Plant modeling three-dimensional modeling automatic pruning method and system based on laser radar

Abstract

The invention provides a laser radar-based plant modeling three-dimensional modeling automatic pruning method and system. The method comprises the steps of obtaining plant modeling data of a plant to be pruned through a laser radar on a running trolley and generating three-dimensional point cloud data Cloudp; carrying out high-precision adaptation processing on the plant standard modeling point cloud data Clouds to generate point cloud data Cloudcut of a to-be-pruned area, and carrying out clustering processing to generate an Areaccut of the to-be-pruned area; and carrying out pruning path planning in the area to be pruned, generating a working track, and executing automatic pruning of the plant to be pruned. Fixed plants are automatically pruned, and the problems that garden modeling plants are repeatedly pruned, work is large, and efficiency is low are solved.

Description

Technical Field

[0001] The invention relates to the application of automation technology in the field of horticulture, in particular to a method and system for automatic pruning of plant shapes based on three-dimensional modeling of laser radar. Background Art

[0002] Garden modeling is a kind of garden art. It uses plants from the environment as materials and creates three-dimensional geometric shapes of various contours according to the specific requirements of the environment and artistic conception. It is a perfect combination of plant cultivation technology and gardening art. It is also a means to transform environmental plants and improve the beauty of the environment.

[0003] At present, there are many garden plants, which can be seen everywhere. There are a large number of plants that need to be pruned in communities, parks, and on both sides of roads. The traditional pruning method is that gardeners use pruning shears to prune one by one according to their own considerations. It is a lot of work and inefficient. Moreover, as the plants grow, they need to be pruned again and again. Summary of the invention

[0004] In order to solve the above technical problems, the present invention proposes a method and system for automatic pruning of plant modeling based on laser radar, which can automatically realize the design of the plant shape model in the computer and the automatic pruning according to the designed model, and can automatically prune fixed plants repeatedly, which can solve the problem of repeated pruning of garden plants, heavy work and low efficiency. Especially for long-distance, single, large-volume, long-term and repeated pruning on both sides of the road, the advantages of this device and method are particularly obvious.

[0005] In a first aspect, the present invention proposes a method for automatic pruning of plant shape three-dimensional modeling based on laser radar, and the method specifically comprises the following steps:

[0006] The laser radar on the running car is used to obtain the plant shape data of the plants to be pruned and generate three-dimensional point cloud data Cloudp;

[0007] The three-dimensional point cloud data Cloud p And plant standard shape point cloud data Cloud s After high-precision adaptation processing, point cloud data of the area to be trimmed is generated. cut , and the point cloud data Cloud of the area to be pruned cut After clustering, the area to be pruned is generated. cut ;

[0008] In the area to be trimmed Areas cut A pruning path planning is performed to generate an operation trajectory, and automatic pruning of the plants to be pruned is performed.

[0009] As a further improved technical solution, the laser radar on the running car obtains the plant shape data of the plants to be pruned and generates 3D point cloud data Cloud p The steps specifically include:

[0010] The point cloud of the plant to be pruned is collected in real time by running the laser radar on the vehicle, and after filtering out invalid point clouds, a point cloud of the plant area is generated according to satellite positioning and prior information of the plant position;

[0011] Select n collection points based on the laser radar field of view and plant size, and calculate the position transformation relationship of each collection point relative to the initial collection point;

[0012] According to the posture transformation relationship, the point clouds of the plant areas at different angles are superimposed to generate three-dimensional point cloud data Cloud p .

[0013] As a further improved technical solution, the steps of collecting point clouds of the plants to be pruned in real time by running a laser radar on a trolley, filtering out invalid point clouds, and generating point clouds of the plant area according to satellite positioning and prior information of the plant position include:

[0014] Set the prior space position of the plant to c k =[X k , Y k , Z k ] T , assuming that the current collection is the kth plant object; the laser radar point cloud at the current frame t is Cloud p_t , through coordinate transformation, Cloud p_ The three-dimensional point coordinates in t are converted into satellite longitude and latitude coordinates to obtain Cloud pGPS_t , judge Cloud pGPS_t Does the three-dimensional space point in belong to space c k If it belongs to the plant area, it is retained, otherwise it is filtered out to generate the point cloud Cloud of the filtered plant area pGPS_t_F ;

[0015] The judgment formula is as follows:

[0016]

[0017] In the formula, k represents the kth operating plant or plant association, Cloud pGPS_t_F (i) represents the i-th 3D spatial point in the filtered point cloud.

