CN116661476A - Precise plant protection multi-rotor unmanned aerial vehicle system for greenhouse and control method - Google Patents
Precise plant protection multi-rotor unmanned aerial vehicle system for greenhouse and control method Download PDFInfo
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- 239000000575 pesticide Substances 0.000 claims abstract description 22
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- 239000000447 pesticide residue Substances 0.000 description 3
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- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
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Abstract
The invention relates to a precise plant protection multi-rotor unmanned aerial vehicle system for a greenhouse and a control method, wherein the system comprises a task load module, a motion control module, a perception obstacle avoidance module and a task management module, the task load module comprises a medicine spraying part and a vision inspection part, the vision inspection part is used for acquiring external image information, the perception obstacle avoidance module is used for acquiring obstacle information on a navigation path of the unmanned aerial vehicle, the task management module performs planning and control on the navigation path of the unmanned aerial vehicle according to the external image information, the obstacle information and the condition of the medicine spraying part, and the motion control module is used for controlling and driving the flight of the unmanned aerial vehicle and the spraying action of the medicine spraying part. Compared with the prior art, the invention has the advantages of uniform pesticide spraying, high utilization rate and the like.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to a precise plant protection multi-rotor unmanned aerial vehicle system for a greenhouse and a control method.
Background
The development of the foreign modern facility agriculture is early and the development speed is fast. A preliminary reasonable facility vegetable production system taking a greenhouse as a center and combining production technologies such as windshields, greenhouses, film soil covering and the like is established in China from the 1980 s. Later, the facility agriculture is steadily developed, and by 2002, china becomes the first large facility agriculture country in the world. Compared with the traditional agricultural production mode, the facility agriculture is more efficient and has more industrialized characteristics. In particular, the facility agriculture is not limited by time and space, and an engineering technology means is used for providing a proper growth environment for plant production, so that higher yield, quality and economic benefit are obtained.
At present, the agricultural application of the unmanned aerial vehicle in the open production environment (field) outside facilities is actively advanced, for example, chinese patent CN108313296A discloses a novel unmanned aerial vehicle which is used for agricultural sowing and adopts a wireless remote control technology, the quantity of seeds stored in the unmanned aerial vehicle can be increased through a storage device, the unmanned aerial vehicle can be used for sowing in a large area during sowing, the unmanned aerial vehicle is prevented from needing to fill seeds back and forth, the agricultural sowing efficiency of equipment is improved, and the current discharge amount of the unmanned aerial vehicle is saved.
But no accurate plant protection unmanned aerial vehicle capable of independently flying is designed aiming at the agricultural scene of facilities. At present, no accurate plant protection unmanned aerial vehicle capable of independently flying for a greenhouse is available. The existing plant protection technology in the greenhouse mainly comprises manual pesticide spraying, a remote pesticide spraying vehicle is used for spraying the pesticide, the penetration of the pesticide spraying vehicle on plants is limited, the pesticide utilization rate is low, and more pesticide residues exist on crops.
Disclosure of Invention
The invention aims to overcome the defects that in the prior art, when spraying medicines manually, the human body of staff is damaged, when spraying medicines by a remote control medicine spraying vehicle, the penetration strength of plants is limited, the utilization rate of pesticides is not high, and the spraying is uneven, so that more pesticide residues exist on crops, and provides a precise plant protection multi-rotor unmanned aerial vehicle system for a greenhouse and a control method.
The aim of the invention can be achieved by the following technical scheme:
a many rotor unmanned aerial vehicle of accurate plant protection system for warmhouse booth, including task load module, motion control module, perception keep away barrier module and task management module, task load module includes that the medicine sprays part and vision inspection part, the vision inspection part is used for acquireing external image information, the perception keeps away barrier module and is used for acquireing the barrier information on the unmanned aerial vehicle navigation route, task management module carries out unmanned aerial vehicle navigation route's planning and control according to external image information, barrier information and the condition that the medicine sprayed the part, motion control module is used for controlling the flight of drive unmanned aerial vehicle and the spraying action of medicine spraying part.
