CN110427032A - A kind of agricultural data acquisition method and system based on flow model data collection point - Google Patents
A kind of agricultural data acquisition method and system based on flow model data collection point Download PDFInfo
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0217—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with energy consumption, time reduction or distance reduction criteria
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0219—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory ensuring the processing of the whole working surface
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
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Abstract
The invention discloses a kind of agricultural data acquisition method and system based on flow model data collection point, it is related to agricultural data acquisition technical field, the flow model data collection point set in target farmland is obtained first, then the location information and orientation information of agricultural robot are obtained by laser positioning and image procossing, furthermore it is based on agricultural robot information and target farmland flow model data collection point, obtain the most short walking path of agricultural robot, finally control agricultural robot traverses each data collection point according to determining most short walking path to acquire the agricultural data in target farmland.The present invention realizes that efficiently, accurately the farm field data based on agricultural robot platform acquires in terms of agricultural robot system configuration and flow model data collection point determine two, to improve the reliability and precision of agricultural data acquisition.
Description
Technical field
The present invention relates to agricultural data acquisition technical fields, more particularly to a kind of agriculture based on flow model data collection point
Industry collecting method and system.
Background technique
Robot is the automation for integrating the multidisciplinary advanced technology such as machinery, electronics, control, sensing, artificial intelligence
Equipment.After being born from Robot industry in 1956, developed by nearly 60 years, robot be widely used in equipment manufacturing,
The high technology industries such as new material, biological medicine, wisdom new energy.Robot and artificial intelligence technology, advanced manufacturing technology and movement
The fusion development of Internet technology has pushed the change of human society life mode.Agricultural robot is that robot is raw in agricultural
Utilization in production is that crop species or ring can be felt and be adapted to one kind, to adapt to various operations, by distinct program software control
Border variation, have the artificial intelligence such as detection (such as vision) and calculation it is of new generation nobody be automatically brought into operation machinery.Agricultural robot is
One of present development trend, with the development of science and technology, application of the new technology in agricultural production of today is increasingly
Extensively.The development of mechanization of agriculture has become the mark of a national development level, and agricultural robot technology is even more to embody
A national scientific and technological strength out.
Data analysis has an application in many fields, but not extensive in the application of agriculture field, but agricultural data is answered
It is very huge with interests and there are many potential benefit.The plantation activity of agriculture practitioner is typically all by rule of thumb, by feel.But
Experience does not have stability, cannot guiding agricultural production activity well.The acquisition of agricultural data at present will rely on profession
Sensor device, such as humidity and temp probe, wind speed wind direction sensor, soil moisture sensor, plant growth measuring instrument are firmly
Part, the multinomial data such as real-time collecting and monitoring soil moisture in farmland, temperature, air humidity, gas concentration lwevel, is sent to
Central controller completes the operations such as farmland temperature promotion or sprinkling irrigation by wireless greenhouse automatic control control system and drip irrigation system etc..
Accurate support is provided for pest and disease damage prevention by the data analysis of profession, realizes increasing both production and income.A wide range of farmland is laid with all kinds of hard
There are two drawbacks for part sensor: first is that the expense of large area laying sensor and equipment loss are serious；Second is that fixed point is adopted
The farm field data of collection can not reflect the time of day in target farmland.
Summary of the invention
The present invention is directed to provide feasible solution for the acquisition of modern agriculture data, provide a kind of based on flow model number
According to the agricultural data acquisition method and system of collection point, to improve the reliability and precision of agricultural data acquisition.
To achieve the above object, the present invention provides following schemes:
A kind of agricultural data acquisition method based on flow model data collection point, comprising:
Obtain target agricultural land information；The target agricultural land information includes the dimension information in target farmland, planting area distribution
Information and farmland traveling road distributed intelligence；The dimension information includes the length value, width value and area in target farmland
Value；
According to the target agricultural land information and the acquisition range of individual data collection point, each data collection point is determined
Distributed intelligence；Wherein, the acquisition area of each data collection point and with the overlapping collection surface of each data collection point
The difference of product sum is not less than preset area, and the number of the data collection point determined is minimum；
Based on laser positioning airmanship, the initial position message of agricultural robot is determined；
According to the target agricultural land information, the distributed intelligence of each data collection point and the agricultural robot
Initial position message determines the most short walking path of agricultural robot using depth-first traversal algorithm；
It controls agricultural robot and traverses each data collection point according to determining most short walking path to acquire target
The agricultural data in farmland.
