CN108804854B - Tree body structure parameter estimation method and system for mechanical fruit tree pruning - Google Patents

Abstract

The invention discloses a method and system for estimating tree structure parameters of mechanical pruning of fruit trees, including preprocessing; extracting the trunk axis, and generating a tree body reference axis; detecting the contour points of the tree crown; The degree of dispersion of the reference axis; the system adopts the scanning module of the tree structure parameter estimation method of fruit tree mechanical pruning for implementation, including the scanning module, which is used to transmit and receive the first signal, and the received first signal The signal is delivered to the control module through the data transmission module. The present invention uses the trunk as a reference axis to study the degree of dispersion of key points on the edge of the canopy to achieve detailed estimation of the tree structure parameters and provide reference information for the automatic adjustment of the position of the tool for mechanical pruning, thereby solving the problem of surrounding the canopy. The fitting surface of the layer has a large deviation in the estimation of the tree structure, and it is also conducive to the efficiency of mechanical pruning, saving time and effort, saving resources, and meeting the needs of use.

Description

Method and system for estimating tree structure parameters of mechanical pruning of fruit trees

technical field

The invention relates to the technical field of mechanized application of orchard management, in particular to a tree structure parameter estimation method and system for fruit tree mechanical pruning.

Background technique

my country is the world's largest apple producer, accounting for more than half of the world's apple production. The vegetative growth and reproductive growth of apple trees are interrelated and affect each other, which will ultimately affect the yield and quality. In order to control the vitality of fruit trees, pruning has become the most important task during the dormant period. Its purpose is to obtain an ideal canopy structure by partially thinning and cutting some organs of the plant to improve the utilization rate of light energy. Although this operation is not as labor-intensive as harvesting, and timing is not important, it is time-consuming for growers. Mechanized pruning is an effective way to solve the above problems.

The cultivation mode of modern apple orchard is developing towards simpler, quicker to form, more accessible and more efficient. Among them, the high-spindle tree body is the preferred tree shape in the intensive high-efficiency cultivation mode of short stock currently promoted, and it is also the tree shape generally adopted by advanced countries in apple production. It only needs to cultivate a strong and straight middle trunk, and its tree-shaped skeleton cultivation has been completed; and because the crown of the fruit tree is small, the length of the main branch is less than or close to the length of a human arm, and all the orchards can be completed by standing between the rows operation, creating conditions for the realization of orchard mechanization.

In a typical mechanical pruning operation, the cutter is mounted on a tractor and the operator drives as straight as possible; however, the canopy profile often changes along the rows, and in order to ensure pruning continuity, pruning is done according to the Crown profile adjustment cutter. As the first step in automatic pruning, the structural parameters of fruit trees need to be estimated by a machine vision system.

In the past, various related technologies have been used to perceive tree structures, such as stereo vision, laser scanners and depth cameras. One of the studies, conducted in a vineyard, uses a sensor system that combines vision and laser scanning principles mounted on a traveling vehicle to scan the grape canopy and provide a dense map of canopy performance. However, such systems are expensive and complex for field data acquisition. Nielsen et al. explored a way of stereo vision to reconstruct peach tree structure for automatic flower thinning. However, the technique needs to further reduce the complexity of stereo matching and improve the robustness of the algorithm in the outdoor orchard environment. In recent years, depth cameras have been applied in 3D reconstruction in the agricultural field by using background light suppression technology and time-of-flight based ranging principle. In a commercial orchard, the camera was used to obtain depth images of tall-spindle apple trees, a method for automatic identification of branches was developed, and an intelligent pruning system was explored; however, low-resolution images lose some important details and cannot It provides reference information for the automatic adjustment of the tool position of mechanical pruning, which is not conducive to the efficiency of mechanical pruning, consumes time and labor, and does not meet the needs of use.

Contents of the invention

The purpose of this section is to outline some aspects of embodiments of the invention and briefly describe some preferred embodiments. Some simplifications or omissions may be made in this section, as well as in the abstract and titles of this application, to avoid obscuring the purpose of this section, the abstract and titles, and such simplifications or omissions should not be used to limit the scope of the invention.