Further, the motion control module comprises a flight control computer, and a gyroscope, an accelerometer, a magnetometer and a barometer which are connected with the flight control computer and are used for controlling the operation of the unmanned aerial vehicle power system and the task load system.
The scheme also provides a control method of the precise plant protection multi-rotor unmanned aerial vehicle system for the greenhouse, which comprises the following steps:
acquiring an area to be inspected, moving the unmanned aerial vehicle to the area to be inspected, acquiring the flight height and the horizontal width of image acquisition of the unmanned aerial vehicle, planning an inspection route of the unmanned aerial vehicle, and enabling the unmanned aerial vehicle to fly autonomously according to the planned inspection route to acquire the image of the area to be inspected;
judging whether plant protection operation is needed according to the acquired image of the area to be inspected, and determining the area to be plant protected when plant protection is needed;
and acquiring the spraying quantity of the unit area of the area to be protected and the unmanned aerial vehicle, planning a plant protection route of the unmanned aerial vehicle according to the distribution characteristic of the nozzles, and enabling the unmanned aerial vehicle to fly autonomously according to the planned plant protection route to perform plant protection operation.
Further, in the routing planning process, the routing interval is determined based on the coverage width of the visual routing component in the horizontal direction, and the routing interval is smaller than the coverage width of the image in the horizontal direction, so that the routing interval is based on a cow tillage reciprocating method to obtain the planned routing.
Further, the unmanned aerial vehicle plant protection route planning comprises the following specific steps:
acquiring the to-be-protected area and the droplet distribution characteristics of the pesticide spraying part at the corresponding flight height of the unmanned aerial vehicle, and determining the plant protection route interval of the unmanned aerial vehicle according to the to-be-protected area and the droplet distribution characteristics of the pesticide spraying part; the plant protection route interval is the horizontal distance between two adjacent routes of the unmanned aerial vehicle; and obtaining a planned plant protection route in the region to be protected according to the plant protection navigation interval based on a Niu Geng reciprocating method.
Further, the plant protection route interval directly influences the overlapping ratio of the fog drops, wherein the overlapping ratio of the fog drops on two routes is defined as the ratio of the overlapping area of the fog drops on the ground on the two routes to the area of the fog drops on the ground on the single route; and (3) determining the optimal plant protection route interval by acquiring the variance of the precipitation amount of the fog drops at each point on the ground and taking the minimum value of the variance as a target in a constraint range.
Further, the variance formula of the amount of mist deposition on the ground is expressed as:
where Var_D represents the variance of the amount of mist deposited on the ground, W max Is the upper limit of the spray width of the nozzle, D (x, L) is the deposition amount of mist drops at one point on the spray zone,is the average value of fog drop deposition on the ground strip, and L represents the plant protection route interval.
Further, the optimal plant protection route interval under the condition of minimum variance is determined through a grid discretization algorithm, and the method specifically comprises the following steps:
dividing the area on the ground into a plurality of small rectangles, wherein the area of each small rectangle is delta S, and the abscissa of the center point of each small rectangle is x i ；
The amount of droplet deposition on each small rectangle was approximated to that of the center point, i.e., D (x) i ,L)；
Approximating the sum of the deposition amounts of droplets on all small rectangles on the ground to the sum of the deposition amounts of droplets on all points on the ground, i.e
The sum of the areas of all small rectangles on the ground is approximated to the number of all points on the ground, i.e
The variance formula of the corresponding precipitation amount of the mist drops on the ground after the determination treatment is expressed as follows:
in the method, in the process of the invention,after the distribution of the spray nozzles of the medicine spraying component is determined, uniformity under different plant protection route intervals is obtained, and further the plant protection route interval with the most uniform ground fog drop distribution is determined.