Optionally, described according to the target agricultural land information and the acquisition range of individual data collection point, it determines each
The distributed intelligence of data collection point, specifically includes:
According to the target agricultural land information, the acquisition range and constraint condition of individual data collection point, every number is determined
According to the distributed intelligence of collection point；Wherein, the constraint condition is Indicate that n data are adopted
Collect the acquisition area and S of pointiIndicate the acquisition area of i-th of data collection point；S' indicates that the overlapping of n data collection point is adopted
Collect area and；95%S indicates preset area, and S indicates the area value in target farmland.
Optionally, described to be based on laser positioning airmanship, determine the initial position message of agricultural robot, it is specific to wrap
It includes:
Laser receiver is built on the agricultural robot, installation swashs respectively in the two fixing points in target farmland
Optical transmitting set determines the initial position message of agricultural robot then according to laser positioning principle of triangulation.
Optionally, described according to the target agricultural land information, the distributed intelligence of each data collection point and described
The initial position message of agricultural robot determines the most short walking path of agricultural robot using depth-first traversal algorithm, tool
Body includes:
Based on the target agricultural land information, rasterizing processing is carried out to the target farmland, determines the grid in target farmland
Matrix；
Each grid in the grid matrix is numbered using decimal coded mode, obtains encoder matrix；Its
In, the Lattice encoding zero setting of the planting area in the target farmland；
According to the initial of the encoder matrix, the distributed intelligence of each data collection point and the agricultural robot
Location information determines the most short walking path of agricultural robot using depth-first traversal algorithm.
Optionally, control agricultural robot according to determining most short walking path traverse each data collection point with
Before the agricultural data for acquiring target farmland, further includes: be based on image Segmentation Technology, adjust the positive direction of agricultural robot.
Optionally, described to be based on image Segmentation Technology, the positive direction of agricultural robot is adjusted, is specifically included:
Obtain the farmland image of agricultural robot forward travel；
Edge Gradient Feature is carried out to the farmland image, segmentation has the planting area of green plants and the farmland row of brown
Access road；
According to the farmland traveling road, the positive direction of agricultural robot is adjusted.
A kind of agricultural data acquisition system based on flow model data collection point, comprising:
Target agricultural land information obtains module, for obtaining target agricultural land information；The target agricultural land information includes target agriculture
Dimension information, planting area distributed intelligence and the farmland traveling road distributed intelligence in field；The dimension information includes target agriculture
Length value, width value and the area value in field；
Data collection point distributed intelligence determining module, for according to the target agricultural land information and individual data collection point
Acquisition range, determine the distributed intelligence of each data collection point；Wherein, the acquisition area of each data collection point and with
The overlapping of each data collection point acquires the difference of area sum not less than preset area, and the data collection point determined
Number is minimum；
Agricultural robot initial position message determining module determines farming machine for being based on laser positioning airmanship
The initial position message of people；
Most short walking path determining module, for point according to the target agricultural land information, each data collection point
The initial position message of cloth information and the agricultural robot determines agricultural robot using depth-first traversal algorithm
Most short walking path；
Target farmland agricultural data acquisition module is traversed for controlling agricultural robot according to determining most short walking path
Each data collection point is to acquire the agricultural data in target farmland.
Optionally, the data collection point distributed intelligence determining module, specifically includes:
Data collection point distributed intelligence determination unit, for according to the target agricultural land information, individual data collection point
Acquisition range and constraint condition determine the distributed intelligence of each data collection point；Wherein, the constraint condition is Indicate the acquisition area and S of n data collection pointiIndicate i-th of data collection point
Acquire area；S' indicate the overlapping acquisition area of n data collection point with；95%S indicates preset area, and S indicates target farmland
Area value.
Optionally, the most short walking path determining module, specifically includes:
Grid matrix computing unit carries out at rasterizing the target farmland for being based on the target agricultural land information
Reason, determines the grid matrix in target farmland；
Encoder matrix computing unit, for being carried out using decimal coded mode to each grid in the grid matrix
Number, obtains encoder matrix；Wherein, the Lattice encoding zero setting of the planting area in the target farmland；
Most short walking path determination unit, for being believed according to the distribution of the encoder matrix, each data collection point
The initial position message of breath and the agricultural robot determines the most short of agricultural robot using depth-first traversal algorithm
Walking path.