[0018] As a further improved technical solution, the steps of selecting n acquisition points based on the laser radar field of view and the plant size and calculating the posture transformation relationship of each acquisition point relative to the initial acquisition point include:

[0019] Set the longitude and latitude coordinates of the initial collection point to L(lat, lon), and the longitude and latitude coordinates of the ωth collection point to L ω (lat ω ,lon ω ), the vehicle posture of the running car at the initial collection point The vehicle posture at the ωth collection point is

[0020] According to the formula:

[0021]

[0022] Calculate the ωth acquisition point L ω (lat ω ,lon ω ) relative to the initial acquisition point L (lat, lon) displacement dis, so based on the relative angle and displacement of the ωth acquisition point in the initial acquisition point position, the translation matrix T is obtained ω ;

[0023] According to the vehicle posture of the ωth acquisition point, the rotation matrix R of the vehicle posture transformation of the ωth acquisition point relative to the initial acquisition point is obtained based on the rotation matrix of the x-axis, y-axis and z-axis. ω ;

[0024] Among them, the rotation matrix based on the x-axis is:

[0025]

[0026] The rotation matrix around the y-axis is:

[0027]

[0028] The rotation matrix around the z-axis is:

[0029]

[0030] R ω =R ωz ·R ωy ·R ωz

[0031] In the above formula, represents the heading angle, θ represents the pitch angle, and y represents the roll angle.

[0032] As a further improved technical solution, the point clouds of the plant areas at different angles are superimposed according to the posture transformation relationship to generate a three-dimensional point cloud data Cloud p The steps include calculating the three-dimensional point cloud data Cloud by formulap :

[0033] Cloud p =Cloud pGPS_t_F_P0 +Cloud pGPS_t_F_p1 [R1 T1]+…+Cloud pGPS_t_F_pn ·[R n T n ]

[0034] In the formula, Cloud pGPS_t_F_Pn Represents the filtered point cloud Cloud obtained from the nth acquisition angle pGPS_t_F .

[0035] As a further improved technical solution, the three-dimensional point cloud data Cloud p And plant standard shape point cloud data Cloud s After high-precision adaptation processing, point cloud data of the area to be trimmed is generated. cut , and the point cloud data Cloud of the area to be pruned cut After clustering, the area to be pruned is generated. cut The steps include:

[0036] The three-dimensional point cloud data Cloud p After encoding according to the preset encoding format, the standard plant shape point cloud data Cloud s High-precision adaptation is performed through the nearest neighbor iterative algorithm, and after coordinate transformation, the coordinate system is entered with the ground as the XY plane and the Z axis as the vertical upwards;

[0037] The space of the plant area is divided into cylindrical grids based on a spatial resolution of 3cm×3cm, and Cloud p and Cloud s The three-dimensional points that fall into the cylindrical grid are recorded as point sets Points p_G_Xi_Yi and Points s_G_Xi_Yi , calculate Points respectively p_G_Xi_Yi The average height of the midpoint d p_G_Xi_Yi and d s_G_Xi_Yi ;

[0038] D p_G_Xi_Yi -d s_G_Xi_Yi The cylindrical grids with a value of ≥τ are marked as the grids to be pruned. After traversing all the cylindrical grids in the space of the plant area, all the grids to be pruned are obtained, and the standard modeling point cloud data of the plant falls into the grids to be pruned, and the point cloud of the area to be pruned is obtained. cut , where τ is a threshold value set to be greater than 0;

[0039] Using the Euclidean distance clustering method, cut Cluster the point cloud in to generate the area to be pruned Areas cut .