Further, the unmanned aerial vehicle autonomous flight process comprises:
the task management module acquires the motion state of the unmanned aerial vehicle through the motion control module, and acquires surrounding environment information through the perception obstacle avoidance module;
according to the motion state of the unmanned aerial vehicle and surrounding environment information, path planning is carried out to obtain a safe navigation route;
and driving the unmanned aerial vehicle to navigate according to the safe navigation route through the motion control module.
Further, the motion control module comprises an accelerometer, a gyroscope, a magnetometer, a barometer and a GNSS, and the acquired motion state comprises the attitude, the speed and the position of the unmanned aerial vehicle.
Compared with the prior art, the invention has the following advantages:
(1) According to the scheme, the unmanned aerial vehicle constructs the variance of the ground fogdrop precipitation quantity related to the plant protection route interval by acquiring the fogdrop distribution characteristics of the plant protection area and the pesticide spraying part, and the variance of the ground fogdrop precipitation quantity is used as an objective function, so that the plant protection route interval capable of enabling fogdrops to be most uniform is obtained, and the pesticide sprayed on plants is distributed more uniformly when the unmanned aerial vehicle performs plant protection operation, the pesticide utilization rate is improved, the pesticide waste is avoided, and the damage to the plants caused by excessive pesticide residues is avoided, so that the plant protection operation is more accurate.
(2) According to the scheme, the unmanned aerial vehicle carries out the safety path planning of autonomous flight according to the self state and the acquired surrounding environment information, so that the process of inspection and plant protection through the manual remote control device is avoided while the navigation safety is ensured, and the accuracy and safety of inspection and plant protection are improved.
(3) Plant protection work is carried out through unmanned aerial vehicle in this scheme, has avoided staff and the closely participation of pesticide spraying process, avoids the danger that pesticide was exposed, is favorable to staff's safety and health.
Drawings
Fig. 1 is a schematic block diagram of an unmanned aerial vehicle system according to the present invention;
fig. 2 is a flowchart of a control method of the unmanned aerial vehicle system provided by the invention;
FIG. 3 is a schematic illustration of a reciprocating method of cow farming provided by the present invention;
FIG. 4 is a schematic view of a routing and imaging area provided by the present invention
FIG. 5 is a flow chart of the plant protection route planning provided by the invention;
FIG. 6 is a flow chart of the inspection task provided by the invention;
fig. 7 is a flowchart of autonomous flight of an unmanned aerial vehicle provided by the invention;
FIG. 8 is a flow chart of plant protection operations provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
Example 1
The embodiment provides a many rotor unmanned aerial vehicle of accurate plant protection system for warmhouse booth, as shown in fig. 1, including task load module, motion control module, perception keep away barrier module and task management module, task load module includes that the medicine sprays part and vision inspection part, the vision inspection part is used for acquireing external image information, the perception keeps away barrier module and is used for the novel barrier on the unmanned aerial vehicle navigation route, task management module carries out unmanned aerial vehicle navigation route's planning and control according to external image information, the novel and medicine of barrier and sprays the condition of part, motion control module is used for controlling the flight of drive unmanned aerial vehicle and the spraying action of medicine spraying part.
Further, the motion control module comprises a flight control computer, and a gyroscope, an accelerometer, a magnetometer and a barometer which are connected with the flight control computer and are used for controlling the operation of the unmanned aerial vehicle power system and the task load system.
The embodiment also provides a control method of the precise plant protection multi-rotor unmanned aerial vehicle system for the greenhouse, as shown in fig. 2, comprising the following steps:
acquiring an area to be inspected, moving the unmanned aerial vehicle to the area to be inspected, acquiring the flight height and the horizontal width of image acquisition of the unmanned aerial vehicle, planning an inspection route of the unmanned aerial vehicle, and enabling the unmanned aerial vehicle to fly autonomously according to the planned inspection route to acquire the image of the area to be inspected;
judging whether plant protection operation is needed according to the acquired image of the area to be inspected, and determining the area to be plant protected when plant protection is needed;
and acquiring the spraying quantity of the unit area of the area to be protected and the unmanned aerial vehicle, planning a plant protection route of the unmanned aerial vehicle according to the distribution characteristic of the nozzles, and enabling the unmanned aerial vehicle to fly autonomously according to the planned plant protection route to perform plant protection operation.