In view of the problems existing in the tree structure parameter estimation method of the above-mentioned existing mechanical pruning of fruit trees, the present invention is proposed.

Therefore, the object of the present invention is to provide a method for estimating tree structure parameters of mechanical pruning of fruit trees, which uses the trunk as a reference axis to study the degree of dispersion of key points on the edge of the canopy to achieve detailed estimation of tree structure parameters , to provide reference information for the automatic adjustment of the tool position of mechanical pruning, so as to solve the problem that the fitting surface around the tree canopy has a large deviation in the tree structure estimation. .

In order to solve the above-mentioned technical problems, the present invention provides the following technical solutions: a method for estimating tree structure parameters of fruit tree mechanical pruning, including preprocessing; extracting the trunk axis, and generating a tree reference axis; detecting the contour points of the crown; and, Calculate how discrete the contour points are to the tree reference axis.

As a preferred solution of the method for estimating tree structure parameters of mechanical pruning of fruit trees in the present invention, wherein: the preprocessing includes scanning the tree body, determining coordinate axes and valid data ranges.

As a preferred solution of the method for estimating tree structure parameters of fruit tree mechanical pruning in the present invention, the scanning module is used for scanning the tree body.

As a preferred solution of the method for estimating tree structure parameters of fruit tree mechanical pruning in the present invention, wherein: the determined coordinate axes and valid data ranges are both set and displayed by a processing terminal.

As a preferred solution of the method for estimating tree structure parameters of fruit tree mechanical pruning in the present invention, wherein: the coordinate axes are a space coordinate system composed of 3D orthogonal space coordinate axes X, Y, and Z.

As a preferred scheme of the method for estimating tree structure parameters of fruit tree mechanical pruning in the present invention, wherein: the extraction of the trunk axis adopts an automatic search algorithm;

Wherein, the algorithm steps of the automatic search: (1) determine the interest point area; (2) generate a cylinder accumulator; (3) determine the backbone position; (4) fit the backbone.

As a preferred scheme of the tree structure parameter estimation method of mechanical pruning of fruit trees in the present invention, wherein: the predicted value of the fitted main line adopts the spatial straight line equation as:

Among them, (x, y, z) represents the point on the space line, a and c represent the slope of the line, b and d represent the intercept of the line;

According to the principle of the spatial least squares method, the sum of the squares of the difference between the predicted value and the real value is ε _x , ε _y :

When the difference square sum ε _x , ε _y is the minimum value, ε _x , ε _y must satisfy the following formula:

The optimal a, b, c, d can be obtained.

As a preferred solution of the tree structure parameter estimation method for mechanical pruning of fruit trees in the present invention, wherein: the detection of the contour points of the tree crown utilizes the convex hull principle.

As a preferred solution of the tree structure parameter estimation method for fruit tree mechanical pruning in the present invention, wherein: the contour points are (x _ki , y _ki , z _ki ).

The degree of dispersion from the outline point to the tree body reference axis is L _i :

Among them, x' _ki and y' _ki represent the abscissa and ordinate of the point on the reference axis at the same height as the contour point.

A system for estimating tree structure parameters suitable for mechanical pruning of fruit trees, the system adopts the scanning module of the method for estimating tree structure parameters of mechanical pruning of fruit trees for implementation, including a scanning module for transmitting and receiving The first signal, and the received first signal is sent to the control module through the data transmission module; the control module reads the received first signal and decodes the first signal into a second signal, and establishes a connection with the processing module ; A processing module, configured to receive the second signal from the control module and process the received second signal to form a scanned data scene and display it on the display screen.

Beneficial effects of the present invention: the present invention uses the trunk as the reference axis to study the degree of dispersion of key points on the edge of the canopy to achieve detailed estimation of the tree structure parameters and provide benchmark information for the automatic adjustment of the position of the tool for mechanical pruning. In this way, the problem that the fitting surface around the tree canopy has a large deviation in the estimation of the tree structure is beneficial to the efficiency of mechanical pruning, saving time and effort, and saving resources to meet the needs of use.

