value or not is judged;

2. The reference surface-based farmland unmanned aerial vehicle obstacle avoidance operation method as claimed in claim 1, wherein the step S8 of calculating the reference bottom surface, the reference top surface and the reference density surface according to the first tension numerical sequence, the second tension numerical sequence, the third tension numerical sequence, … and the nth tension numerical sequence comprises:

s801, according to a formula: | A _i -A _i+1 |≥p ₁ ；|A _i -A _i+1 |/|t _i -t _i+1 |≥p ₂ Screening out the mutation value A in the tension value sequence _i+1 Thus obtaining n sets of variation values respectively corresponding to the first tension numerical sequence, the second tension numerical sequence, the third tension numerical sequence, … and the nth tension numerical sequence; wherein each set of mutation values comprises at least two members; a. The _i Is the ith member of the tensile force number series, A _i+1 Is the (i + 1) th member of the tensile force number sequence, p ₁ Is a predetermined mutation value threshold, p ₂ Is a predetermined mutation rate threshold, t _i To correspond to A _i The value of (a) is collected at a time point, t _i+1 To correspond to A _i+1 I is an integer greater than 1 and less than the number of members in the tension numerical sequence;

3. The reference surface-based obstacle avoidance operation method for the farmland unmanned aerial vehicle as claimed in claim 2, wherein according to a formula: | A _i -A _i+1 |≥p ₁ ；|A _i -A _i+1 |/|t _i -t _i+1 |≥p ₂ Screening out the mutation value A in the tension value sequence _i+1 So as to obtain n sets of variation values corresponding to the first, second, third, … and nth pull force value sequences respectivelyAfter S801, the method includes:

s8011, selecting the first mutation value with the top sequence from each mutation value set respectively, and acquiring a first acquisition time point corresponding to the first mutation value;

4. The reference surface-based farmland unmanned aerial vehicle obstacle avoidance operation method as claimed in claim 3, wherein the rope end is further provided with a light intensity sensor and a wireless transmitter, the wireless transmitter is used for transmitting light intensity data sensed by the light intensity sensor to the unmanned aerial vehicle terminal;

s80134, mean processing is carried out on all members in the specified rope descending length set to obtain a specified mean rope length, and the height of the first aerial position is adopted to subtract the specified mean rope length, so that the initial height of a reference density surface is obtained;

5. The reference surface-based farmland unmanned aerial vehicle obstacle avoidance operation method as claimed in claim 1, wherein said step S10 of generating an obstacle avoidance flight strategy according to said reference bottom surface, reference top surface, reference density surface and said response data, and controlling unmanned aerial vehicle obstacle avoidance flight according to said obstacle avoidance flight strategy, comprises:

6. The utility model provides a farmland unmanned aerial vehicle keeps away barrier operation device based on reference surface which characterized in that includes:

the first cable descending unit is used for indicating the unmanned aerial vehicle terminal to execute a first cable descending operation at a first air position so as to descend a rope preset on the lower surface of the unmanned aerial vehicle; in the process of descending the rope, sensing the tension of the rope in real time through a preset sensor to obtain a first tension numerical sequence; wherein the density of the rope ends is greater than the density of the rope elsewhere;

a second rope lowering unit for performing a second rope lowering operation at the second airborne position to lower the rope; in the process of descending the rope, the tension of the rope is sensed in real time through the sensor, so that a second tension numerical sequence is obtained;

7. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 5 when executing the computer program.

8. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.