In the course of routing inspection route planning, the routing inspection route interval is determined based on the coverage width of the vision routing inspection component acquisition image in the horizontal direction, and the routing inspection route interval is smaller than the coverage width of the image in the horizontal direction, so that the routing inspection route interval is obtained based on a cow cultivation reciprocating method.
Specifically, the unmanned aerial vehicle plant protection route planning comprises the following specific steps:
acquiring the to-be-protected area and the droplet distribution characteristics of the pesticide spraying part at the corresponding flight height of the unmanned aerial vehicle, and determining the plant protection route interval of the unmanned aerial vehicle according to the to-be-protected area and the droplet distribution characteristics of the pesticide spraying part; the plant protection route interval is the horizontal distance between two adjacent routes of the unmanned aerial vehicle; and obtaining a planned plant protection route in the region to be protected according to the plant protection navigation interval based on a Niu Geng reciprocating method.
The plant protection route interval directly influences the overlapping ratio of the fog drops, wherein the overlapping ratio of the fog drops on two routes is defined as the ratio of the overlapping area of the fog drops on the ground on the two routes to the area of the fog drops on the ground on the single route; and (3) determining the optimal plant protection route interval by acquiring the variance of the precipitation amount of the fog drops at each point on the ground and taking the minimum value of the variance as a target in a constraint range.
Further, the variance formula of the precipitation amount of mist droplets on the ground is expressed as:
where Var_D represents the variance of the amount of mist deposited on the ground，W max Is the upper limit of the spray width of the nozzle, D (x, L) is the deposition amount of mist drops at one point on the spray zone,is the average value of fog drop deposition on the ground strip, and L represents the plant protection route interval.
Preferably, the optimal plant protection route interval under the condition of minimum variance is determined by a grid discretization algorithm, and the specific steps comprise:
dividing the area on the ground into a plurality of small rectangles, wherein the area of each small rectangle is delta S, and the abscissa of the center point of each small rectangle is x i ；
The amount of droplet deposition on each small rectangle was approximated to that of the center point, i.e., D (x) i ,L)；
Approximating the sum of the deposition amounts of droplets on all small rectangles on the ground to the sum of the deposition amounts of droplets on all points on the ground, i.e
The sum of the areas of all small rectangles on the ground is approximated to the number of all points on the ground, i.e
The variance formula of the corresponding precipitation amount of the mist drops on the ground after the determination treatment is expressed as follows:
in the method, in the process of the invention,after the distribution of the spray nozzles of the medicine spraying component is determined, uniformity under different plant protection route intervals is obtained, and further the plant protection route interval with the most uniform ground fog drop distribution is determined.
Specifically, the unmanned aerial vehicle autonomous flight process includes:
the task management module acquires the motion state of the unmanned aerial vehicle through the motion control module, and acquires surrounding environment information through the perception obstacle avoidance module;
according to the motion state of the unmanned aerial vehicle and surrounding environment information, path planning is carried out to obtain a safe navigation route;
and driving the unmanned aerial vehicle to navigate according to the safe navigation route through the motion control module.
The motion control module comprises an accelerometer, a gyroscope, a magnetometer, a barometer and a GNSS, and the acquired motion state comprises the gesture, the speed and the position of the unmanned aerial vehicle.
In combination with the above, this embodiment also provides an embodiment of a more specific precise plant protection multi-rotor unmanned aerial vehicle system and control method for a greenhouse, which specifically includes:
a many rotor unmanned aerial vehicle of accurate plant protection for warmhouse booth can realize unmanned aerial vehicle in warmhouse booth and independently fly, carries out unmanned aerial vehicle inspection task and unmanned aerial vehicle plant protection task.