Optionally, further includes: agricultural robot forward direction adjusts agriculture for being based on image Segmentation Technology towards adjustment module
The positive direction of industry robot.
The specific embodiment provided according to the present invention, the invention discloses following technical effects:
The present invention provides a kind of agricultural data acquisition method and system based on flow model data collection point.By to agriculture
The system of industry robot is arranged and the determination of farmland flow model data collection point, realizes in terms of two efficiently, accurately, reliably
Based on agricultural robot platform farm field data acquisition.
Detailed description of the invention
It in order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will be to institute in embodiment
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without any creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is the flow diagram of agricultural data acquisition method of the embodiment of the present invention based on flow model data collection point；
Fig. 2 is that flow model of embodiment of the present invention data collection point determines schematic diagram and work route figure；
Fig. 3 is that agricultural robot of embodiment of the present invention position acquisition and adjustment are schemed；
Fig. 4 is target of embodiment of the present invention farmland grid region figure；
Fig. 5 is target of embodiment of the present invention farmland grid planting area figure；
Fig. 6 is the structural schematic diagram of agricultural data acquisition system of the embodiment of the present invention based on flow model data collection point.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The object of the present invention is to provide a kind of agricultural data acquisition method and system based on flow model data collection point, with
Improve the reliability and precision of agricultural data acquisition.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, with reference to the accompanying drawing and specific real
Applying mode, the present invention is described in further detail.
As shown in Figure 1, a kind of agricultural data acquisition method based on flow model data collection point provided in this embodiment, packet
It includes:
Step 101: obtaining target agricultural land information；The target agricultural land information includes the dimension information in target farmland, plantation
Area distribution information and farmland traveling road distributed intelligence；The dimension information includes the length value in target farmland, width value
And area value.Target farmland as shown in Figure 2, it is long X meters of target farmland, Y meters wide, along long side road M item, along broadside road
N item；The area value in target farmland is denoted as S.
Step 102: according to the target agricultural land information and the acquisition range of individual data collection point, determining each data
The distributed intelligence of collection point；Wherein, the acquisition area of each data collection point and the weight with each data collection point
The difference of folded acquisition area sum is not less than preset area, and the number of the data collection point determined is minimum.
Step 103: being based on laser positioning airmanship, determine the initial position message of agricultural robot.
Step 104: according to the distributed intelligence and the agricultural of the target agricultural land information, each data collection point
The initial position message of robot determines the most short walking path of agricultural robot using depth-first traversal algorithm.
Step 105: control agricultural robot according to determining most short walking path traverse each data collection point with
Acquire the agricultural data in target farmland.
Wherein, step 102 specifically includes:
According to the target agricultural land information, the acquisition range of individual data collection point and the constraint condition of satisfaction, determine
The distributed intelligence of each data collection point.
Wherein, the set of data collection point is denoted as A；Data collection point is denoted as A1、A2、A3......An；Data collection point
Effectively acquisition area is denoted as S1、S2、S3......Sn；The overlapping of each data collection point acquires area and is denoted as S'.According to investigation with
The agricultural land information effective range of individual data collection point known to experiment is the border circular areas of diameter 4M；The data in target farmland region
Collection point needs to meet following constraint condition:
Indicate the acquisition area and S of n data collection pointiIndicate i-th of data
The acquisition area of collection point；S' indicate the overlapping acquisition area of n data collection point with；95%S indicates preset area, and S is indicated
The area in target farmland.
Different croplands size and road obtain different data collection point set；The same available multiple groups in farmland are different
Data collection point set, here, needing to choose comprising the least data collection point set of data collection point to improve farming machine
Task efficiency.
Step 103 specifically includes:
As shown in figure 3, laser receiver is built on the agricultural robot, in the two fixing points in target farmland
Laser emitter is installed respectively, then according to laser positioning principle of triangulation, determines the initial position message of agricultural robot.
Step 104 specifically includes:
For the ease of storing the information in target farm environment region, target farmland is subjected to rasterizing processing, target first
Long X meters of farmland, wide Y meters of target farmland, along long side road M item, along broadside road N item, the fuselage diameter of agricultural robot
It is 0.5 meter, then can is the grid of [(X/0.5+1) * (Y/0.5+1)] as shown in Figure 4 by rectangular target farmland region rasterizing
Matrix.Also determine agricultural robot and data collection point in the location status of target farmland grid region in the process.