Description of drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings that need to be used in the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For Those of ordinary skill in the art can also obtain other drawings based on these drawings without any creative effort. in:

FIG. 1 is a schematic diagram of the overall structure of the first and second embodiments of the method for estimating tree structure parameters of mechanical pruning of fruit trees and the system thereof according to the present invention.

Fig. 2 is a scene diagram of scanned data described in the first embodiment of the method for estimating tree structure parameters of mechanical pruning of fruit trees and the system thereof according to the present invention.

Fig. 3 is a schematic diagram showing the 3D data display of the tree body in the first embodiment of the method for estimating tree body structure parameters of mechanical pruning of fruit trees and the system thereof according to the present invention.

Fig. 4 is a structural diagram of a cylindrical accumulator containing the most data points of the first embodiment of the method for estimating tree structure parameters of fruit tree mechanical pruning and the system thereof.

Fig. 5 is a tree trunk scatter diagram extracted by the first embodiment of the method for estimating tree structure parameters of mechanical pruning of fruit trees and the system thereof according to the present invention.

Fig. 6 is a fitting tree trunk line of the first embodiment of the method for estimating tree structure parameters of mechanical pruning of fruit trees and the system thereof according to the present invention.

Fig. 7 is a schematic diagram of the extraction effect of key edge points of the canopy in the first embodiment of the method for estimating tree body structure parameters of mechanical pruning of fruit trees and the system thereof according to the present invention.

Fig. 8 is a schematic diagram of the effect of the key edge point projection reference axis of the first embodiment of the tree structure parameter estimation method and system of fruit tree mechanical pruning according to the present invention.

Fig. 9 is a schematic flowchart of the second embodiment of the method for estimating tree structure parameters of mechanical pruning of fruit trees and the system thereof according to the present invention.

Detailed ways

In order to make the above objects, features and advantages of the present invention more obvious and comprehensible, specific implementations of the present invention will be described in detail below in conjunction with the accompanying drawings.

In the following description, a lot of specific details are set forth in order to fully understand the present invention, but the present invention can also be implemented in other ways different from those described here, and those skilled in the art can do it without departing from the meaning of the present invention. By analogy, the present invention is therefore not limited to the specific examples disclosed below.

Second, "one embodiment" or "an embodiment" referred to herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. "In one embodiment" appearing in different places in this specification does not all refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

Secondly, the present invention is described in detail in conjunction with schematic diagrams. When describing the embodiments of the present invention in detail, for the convenience of explanation, the cross-sectional view showing the device structure will not be partially enlarged according to the general scale, and the schematic diagram is only an example, and it should not be used here. Limit the scope of protection of the present invention. In addition, the three-dimensional space dimensions of length, width and depth should be included in actual production.

Referring to Figs. 1 to 8, the first embodiment of the present invention provides a schematic diagram of the overall structure of a tree structure parameter estimation method for mechanical pruning of fruit trees, as shown in Fig. 1, a tree structure parameter for mechanical pruning of fruit trees The estimation method includes preprocessing; extracting the main axis and generating the reference axis of the tree body; detecting the contour points of the tree crown; and calculating the degree of dispersion of the contour points to the reference axis of the tree body.

Specifically, the method of the present invention includes preprocessing; extracting the main axis, and generating the tree body reference axis; detecting the contour points of the tree crown; The structural parameters are estimated, which is beneficial to provide benchmark information for the automatic adjustment of the tool position of mechanical pruning, which is conducive to the efficiency of mechanical pruning, saves time and effort, saves resources, and meets the needs of use.