Specifically, as shown in fig. 1, the pesticide spraying component consists of a pesticide box, a water pump, a spray head, a liquid level meter, a flowmeter and a connecting pipeline; the vision inspection component consists of a camera and a cradle head.
The motion control module is as follows:
the flight control computer is connected with the gyroscope, the accelerometer, the magnetometer and the barometer to control the operation of the power system and the task load system of the unmanned aerial vehicle. The electric actuating mechanism comprises a motor, a rotor wing and a frame for fixing the equipment of the unmanned aerial vehicle.
The perception obstacle avoidance module is as follows:
the obstacle avoidance sensing module is a sensor such as ultrasonic, radar, laser and vision
The task management module:
and the airborne computer and the communication link are connected with the motion control module, the camera in the task load module and the perception obstacle avoidance module, and can be accessed to a wireless network.
The ground station is comprehensively displayed as a data link of the unmanned aerial vehicle which can be accessed by a computer and is used for displaying the state information of the unmanned aerial vehicle.
As shown in fig. 2, the overall flow of the unmanned aerial vehicle system is: the unmanned aerial vehicle uses the mounted cradle head camera module to carry out inspection operation on the planting area, and judges whether plant protection operation is needed according to the inspection result; if the plant protection operation is needed, firstly determining the plant protection area, and then carrying out the plant protection. The unmanned aerial vehicle completes the inspection task and the plant protection task in an autonomous flight mode.
The inspection task refers to that an unmanned aerial vehicle uses a mounted camera to collect images in an area to be inspected and uploads the images to a server for analysis and judgment.
As shown in fig. 6, after the area to be inspected is obtained, the coverage area of the photo can be determined according to the camera model and the flying height in the inspection task. And determining the route interval according to the coverage width of the image in the horizontal direction. The lane spacing is slightly smaller than the coverage width of the image in the horizontal direction. The distance between shots will be slightly less than the coverage distance in the vertical direction of the image. The route is planned by using a ox farming reciprocating method according to the route interval, as shown in figure 3.
During the inspection process, no one can add the accurate position information in shooting to the image, and the image is uploaded to a server. In the inspection operation process, the unmanned aerial vehicle carries out autonomous flight without manual control. Autonomous flight of the drone will end after the plant protection mission.
As shown in fig. 4, for a rectangular inspection area, the solid black line is the planned course and the dashed line is the imaging area for each photograph.
As shown in fig. 8, the plant protection task refers to that the unmanned aerial vehicle uses a mounted spraying system to uniformly spray the liquid medicine to the area to be plant protected. The plant protection task is input into the area and the spraying amount of unit area where the plant protection operation is required. The unmanned aerial vehicle will plan the route of plant protection according to the distribution characteristics of the nozzle.
After planning the plant protection route, add the liquid medicine to unmanned aerial vehicle, unmanned aerial vehicle will carry out the plant protection operation with plant protection task segmentation according to the load capacity when the plant protection operation. In the plant protection operation process, unmanned aerial vehicle uses autonomous flight mode operation, sprays the velocity of flow according to unmanned aerial vehicle's flight speed automatically regulated, improves the degree of consistency of spraying.
Without fig. 5, the route planning of unmanned aerial vehicle plant protection operation is a full coverage path planning, and the route is usually planned by using cow tillage reciprocating regulation.
The key to this approach is to determine the course interval. The course interval refers to the horizontal distance between two adjacent courses, and directly influences the distribution condition of mist drops on the ground in the spraying process.