[0040] As a further improved technical solution, in the to-be-trimmed area Areas cut The steps of planning a pruning path to generate an operation trajectory and automatically pruning the plants to be pruned include:

[0041] According to the pruning space of the pruning manipulator on the running trolley, the plant pruning operation is divided into m operation points and connected to the area to be pruned Areas cut After the corresponding relationship is established, multiple to-be-pruned areas belonging to the same operation point are sorted from left to right and from top to bottom; for the same to-be-pruned area, the to-be-pruned area is divided into several sub-areas according to the width of the operation; the key points of the operation path are selected, that is, the operation, and the key points are the operation starting point and end point of the sub-area. Among them, the path between the key points is planned by the hybrid A* algorithm to generate an operation sub-trajectory of a sub-area to realize traversal pruning; and the operation trajectory is generated based on the following encoding method:

[0042] [Working point 1: track 1, ..., track n1;

[0043] Operation point 2: track 1, ..., track n2;

[0044] …

[0045] Operation point n: track 1, ..., track nn]

[0046] The running vehicle automatically prunes the plants to be pruned according to the operation trajectory.

[0047] In the second aspect, the present invention also proposes a three-dimensional modeling automatic pruning system for plant modeling based on laser radar, the system comprising: a running trolley, a pruning device and a back-end data processing platform, the pruning device is located on the running trolley and includes a laser radar and two pruning manipulators, the running trolley also includes a control module for controlling the running trolley and the pruning device and performing data interaction with the back-end data processing platform;

[0048] The running vehicle walks around the plant to be pruned, obtains plant shape data of the plant to be pruned through the laser radar and generates three-dimensional point cloud data Cloudp;

[0049] The three-dimensional point cloud data Cloud p It is sent to the back-end data processing platform through TCP / IP protocol and compared with the plant standard modeling point cloud data Cloud sAfter high-precision adaptation processing, point cloud data of the area to be trimmed is generated. cut , and the point cloud data Cloud of the area to be pruned cut After clustering, the area to be pruned is generated. cut , in the area to be trimmed Areas cut Perform pruning path planning to generate the operation trajectory of the pruning manipulator;

[0050] The operation trajectory is sent to the control module, and the control module controls the pruning robot to perform automatic pruning of the plants to be pruned.

[0051] Compared with the prior art, the present invention has the following beneficial technical effects:

[0052] The present invention mainly aims at the pruning of garden modeling plants, and proposes automatic pruning equipment and method based on laser radar three-dimensional modeling of garden modeling plants, which can realize fully automatic, repeated, and less human participation plant pruning, and can efficiently complete the batch pruning of garden modeling plants. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a flow chart of the automatic pruning method for three-dimensional plant modeling based on laser radar proposed in the present invention.

[0054] Figure 2 This is a framework diagram of the laser radar-based plant three-dimensional modeling and automatic pruning system proposed for the invention. DETAILED DESCRIPTION

[0055] For ease of understanding, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] The terms used herein are only used for the purpose of describing specific example embodiments and are not restrictive. For example, unless the context clearly indicates otherwise, as used herein, the singular forms "a", "an" and "the" may also include plural forms. When used in this specification, the terms "include", "comprise" and / or "contain" mean that the associated integers, steps, operations, elements and / or components exist, but do not exclude the existence of one or more other features, integers, steps, operations, elements, components and / or groups or that other features, integers, steps, operations, elements, components and / or groups may be added in the system / method.

[0057] In view of the following description, these and other features of the present specification, as well as the operation and function of the related elements of the structure, and the economy of the combination and manufacture of the parts can be significantly improved. Reference is made to the accompanying drawings, all of which form a part of this specification. However, it should be clearly understood that the drawings are for illustration and description purposes only and are not intended to limit the scope of this specification. It should also be understood that the drawings are not drawn to scale.

[0058] The flowcharts used in this specification illustrate the operations implemented by the system according to some embodiments in this specification. It should be clearly understood that the operations of the flowcharts may not be implemented in sequence. On the contrary, the operations may be implemented in reverse order or simultaneously. In addition, one or more other operations may be added to the flowchart. One or more operations may be removed from the flowchart.