Each grid in the grid matrix is numbered using decimal coded mode, obtains encoder matrix；Its
In, as shown in figure 5, then making the region Lattice encoding zero setting if it is planting area, coding method is constant.
According to the initial of the encoder matrix, the distributed intelligence of each data collection point and the agricultural robot
Location information determines the most short walking path of agricultural robot using depth-first traversal algorithm.Specifically: based on agriculture machine
Device people and data collection point target farmland grid region location status, using depth-first traversal algorithm from agricultural robot
Initial position set out and traverse each data collection point, establish overall situation Open, Closed list and be used to store each data collection point
The information of data collection point is acquired.
The mobile cost between adjacent data collection point is obtained using Man Hadu distance:
D=| xi-xj|+|yi-yj|；Wherein, (xi,yi),(xj,yj) it is respectively that agricultural robot position coordinates and data are adopted
Set point location coordinate obtains the most short walking path that agricultural robot carries out data Collecting operation.
Before executing step 105, this method further include: be based on image Segmentation Technology, adjust the forward direction of agricultural robot
Direction.Specifically: obtain the farmland image of agricultural robot forward travel；Edge Gradient Feature is carried out to the farmland image,
Segmentation has the planting area of green plants and the farmland traveling road of brown；According to the farmland traveling road, agriculture is determined with this
Industry robot towards posture, and then adjust the positive direction of agricultural robot, i.e., crawler belt moved by control agricultural robot
The positive direction of pedestal adjustment agricultural robot.
Step 105 specifically includes:
Initial position message and most short walking path based on agricultural robot, first control agricultural robot move bottom
Seat is advanced forward according to the most short walking path of planning；In road inflection point, agricultural robot movement crawler belt base is carried out
Differential control completes go to action, then proceedes to advance.Movement crawler belt base stops after agricultural robot reaches data collection point
Only, controllor for step-by-step motor sends control signal, controls agricultural robot mechanical arm stepper motor, fills data acquisition with transmitting-receiving
It sets and moves to the data collection that farm field data collection point is completed in target position.
Secondly, updating the job state of agricultural robot；Agricultural robot determines own location information by laser positioning.
It establishes overall situation Open, Closed list to be used to store each data collection point and acquired the information of data collection point, when having acquired
After one data collection point, overall situation Open, Closed list is updated, determines the state space of agricultural robot, is carried out next
The farm field data Collecting operation of data collection point.
In the present embodiment, agricultural robot also carries data acquisition and R-T unit in addition to building laser receiver；
Data acquisition refers to R-T unit for acquiring target farm field data, sending target farm field data and receiving central control board
It enables；The target farm field data includes soil moisture, nitrogen content, phosphorus content, potassium content, permeability, the fluffy degree, gas in farmland
The multinomial data such as temperature, air humidity, gas concentration lwevel.
Embodiment two
As shown in fig. 6, present embodiments providing a kind of agricultural data acquisition system based on flow model data collection point, wrap
It includes:
Target agricultural land information obtains module 100, for obtaining target agricultural land information；The target agricultural land information includes target
Dimension information, planting area distributed intelligence and the farmland traveling road distributed intelligence in farmland；The dimension information includes target
Length value, width value and the area value in farmland.
Data collection point distributed intelligence determining module 200, for being adopted according to the target agricultural land information and individual data
The acquisition range for collecting point, determines the distributed intelligence of each data collection point；Wherein, the acquisition area of each data collection point
With with each data collection point it is Chong Die acquisition area and difference be not less than preset area, and determine the data acquisition
The number of point is minimum.
Agricultural robot initial position message determining module 300 determines agricultural machine for being based on laser positioning airmanship
The initial position message of device people.
Most short walking path determining module 400, for according to the target agricultural land information, each data collection point
The initial position message of distributed intelligence and the agricultural robot determines agricultural robot using depth-first traversal algorithm
Most short walking path.
Target farmland agricultural data acquisition module 500, for controlling agricultural robot according to determining most short walking path
Each data collection point is traversed to acquire the agricultural data in target farmland.
The data collection point distributed intelligence determining module 200, specifically includes:
Data collection point distributed intelligence determination unit, for according to the target agricultural land information, individual data collection point
Acquisition range and constraint condition determine the distributed intelligence of each data collection point；Wherein, the constraint condition is Indicate the acquisition area and S of n data collection pointiIndicate i-th of data collection point
Acquire area；S' indicate the overlapping acquisition area of n data collection point with；95%S indicates preset area, and S indicates target farmland
Area value.