If the distance between the air lines is too large, the overlapping ratio of fog drops between adjacent air lines is too low, so that the deposition amount of some areas on the ground is insufficient, and the control effect is affected; if the distance between the routes is too small, the overlapping degree of fog drops between adjacent routes is too high, so that the deposition amount of some areas on the ground is too large, and the medicine waste and the environmental pollution are caused. The overlap ratio of the fog drops refers to the ratio of the overlapping area of the fog drops on the ground on two airlines to the area of the fog drops on the ground on a single airline. The overlapping ratio of the fog drops is in a proper range, and the deposition quantity between adjacent aviation wires has a certain compensation effect, so that the overall uniformity is improved.
The present invention uses variance as an indicator of uniformity.
Plant protection is more concerned with the uniformity of the deposition amount of mist drops at each point on the ground, namely, the deposition amount of each point on the ground is as equal as possible. The variance is an index for measuring the discrete degree of data distribution, and the smaller the variance is, the more data is concentrated near the average value; the larger the variance, the more scattered the description data.
Where Var_D represents the variance of the amount of mist deposited on the ground, W max Is the upper limit of the spray width of the nozzle, D9x, L) is the deposition amount of mist drops at one point on the spray zone,is the average value of fog drop deposition on the ground strip, and L represents the plant protection route interval. The calculation formula of the deposition amount of mist drops at one point on the spraying belt is expressed as follows:
where Q is the total amount of mist droplets sprayed by the unmanned aerial vehicle, n is the course number, n=0 represents the course passing through the point x, n= -1 represents the left adjacent course, n=1 represents the right adjacent course, and so on. f (x) represents the distribution density of the mist droplets sprayed by the unmanned aerial vehicle on the ground spray strip.
When n is sufficiently large, f (x+nL) tends to be 0, and the spray width of each nozzle is affected by the pressure and the height, typically having an upper limit W max . A reasonable range can therefore be chosen to approximate the calculation where we take n=1, i.e. the amount of spray deposition at the point under each course is only affected by the two adjacent courses. The calculation formula of the deposition amount of the mist drops at one point on the spraying belt can be simplified as follows:
D(x,L)＝Q·[f(x)+f(x-L)+f(x+L)]
the calculation formula of the average value of the deposition of the fog drops on the ground strip is as follows:
the above is the final form of the variance of the amount of deposited droplets on the ground, which can be seen as a function of the course interval L. Using this formula, the variance at different values of L can be calculated.
The route interval calculating method comprises the following steps:
based on the formula, an optimization algorithm is designed, and an optimal route interval L is calculated in a reasonable range so as to minimize variance and ensure that the deposition amount of each position on the ground is equal as much as possible.
A grid discretization algorithm is proposed to calculate the optimal interval with minimum variance. The specific flow is as follows
S1: dividing the area on the ground into a plurality of small rectangles, wherein the area of each small rectangle is delta S, and the abscissa of the center point of each small rectangle is x i ；
S2: the deposition amount of the mist drop on each small rectangle is approximately equal to the center pointMist deposition, i.e. D (x) i ,L)；
S3: approximating the sum of the deposition amounts of droplets on all small rectangles on the ground to the sum of the deposition amounts of droplets on all points on the ground, i.e
S4: the sum of the areas of all small rectangles on the ground is approximated to the number of all points on the ground, i.e
When Δs goes to 0, these approximations become equations.
Therefore, a discrete formula can be obtained, and the corresponding variance formula for determining the precipitation amount of the mist drops on the ground after treatment is expressed as follows:
where N is the number of samples on the ground, D (x i ,y i ) After the deposition amount of the ith point is used for determining the distribution of the spray nozzles of the medicine spraying component, uniformity of different plant protection route intervals is obtained, and further the plant protection route interval with most uniform ground fog drop distribution is determined.
After the distribution of the nozzles is determined, the uniformity at different route intervals can be calculated by using the algorithm, and the route interval with the best uniformity can be found. And planning a plant protection route by using a cow cultivation reciprocating operation method according to the interval.
In the plant protection operation process, unmanned aerial vehicle carries out autonomous flight, does not need manual control. The autonomous flight operation principle of the unmanned aerial vehicle is as follows.