[0059] Figure 1 The flowchart of the automatic pruning method for plant modeling based on laser radar 3D modeling proposed by the present invention is shown. As shown in FIG1 , the automatic pruning method for plant modeling based on laser radar 3D modeling proposed by the present invention specifically includes the following steps:

[0060] Step S100: Obtain the plant modeling data of the plant to be pruned by running the laser radar on the vehicle and generate a three-dimensional point cloud data Cloud p .

[0061] In this embodiment, the pruning device is moved to the front of the pruning plant by the running trolley, and the running trolley walks around the plant. The laser radar collects 360° plant shape data, and generates a complete plant shape three-dimensional point cloud Cloud by coupling with inertial navigation data and satellite positioning data. p The specific steps include:

[0062] Step S101. The point cloud of the plant to be pruned is collected in real time by running the laser radar on the vehicle, and after filtering out invalid point clouds, a point cloud of the plant area is generated according to satellite positioning and prior information of the plant position.

[0063] In this embodiment, the a priori spatial position of the plant is set as c k =[X k , Y k , Z k ] T , assuming that the current collection is the kth plant object; the laser radar point cloud at the current frame t is Cloud p_t , through coordinate transformation, Cloud p_t The three-dimensional point coordinates in the cloud are converted into satellite longitude and latitude coordinates. pGPS_t , judge Cloud pGPS_t Does the three-dimensional point in space belong to space c? kIf it belongs to the plant area, it is retained, otherwise it is filtered out to generate the point cloud Cloud of the filtered plant area pGPS_t_F ;

[0064] The judgment formula is as follows:

[0065]

[0066] In the formula, k represents the kth operating plant or plant association, Cloud pGPS_t_F (i) represents the i-th 3D spatial point in the filtered point cloud.

[0067] Step S102: Select n acquisition points based on the laser radar field of view and the plant size, and calculate the posture transformation relationship of each acquisition point relative to the initial acquisition point.

[0068] In this embodiment, the longitude and latitude coordinates of the initial collection point are set to L (lat, lon), and the longitude and latitude coordinates of the ωth collection point are set to L ω (lat ω ,lon ω ), the vehicle posture of the running car at the initial collection point The vehicle posture at the ωth collection point is

[0069] According to the formula:

[0070]

[0071] Calculate the ωth acquisition point L ω (lat ω ,lon ω ) relative to the initial acquisition point L (lat, lon) displacement dis, so based on the relative angle and displacement of the ωth acquisition point in the initial acquisition point position, the translation matrix T is obtained ω ;

[0072] According to the vehicle posture of the ωth acquisition point, the rotation matrix R of the vehicle posture transformation of the ωth acquisition point relative to the initial acquisition point is obtained based on the rotation matrix of the x-axis, y-axis and z-axis. ω ;

[0073] Among them, the rotation matrix based on the x-axis is:

[0074]

[0075] The rotation matrix around the y-axis is:

[0076]

[0077] The rotation matrix around the z-axis is:

[0078]

[0079] R ω =R ωx ·R ωy ·R ωz

[0080] In the above formula, represents the heading angle, θ represents the pitch angle, and γ represents the roll angle.

[0081] According to the posture transformation relationship, the filtered point cloud of the plant area at different angles is obtained. pGPS_ t _F Generate 3D point cloud data after superposition p The steps include:

[0082] Cloud p =Cloud pGPS_t_F_P0 +Cloud pGPS_t_F_ p1·[R1 T1]+…+Cloud pGPS_t_F_pn ·[R n T n ]

[0083] In the formula, Cloud pGPs_t_F_Pn Represents the filtered point cloud Cloud obtained from the nth acquisition angle pGPS_t_F .

[0084] Calculate the 3D point cloud data Cloud p .

[0085] Step S103: Generate a three-dimensional point cloud data Cloud by superimposing the point clouds of the plant area at different angles according to the posture transformation relationship p .

[0086] In this embodiment, the formula:

[0087] Cloud p =Cloud P0 +Cloud P1 [R1 T1]+…+Cloud Pn ·[R n T n ]

[0088] Calculate the 3D point cloud data Cloud p .