Further, the preprocessing includes scanning the tree body, determining the coordinate axis and the effective data range, wherein the scanning tree body adopts the scanning module 100, preferably, the scanning module is a VLP-16 scanner, and the VLP-16 scanner is also called VLP- 16 Lidar sensors, which have real-time data, 360° field of view, three-dimensional coordinates, and calibrated reflectivity measurement, and are small in size, low in power consumption, and reasonable in cost. As the main equipment for generating high-resolution 3D models, when used, According to the height and spacing of tall spindle-shaped trees, the VLP-16 scanner is rotated 90 degrees and placed on a tripod at a certain height (1.7 meters) from the ground to scan a single tree, in order to be suitable for the processing environment To determine the coordinate axis, the Y axis is transformed into the Z axis, the X axis is transformed into the Y axis, and the Z axis is transformed into the X axis. Among them, the X axis represents the left and right displacement of the scanned object from the coordinate center of the scanner, and the Y represents The distance between the scanned object and the coordinate center of the scanner, and Z represents the height of the scanned object from the coordinate center of the scanner; at the same time, according to the characteristics of the scanned data of the VLP-16 scanner (can return data within 100 meters, between 30 degrees up and down) , will mix the information of the ground and other trees, so by formulating the constraint conditions of the Y value and Z value range, the constraint condition is that the Y value of the target fruit tree is between 0.5 meters and 2.5 meters from the scanner, and the starting point of the effective tree trunk When the height Z value is greater than -1.5 meters (the height of the weeds on the ground is about 0.2 meters), invalid data is automatically eliminated, thereby determining the effective data range; it should be noted that the settings for determining the coordinate axis and the valid data range are all set by the processing terminal. The processing terminal is a notebook, computer, tablet or mobile phone, etc., and its coordinate axis is a space coordinate system composed of 3D orthogonal space coordinate axes X, Y, and Z.

Further, an automatic search algorithm is used to extract the main axis; wherein, the specific steps of the automatic search algorithm are as follows:

(1) Determine the point of interest area

Point coordinates that meet a certain Z value are saved as interest point areas, in order to ensure that the number of scanned points truly reflects the bottom of the trunk, and to avoid the impact of weeds at the bottom of the tree on the recognition.

(2) Generate a cylindrical accumulator

According to the size of the Z value, the points of interest are sequentially extracted as the center of the cylinder bottom; according to the conventional tree diameter (0.05m) combined with a certain empirical offset of 0.01-0.05m, set the appropriate threshold for the radius of the cylinder; the reference is clear The trunk height (that is, the height below the growth point of the main branch) sets the column height.

(3) Determine the backbone position

Using a series of cylindrical accumulators generated, compare the coordinates of the interest point and the coordinate range of the cylindrical accumulator respectively, record the coordinate points (xi _, y _i , zi ₎ inside the cylindrical accumulator, and count their number m, Extract the cylinder with the largest number of data points to determine the trunk position of the tree (see Figure 4).

(4) Fitting the main line

Since the spatial straight line is equivalent to the intersecting line of two planes, the data inside the cylinder (shown in Figure 5) is fitted using the spatial least squares method, and the predicted value of the fitted main line adopts the spatial straight line equation as follows:

Among them, (x, y, z) represents the point on the space straight line, a and c represent the slope of the line, b and d represent the intercept of the line; but in the actual scatter fitting, the above spatial straight line equation is used to calculate The result of is the predicted value. In order to determine the sum of the squares of the differences between the predicted value and the real value ε _x , ε _y is the minimum value to obtain the results of a, b, c, and d.

According to the principle of the spatial least squares method, the sum of the squares of the difference between the predicted value and the real value is ε _x , ε _y :

When the difference square sum ε _x , ε _y is the minimum value, ε _x , ε _y must satisfy the following formula:

The optimal a, b, c, d can be obtained.

Further, the points outside the cylindrical accumulator are defined as contour points (x _ki , y _ki , z _ki ), which use the convex hull principle to extract key edge points in the contour points (as shown in Figure 7), the process: from Starting from the leftmost and rightmost endpoints of the contour points, scan other points in a counterclockwise direction; if the convexity of the graph formed by the newly scanned point and the determined point remains unchanged (that is, the result of the cross product of the vector corresponding to the adjacent edge of the graph greater than 0), then temporarily store the new scanning point as a definite point, and continue to scan the next point; otherwise, delete the previous definite point, save the new scanning point, and then scan other points, and continue to compare the convexity until there is no change; finally, the The scanned upper and lower graphics are merged together to determine the convex hull, and the key edge point is the apex of the convex hull; since most main branch ends are located at the edge points, post-processing can be simplified and greatly reduced Running time; then extend the trunk fitting line and use it as a reference axis to project all key edge points to the reference axis, the effect is close to the spatial distribution of branches in the canopy.