The most short walking path determining module 400, specifically includes:
Grid matrix computing unit carries out at rasterizing the target farmland for being based on the target agricultural land information
Reason, determines the grid matrix in target farmland.
Encoder matrix computing unit, for being carried out using decimal coded mode to each grid in the grid matrix
Number, obtains encoder matrix；Wherein, the Lattice encoding zero setting of the planting area in the target farmland.
Most short walking path determination unit, for being believed according to the distribution of the encoder matrix, each data collection point
The initial position message of breath and the agricultural robot determines the most short of agricultural robot using depth-first traversal algorithm
Walking path.
In addition, the system further include: agricultural robot forward direction is adjusted towards adjustment module for being based on image Segmentation Technology
The positive direction of whole agricultural robot.Specifically: specifically: obtain the farmland image of agricultural robot forward travel；To described
Farmland image carries out Edge Gradient Feature, and segmentation has the planting area of green plants and the farmland traveling road of brown；According to institute
State farmland traveling road, with this determine agricultural robot towards posture, and then adjust the positive direction of agricultural robot, i.e., it is logical
Cross the positive direction of control agricultural robot movement crawler belt base adjustment agricultural robot.
The present invention using the dimension data in one piece of target farmland and structured data as analysis foundation, obtains farm field data first
Collection point；Wherein, 95% of the Limit of J-validity of farm field data collection point more than or equal to farmland area, and data collection point
Number is at least to improve operating efficiency；By laser positioning and image segmentation obtain agricultural robot and farmland relative position and
Direction, and be adjusted correspondingly；Agricultural robot operating path is planned according to data collection point and target agricultural land information, is used
Depth-first traversal algorithm obtains most short walking path；Agricultural robot is travelled according to most short walking path to each farm field data
Collection point, reaches target data collection point, and the data acquisition device of agricultural robot carries out farm field data Collecting operation, farmland number
Central control board, data acquisition process are sent to according to the data transmitter-receiver set by agricultural robot.Therefore, the present invention mentions
The agricultural data acquisition method and system based on flow model data collection point supplied, it is multinomial to farmland using agricultural robot platform
Data carry out the acquisition of on-fixed data collection point, so that the reliability and validity of farm field data are improved, to guarantee agriculture number
According to analysis result to the practicability and value of rural activity.
Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with other
The difference of embodiment, the same or similar parts in each embodiment may refer to each other.For system disclosed in embodiment
For, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is said referring to method part
It is bright.
Used herein a specific example illustrates the principle and implementation of the invention, and above embodiments are said
It is bright to be merely used to help understand method and its core concept of the invention；At the same time, for those skilled in the art, foundation
Thought of the invention, there will be changes in the specific implementation manner and application range.In conclusion the content of the present specification is not
It is interpreted as limitation of the present invention.
Claims (10)
1. a kind of agricultural data acquisition method based on flow model data collection point, which is characterized in that the agricultural data acquisition
Method, comprising:
Obtain target agricultural land information；The target agricultural land information includes the dimension information in target farmland, planting area distributed intelligence
And farmland traveling road distributed intelligence；The dimension information includes the length value, width value and area value in target farmland；
According to the target agricultural land information and the acquisition range of individual data collection point, the distribution of each data collection point is determined
Information；Wherein, the acquisition area of each data collection point and acquisition area overlapping with each data collection point and
Difference be not less than preset area, and determine the data collection point number it is minimum；
Based on laser positioning airmanship, the initial position message of agricultural robot is determined；
According to the initial of the target agricultural land information, the distributed intelligence of each data collection point and the agricultural robot
Location information determines the most short walking path of agricultural robot using depth-first traversal algorithm；
It controls agricultural robot and traverses each data collection point according to determining most short walking path to acquire target farmland
Agricultural data.
2. agricultural data acquisition method according to claim 1, which is characterized in that described according to the target agricultural land information
And the acquisition range of individual data collection point, it determines the distributed intelligence of each data collection point, specifically includes:
According to the target agricultural land information, the acquisition range and constraint condition of individual data collection point, determine that each data are adopted
Collect the distributed intelligence of point；Wherein, the constraint condition is Indicate n data collection point
Acquire area and SiIndicate the acquisition area of i-th of data collection point；S' indicates that the overlapping of n data collection point acquires area
With；95%S indicates preset area, and S indicates the area value in target farmland.