[0089] Step S200: The three-dimensional point cloud data Cloud p And plant standard shape point cloud data Clouds After high-precision adaptation processing, point cloud data of the area to be trimmed is generated. cut , and the point cloud data Cloud of the area to be pruned cut After clustering, the area to be pruned is generated. cut .

[0090] In this embodiment, step S200 specifically includes the following contents:

[0091] Step S201. The three-dimensional point cloud data Cloud p After encoding according to the preset encoding format, the standard plant shape point cloud data Cloud s High-precision adaptation is performed through the nearest neighbor iterative algorithm, and after coordinate transformation, it enters a spatial coordinate system with the ground as the XY plane and the z-axis vertically upward.

[0092] The specific encoding method is shown in the following table:

[0093] Serial number protocol content describe 1 $ Frame Header 2 PGA Protocol Name 3 PLANTNO Plant number Range: 0-10000 4 Number Number of points Range: 0-10000000 5 ddd.mmmmmmm longitude 6 ddd.mmmmmmm latitude 8 dd.mmm Height above ground Range: 0-3; 9 M Unit meter 10 * Frame end 11 HH Checksum

[0094] Step S202: Divide the space of the plant area into cylindrical grids based on a spatial resolution of 3 cm × 3 cm, and calculate Cloud p and Cloud s The three-dimensional points that fall into the cylindrical grid are recorded as point sets Points p_G_Xi_Yi and Points s_G_Xi_Yi , calculate Points respectively p_G_Xi_Yi The average height of the midpoint d p_G_Xi_Yi and d s_G_Xi_Yi ;

[0095] Step S203. p_G_Xi_Yi -d s_G_Xi_Yi The cylindrical grids with a value of ≥τ are marked as the grids to be pruned. After traversing all the cylindrical grids in the space of the plant area, all the grids to be pruned are obtained, and the standard modeling point cloud data of the plant falls into the grids to be pruned, and the point cloud of the area to be pruned is obtained. cut , where τ is a threshold value set to be greater than 0;

[0096] Using the Euclidean distance clustering method, cut Cluster the point cloud in to generate the area to be pruned Areas cut .

[0097] Step S300: In the area to be trimmed Areas cut A pruning path planning is performed to generate an operation trajectory, and automatic pruning of the plants to be pruned is performed.

[0098] In this embodiment, the plant pruning operation is divided into m operation points according to the pruning space of the pruning manipulator on the running vehicle, and the pruning area Areas cut After the corresponding relationship is established, multiple to-be-pruned areas belonging to the same operation point are sorted from left to right and from top to bottom; for the same to-be-pruned area, the to-be-pruned area is divided into several sub-areas according to the width of the operation; the key points of the operation path are selected, that is, the operation, and the key points are the operation starting point and end point of the sub-area. Among them, the path between the key points is planned by the hybrid A* algorithm to generate an operation sub-trajectory of a sub-area to realize traversal pruning; and the operation trajectory is generated based on the following encoding method:

[0099] [Working point 1: track 1, ..., track n1;

[0100] Operation point 2: track 1, ..., track n2;

[0101] …

[0102] Operation point n: track 1, ..., track nn]

[0103] The running vehicle automatically prunes the plants to be pruned according to the operation trajectory.

[0104] like Figure 2 As shown, the present invention also proposes an automatic pruning system based on the automatic pruning method described in the first aspect, the system comprising: a running trolley, a pruning device and a back-end data processing platform, the pruning device is located on the running trolley and includes a laser radar and two pruning manipulators, the running trolley also includes a control module for controlling the running trolley and the pruning device to operate and to interact with the back-end data processing platform;

[0105] The running car walks around the plant to be pruned, obtains the plant shape data of the plant to be pruned through the laser radar and generates a three-dimensional point cloud data Cloud p ;

[0106] The three-dimensional point cloud data Cloud p It is sent to the back-end data processing platform through TCP / IP protocol and compared with the plant standard modeling point cloud data Cloud s After high-precision adaptation processing, point cloud data of the area to be trimmed is generated. cut , and the point cloud data Cloud of the area to be pruned cut After clustering, the area to be pruned is generated. cut , in the area to be trimmed Areas cut Perform pruning path planning to generate the operation trajectory of the pruning manipulator;

[0107] The operation trajectory is sent to the control module, and the control module controls the pruning robot to perform automatic pruning of the plants to be pruned.