As shown in fig. 7, the unmanned aerial vehicle needs to realize autonomous flight, and needs to know not only its own state but also the surrounding environment. In the block diagram, the state estimation refers to estimating the real-time attitude, speed and position of the unmanned aerial vehicle by using the measurement data of the onboard accelerometer, gyroscope, magnetometer, barometer, GNSS and other sensors. The environmental perception means that the unmanned aerial vehicle obtains surrounding environment information by using a perception module such as carrying vision, radar, ultrasonic wave and the like. After the self state and the surrounding environment of the unmanned aerial vehicle are known, a safe flight route can be planned. The motion control part controls the power output of the unmanned aerial vehicle to enable the unmanned aerial vehicle to fly at a specified speed according to a planned route.
More specifically, in this embodiment, the wheelbase of the X-type quad-rotor unmanned helicopter is 1000mm. The power system adopts a 6215KV180 brushless motor, and the rotor wing is a foldable blade with a 24-inch-diameter screw pitch 70. The battery used was a 12s16000mAh lithium polymer battery. The pesticide spraying system used a 5L pesticide tank, a brushless water pump, and a fan nozzle. The inspection system uses 500 ten thousand pixel industrial cameras. The onboard computer uses nvidia jetson orin nano. The unmanned aerial vehicle uses a positioning mode of GNSS+RTK. The flight control computer uses Lei Xun v6x.
The foregoing describes in detail preferred embodiments of the present invention. It should be understood that numerous modifications and variations can be made in accordance with the concepts of the invention by one of ordinary skill in the art without undue burden. Therefore, all technical solutions which can be obtained by logic analysis, reasoning or limited experiments based on the prior art by the person skilled in the art according to the inventive concept shall be within the scope of protection defined by the claims.
Claims (10)
1. A many rotor unmanned aerial vehicle of accurate plant protection system for warmhouse booth, a serial communication port, including task load module, motion control module, perception keep away barrier module and task management module, task load module includes that the medicine sprays part and vision inspection part, the vision inspection part is used for acquireing external image information, the perception keeps away barrier module and is used for acquireing the barrier information on the unmanned aerial vehicle navigation route, task management module carries out unmanned aerial vehicle navigation route's planning and control according to external image information, barrier information and the circumstances that the medicine sprayed the part, motion control module is used for controlling the flight of drive unmanned aerial vehicle and the spraying action of medicine spraying part.
2. The precise plant protection multi-rotor unmanned aerial vehicle system for a greenhouse of claim 1, wherein the motion control module comprises a flight control computer, and a gyroscope, an accelerometer, a magnetometer and a barometer connected with the flight control computer for controlling the operation of a unmanned aerial vehicle power system and a mission load system.
3. A control method of a precise plant protection multi-rotor unmanned aerial vehicle system for a greenhouse based on any one of claims 1-2, comprising the following steps:
acquiring an area to be inspected, moving the unmanned aerial vehicle to the area to be inspected, acquiring the flight height and the horizontal width of image acquisition of the unmanned aerial vehicle, planning an inspection route of the unmanned aerial vehicle, and enabling the unmanned aerial vehicle to fly autonomously according to the planned inspection route to acquire the image of the area to be inspected;
judging whether plant protection operation is needed according to the acquired image of the area to be inspected, and determining the area to be plant protected when plant protection is needed;
and acquiring the spraying quantity of the unit area of the area to be protected and the unmanned aerial vehicle, planning a plant protection route of the unmanned aerial vehicle according to the distribution characteristic of the nozzles, and enabling the unmanned aerial vehicle to fly autonomously according to the planned plant protection route to perform plant protection operation.