3. agricultural data acquisition method according to claim 1, which is characterized in that described based on laser positioning navigation skill
Art determines the initial position message of agricultural robot, specifically includes:
Laser receiver is built on the agricultural robot, laser hair is installed respectively in the two fixing points in target farmland
Emitter determines the initial position message of agricultural robot then according to laser positioning principle of triangulation.
4. agricultural data acquisition method according to claim 1, which is characterized in that described to be believed according to the target farmland
The initial position message of breath, the distributed intelligence of each data collection point and the agricultural robot, using depth-first
Ergodic algorithm determines the most short walking path of agricultural robot, specifically includes:
Based on the target agricultural land information, rasterizing processing is carried out to the target farmland, determines the grid matrix in target farmland；
Each grid in the grid matrix is numbered using decimal coded mode, obtains encoder matrix；Wherein, institute
State the Lattice encoding zero setting of the planting area in target farmland；
According to the initial position of the encoder matrix, the distributed intelligence of each data collection point and the agricultural robot
Information determines the most short walking path of agricultural robot using depth-first traversal algorithm.
5. agricultural data acquisition method according to claim 1, which is characterized in that in control agricultural robot according to determination
Most short walking path traverse agricultural data of each data collection point to acquire target farmland before, further includes: be based on
Image Segmentation Technology adjusts the positive direction of agricultural robot.
6. agricultural data acquisition method according to claim 5, which is characterized in that it is described to be based on image Segmentation Technology, it adjusts
The positive direction of whole agricultural robot, specifically includes:
Obtain the farmland image of agricultural robot forward travel；
Edge Gradient Feature is carried out to the farmland image, segmentation has the planting area of green plants and the farmland traveling road of brown
Road；
According to the farmland traveling road, the positive direction of agricultural robot is adjusted.
7. a kind of agricultural data acquisition system based on flow model data collection point, which is characterized in that the agricultural data acquisition
System, comprising:
Target agricultural land information obtains module, for obtaining target agricultural land information；The target agricultural land information includes target farmland
Dimension information, planting area distributed intelligence and farmland traveling road distributed intelligence；The dimension information includes target farmland
Length value, width value and area value；
Data collection point distributed intelligence determining module, for adopting according to the target agricultural land information and individual data collection point
Collect range, determines the distributed intelligence of each data collection point；Wherein, the acquisition area of each data collection point and with it is each
The difference of the overlapping acquisition area sum of the data collection point is not less than preset area, and the number of the data collection point determined
At least；
Agricultural robot initial position message determining module determines agricultural robot for being based on laser positioning airmanship
Initial position message；
Most short walking path determining module, for being believed according to the distribution of the target agricultural land information, each data collection point
The initial position message of breath and the agricultural robot determines the most short of agricultural robot using depth-first traversal algorithm
Walking path；
Target farmland agricultural data acquisition module traverses each for controlling agricultural robot according to determining most short walking path
The data collection point is to acquire the agricultural data in target farmland.
8. agricultural data acquisition system according to claim 7, which is characterized in that the data collection point distributed intelligence is true
Cover half block, specifically includes:
Data collection point distributed intelligence determination unit, for the acquisition according to the target agricultural land information, individual data collection point
Range and constraint condition determine the distributed intelligence of each data collection point；Wherein, the constraint condition is Indicate the acquisition area and S of n data collection pointiIndicate i-th of data collection point
Acquire area；S' indicate the overlapping acquisition area of n data collection point with；95%S indicates preset area, and S indicates target farmland
Area value.
9. agricultural data acquisition system according to claim 7, which is characterized in that the most short walking path determines mould
Block specifically includes:
Grid matrix computing unit carries out rasterizing processing to the target farmland, really for being based on the target agricultural land information
Set the goal the grid matrix in farmland；
Encoder matrix computing unit, for being compiled using decimal coded mode to each grid in the grid matrix
Number, obtain encoder matrix；Wherein, the Lattice encoding zero setting of the planting area in the target farmland；
Most short walking path determination unit, for according to the distributed intelligence of the encoder matrix, each data collection point with
And the initial position message of the agricultural robot determines the most short walking of agricultural robot using depth-first traversal algorithm
Path.
10. agricultural data acquisition system according to claim 7, which is characterized in that further include: agricultural robot forward direction court
The positive direction of agricultural robot is adjusted for being based on image Segmentation Technology to adjustment module.
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