[0108] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for automatic pruning of plant shape three-dimensional modeling based on laser radar, characterized in that: The method specifically comprises the following steps: The laser radar on the running car obtains the plant shape data of the plants to be pruned and generates 3D point cloud data Cloud p ; The three-dimensional point cloud data Cloud p And plant standard shape point cloud data Cloud s After high-precision adaptation processing, point cloud data of the area to be trimmed is generated. cut , and the point cloud data Cloud of the area to be pruned cut After clustering, the area to be pruned is generated. cut ; In the area to be trimmed Areas cut A pruning path planning is performed to generate an operation trajectory, and automatic pruning of the plants to be pruned is performed.

2. The method for automatic pruning of plant modeling based on laser radar according to claim 1, characterized in that: The laser radar on the running car obtains the plant shape data of the plants to be pruned and generates 3D point cloud data Cloud p The steps specifically include: The point cloud of the plant to be pruned is collected in real time by running the laser radar on the vehicle, and after filtering out invalid point clouds, a point cloud of the plant area is generated according to satellite positioning and prior information of the plant position; Select n collection points based on the laser radar field of view and plant size, and calculate the position transformation relationship of each collection point relative to the initial collection point; According to the posture transformation relationship, the point clouds of the plant areas at different angles are superimposed to generate three-dimensional point cloud data Cloud p .

3. The automatic pruning method for plant modeling based on laser radar according to claim 2 is characterized in that: The steps of collecting point clouds of the plants to be pruned in real time by running a laser radar on the vehicle, filtering out invalid point clouds, and generating point clouds of the plant area according to satellite positioning and prior information of the plant position include: Set the prior space position of the plant to c k =[X k , Y k , Z k ] T , assuming that the current collection is the kth plant object; the laser radar point cloud at the current frame t is Cloud p_t , through coordinate transformation, Cloud p_t The three-dimensional point coordinates in the cloud are converted into satellite longitude and latitude coordinates. pGPS_t , judge Cloud pGPS_t Does the three-dimensional point in space belong to space c? k If it belongs to the plant area, it is retained, otherwise it is filtered out to generate the point cloud Cloud of the filtered plant area pGPS_t_F ; The judgment formula is as follows: In the formula, k represents the kth operating plant or plant association, Cloud pGPS_t_F (i) represents the i-th 3D spatial point in the filtered point cloud.

4. The method for automatic pruning of plant shape three-dimensional modeling based on laser radar according to claim 3 is characterized in that: The steps of selecting n acquisition points based on the laser radar field of view and the plant size and calculating the posture transformation relationship of each acquisition point relative to the initial acquisition point include: Set the longitude and latitude coordinates of the initial collection point to L(lat, lon), and the longitude and latitude coordinates of the ωth collection point to L ω (lat ω ,lon ω ), the vehicle posture of the running car at the initial collection point The vehicle posture at the ωth collection point is According to the formula: Calculate the ωth acquisition point L ω (lat ω ,lon ω ) relative to the initial acquisition point L (lat, lon) displacement dis, so based on the relative angle and displacement of the ωth acquisition point in the initial acquisition point position, the translation matrix T is obtained ω ; According to the vehicle posture of the ωth acquisition point, the rotation matrix R of the vehicle posture transformation of the ωth acquisition point relative to the initial acquisition point is obtained based on the rotation matrix of the x-axis, y-axis and z-axis. ω ; Among them, the rotation matrix based on the x-axis is: The rotation matrix around the y-axis is: The rotation matrix around the z-axis is: R ω =R ωx ·R ωy ·R ωz In the above formula, represents the heading angle, θ represents the pitch angle, and γ represents the roll angle.