4. The control method of the precise plant protection multi-rotor unmanned aerial vehicle system for the greenhouse according to claim 3, wherein in the process of planning a patrol route, the patrol route interval is determined based on the coverage width of an acquired image of a visual patrol component in the horizontal direction, and the patrol route interval is smaller than the coverage width of the image in the horizontal direction, so that the planned patrol route is obtained based on a cow tillage reciprocating method.
5. The method for controlling a precise plant protection multi-rotor unmanned aerial vehicle system for a greenhouse according to claim 3, wherein the specific steps of unmanned aerial vehicle plant protection route planning are as follows:
acquiring the to-be-protected area and the droplet distribution characteristics of the pesticide spraying part at the corresponding flight height of the unmanned aerial vehicle, and determining the plant protection route interval of the unmanned aerial vehicle according to the to-be-protected area and the droplet distribution characteristics of the pesticide spraying part; the plant protection route interval is the horizontal distance between two adjacent routes of the unmanned aerial vehicle; and obtaining a planned plant protection route according to the plant protection route interval in the region to be protected based on a cow cultivation reciprocating method.
6. The method for controlling a precise plant protection multi-rotor unmanned aerial vehicle system for a greenhouse according to claim 5, wherein the plant protection route interval directly influences the overlapping ratio of the fog drops, wherein the overlapping ratio of the fog drops on two routes is defined as the ratio of the overlapping area of the fog drops on the ground on two routes to the area of the fog drops on the ground on a single route; and (3) determining the optimal plant protection route interval by acquiring the variance of the precipitation amount of the fog drops at each point on the ground and taking the minimum value of the variance as a target in a constraint range.
7. The method for controlling a precise plant protection multi-rotor unmanned aerial vehicle system for a greenhouse according to claim 6, wherein the variance formula of the precipitation amount of the mist drops on the ground is expressed as follows:
where Var_D represents the variance of the amount of mist deposited on the ground, W max Is the upper limit of the spray width of the nozzle, D (x, L) is the deposition amount of mist drops at one point on the spray zone,is the average value of fog drop deposition on the ground strip, and L represents the plant protection route interval.
8. The method for controlling a precise plant protection multi-rotor unmanned aerial vehicle system for a greenhouse according to claim 7, wherein the method for determining the optimal plant protection route interval under the condition of minimum variance through a grid discretization algorithm comprises the following specific steps:
dividing the area on the ground into a plurality of small rectangles, wherein the area of each small rectangle is delta s, and the abscissa of the center point of each small rectangle is x i ；
The amount of droplet deposition on each small rectangle was approximated to that of the center point, i.e., D (x) i ,L)；
Approximating the sum of the deposition amounts of droplets on all small rectangles on the ground to the sum of the deposition amounts of droplets on all points on the ground, i.e
The sum of the areas of all small rectangles on the ground is approximated to the number of all points on the ground, i.e
The variance formula of the corresponding precipitation amount of the mist drops on the ground after the determination treatment is expressed as follows:
in the method, in the process of the invention,after the distribution of the spray nozzles of the medicine spraying component is determined, uniformity under different plant protection route intervals is obtained, and further the plant protection route interval with the most uniform ground fog drop distribution is determined.
9. The method for controlling a precise plant protection multi-rotor unmanned aerial vehicle system for a greenhouse according to claim 3, wherein the autonomous flight process of the unmanned aerial vehicle comprises the following steps:
the task management module acquires the motion state of the unmanned aerial vehicle through the motion control module, and acquires surrounding environment information through the perception obstacle avoidance module;
according to the motion state of the unmanned aerial vehicle and surrounding environment information, path planning is carried out to obtain a safe navigation route;
and driving the unmanned aerial vehicle to navigate according to the safe navigation route through the motion control module.
10. The method for controlling a precise plant protection multi-rotor unmanned aerial vehicle system for a greenhouse according to claim 9, wherein the motion control module comprises an accelerometer, a gyroscope, a magnetometer, a barometer and a GNSS, and the acquired motion state comprises a posture, a speed and a position of the unmanned aerial vehicle.
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