It should be noted that the degree of dispersion _of the calculated contour points to _the reference axis of the tree is calculated by _{using the spatial straight line equation to calculate the point (x′ ki ,} y ' _ki , z _ki ), let the degree of dispersion from the contour point to the reference axis of the tree body be L _i , according to the following formula:

It can reflect the change trend of the outer surface of the canopy, and then complete the estimation of the tree structure parameters. The completed model data is sent to the position of the mechanical pruning tool for automatic adjustment to provide benchmark information.

Referring to Figs. 1 and 9, it is a second embodiment of the present invention, which provides a schematic diagram of a system flow structure suitable for tree structure parameter estimation of fruit tree mechanical pruning, as shown in Fig. 9, a kind of system suitable for fruit tree mechanical pruning A system for estimating tree structure parameters, the system adopts the scanning module 100 of the method for estimating tree structure parameters of fruit tree mechanical pruning, including the scanning module 100, which is used to transmit and receive the first signal, and the received second signal A signal is sent to the control module 300 through the data transmission module 200; the control module 300 reads the received first signal and decodes the first signal into a second signal, and establishes a connection with the processing module 400; the processing module 400 is used to receive The second signal of the control module 300 is processed and the received second signal is formed to form a scanned data scene and display it on the display screen.

Specifically, this system is suitable for tree structure parameter estimation of fruit tree mechanical pruning, and is used to control the processes of signal sending and receiving, signal processing, data transmission, parameter estimation and modeling of the scanning module 100 in the present invention.

Further, it adopts the scanning module 100 of the tree structure parameter estimation method of mechanical pruning of fruit trees for implementation, including the scanning module 100, which is used to transmit and receive the first signal, and pass the received first signal through the data transmission module 200 is sent to the control module 300; the control module 300 reads the received first signal and decodes the first signal into a second signal, and establishes a connection with the processing module 400; the processing module 400 is used to receive the second signal of the control module 300 signal and process the received second signal to form a scanned data scene and display it on the display screen.

Specifically, the scanning module 100 in the present invention is used to transmit the first signal to the surface of the tree body. Since the first signal will be reflected when encountering the tree body, the scanning module 100 can also receive the reflected first signal. The first signal The data is transmitted to the control module 300 through the data transmission module 200. The control module 300 and the processing module 400 determine the spatial coordinates of the surface reflection points by analyzing the relative distance of the calculation points, and finally obtain the tree scanning data, and then establish a data model through matlab.

It should be noted that the scanning module 100 is fixed on a tripod, and includes a signal transmitter 101 and a signal receiver 102 . Wherein, the signal transmitter 101 adopts a light pulse transmitter, which transmits a first signal to the tree, and captures the reflected first signal through the signal receiver 102, wherein the first signal is a pulse signal. The signal transmitter 101 projects the light (laser line) at high frequency (on/off), and continuously projects it onto the surface of the measured tree body to form dense reflection points to ensure the accuracy of the measurement.

Further, the data transmission module 200 can use a cable, the two ends of which are respectively connected to the signal receiver 102 and the control module 300, for transmitting the received signal from the signal receiver 102 to the control module 300, and the control module 300 reads the received signal The first signal is decoded into a second signal, and finally transmitted to the processing module 400 through the control module 300 for data analysis and processing.

The control module 300 is mainly used to collect and convert signals, and transmit the data after the converted signals to the processing module 400, which can be a control box; wherein, the transmission between the control module 300 and the processing module 400 can be through the data transmission module 200 or wireless communication transfer data.

The processing module 400 is arranged on the processing terminal, and the processing module 400 is used to receive the second signal of the control module 300 and process the received second signal to form a scanned data scene and display it on the display screen of the processing terminal, wherein the processing Module 400 is a processor.

It is important to note that the construction and arrangement of the application, shown in the various exemplary embodiments, are illustrative only. Although only a few embodiments have been described in detail in this disclosure, it should be readily apparent to those who review this disclosure that many modifications are possible without materially departing from the novel teachings and advantages of the subject matter described in this application. are possible (e.g., variations in dimensions, dimensions, structures, shapes and proportions of various elements, as well as parameter values (e.g., temperature, pressure, etc.), mounting arrangements, use of materials, colors, orientations, etc.). For example, elements shown as integrally formed may be constructed of multiple parts or elements, the position of elements may be inverted or otherwise varied, and the nature or number or positions of discrete elements may be altered or varied. Accordingly, all such modifications are intended to be included within the scope of this invention. The order or sequence of any process or method steps may be varied or re-sequenced according to alternative embodiments. In the claims, any "means-plus-function" clause is intended to cover the structures described herein as performing the recited function and not only structural equivalents but also equivalent structures. Other substitutions, modifications, changes and omissions may be made in the design, operation and arrangement of the exemplary embodiments without departing from the scope of the invention. Accordingly, the invention is not limited to a particular embodiment, but extends to various modifications still falling within the scope of the appended claims.

Moreover, in order to provide a concise description of exemplary embodiments, not all features of an actual embodiment (i.e., those features not relevant to the best mode presently considered for carrying out the invention, or to practicing the invention feature).

It should be appreciated that during the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort would be complex and time-consuming, but would be a routine matter of design, fabrication, and production without undue experimentation to those of ordinary skill having the benefit of this disclosure .

It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention without limitation, although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be carried out Modifications or equivalent replacements without departing from the spirit and scope of the technical solution of the present invention shall be covered by the claims of the present invention.

Claims (2)

1. A tree structure parameter estimation method of mechanical pruning of fruit trees, characterized in that: comprising, preprocessing; Extract the main axis and generate the tree reference axis; Detect the contour points of the tree canopy; and, Calculate the degree of dispersion of the contour points to the tree reference axis; The preprocessing includes scanning the tree body, determining coordinate axes and valid data ranges; The scanning tree adopts a scanning module; Both the determined coordinate axes and the effective data range are set and displayed by the processing terminal; The coordinate axes are a space coordinate system formed by 3D orthogonal space coordinate axes X, Y, and Z; The extraction of the main axis adopts an automatic search algorithm; Wherein, the algorithm steps of described automatic search: (1) determine interest point area; (2) generate cylindrical accumulator; (3) determine backbone position; (4) fit backbone; The predicted value of the fitted main line adopts the spatial straight line equation as:

Among them, (x, y, z) represents the point on the space line, a and c represent the slope of the line, b and d represent the intercept of the line; Record the coordinate points (x _i , y _i , z _i ) inside the cylindrical accumulator, and count their number m; According to the principle of the spatial least squares method, the sum of the squares of the difference between the predicted value and the real value is ε _x , ε _y :

When the difference square sum ε _x , ε _y is the minimum value, ε _x , ε _y must satisfy the following formula:

The optimal a, b, c, d can be obtained; The contour points of the detected tree crown utilize the convex hull principle; The contour points are (x _ki , y _ki , z _ki ); Wherein, the degree of dispersion from the outline point to the reference axis of the tree body is L _i :

Among them, x' _ki and y' _ki represent the abscissa and ordinate of the point on the reference axis at the same height as the contour point. 2. A system for estimating tree structure parameters of fruit tree mechanical pruning, applied to the tree structure parameter estimation method of fruit tree mechanical pruning as claimed in claim 1, characterized in that: said system adopts said fruit tree machinery The scanning module of the tree structure parameter estimation method for pruning is implemented, including, The scanning module is used to transmit and receive the first signal, and transmit the received first signal to the control module through the data transmission module; The control module reads the received first signal and decodes the first signal into a second signal, and establishes a connection with the processing module; The processing module is used to receive the second signal from the control module and process the received second signal to form a scanned data scene and display it on the display screen.

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