5. The method for automatic pruning of plant shape three-dimensional modeling based on laser radar according to claim 4 is characterized in that: According to the posture transformation relationship, the point clouds of the plant areas at different angles are superimposed to generate three-dimensional point cloud data Cloud p The steps include calculating the three-dimensional point cloud data Cloud by formula p : Cloud p =Cloud pGPS_t_F_P0 +Cloud pGPS_t_F_P1 ·[R1 T1]+…+Cloud pGPS_t_F_Pn ·[R n T n ] In the formula, Cloud pGPS_t_F_Pn Represents the filtered point cloud Cloud obtained from the nth acquisition angle pGPS_t_F .

6. The method for automatic pruning of plant shape three-dimensional modeling based on laser radar according to claim 5 is characterized in that: The three-dimensional point cloud data Cloud p And plant standard shape point cloud data Cloud s After high-precision adaptation processing, point cloud data of the area to be trimmed is generated. cut , and the point cloud data Cloud of the area to be pruned cut After clustering, the area to be pruned is generated. cut The steps include: The three-dimensional point cloud data Cloud p After encoding according to the preset encoding format, the standard plant shape point cloud data Cloud s High-precision adaptation is performed through the nearest neighbor iterative algorithm, and after coordinate transformation, the coordinate system is entered with the ground as the XY plane and the Z axis as the vertical upwards; The space of the plant area is divided into cylindrical grids based on a spatial resolution of 3cm×3cm, and Cloud p and Cloud s The three-dimensional points that fall into the cylindrical grid are recorded as point sets Points p_G_Xi_Yi and Points s_G_Xi_Yi , calculate Points respectively p_G_Xi_Yi The average height of the midpoint d p_G_Xi_Yi and d s_G_Xi_Yi ; D p_G_Xi_Yi -d s_G_Xi_Yi The cylindrical grids with a value of ≥τ are marked as the grids to be pruned. After traversing all the cylindrical grids in the space of the plant area, all the grids to be pruned are obtained, and the standard modeling point cloud data of the plant falls into the grids to be pruned, and the point cloud of the area to be pruned is obtained. cut , where τ is a threshold value set to be greater than 0; Using the Euclidean distance clustering method, cut Cluster the point cloud in to generate the area to be pruned Areas cut .

7. The method for automatic pruning of plant shape three-dimensional modeling based on laser radar according to claim 6, characterized in that: In the area to be trimmed Areas cut The steps of planning a pruning path to generate an operation trajectory and automatically pruning the plants to be pruned include: According to the pruning space of the pruning manipulator on the running trolley, the plant pruning operation is divided into m operation points and connected to the area to be pruned Areas cut After the corresponding relationship is established, multiple to-be-pruned areas belonging to the same operation point are sorted from left to right and from top to bottom; for the same to-be-pruned area, the to-be-pruned area is divided into several sub-areas according to the operation width; the key points of the operation path are selected, that is, the operation, and the key points are the operation starting point and end point of the sub-area. Among them, the path between the key points is planned by the hybrid A* algorithm to generate an operation sub-trajectory of a sub-area to realize traversal pruning; and the operation trajectory is generated based on the following encoding method: [Working point 1: track 1, ..., track n1; Operation point 2: track 1, ..., track n2; … Operation point n: track 1, ..., track nn] The running vehicle automatically prunes the plants to be pruned according to the operation trajectory.

8. An automatic pruning system based on the automatic pruning method for plant modeling three-dimensional modeling based on laser radar according to claims 1-7, characterized in that: The system includes: a running trolley, a pruning device and a back-end data processing platform. The pruning device is located on the running trolley and includes a laser radar and two pruning manipulators. The running trolley also includes a control module that controls the running trolley and the pruning device and exchanges data with the back-end data processing platform. The running trolley walks around the plant to be pruned, obtains the plant modeling data of the plant to be pruned through the laser radar, and generates a three-dimensional point cloud data Cloud p ; The three-dimensional point cloud data Cloud p It is sent to the back-end data processing platform through TCP / IP protocol and compared with the plant standard modeling point cloud data Cloud s After high-precision adaptation processing, point cloud data of the area to be trimmed is generated. cut , and the point cloud data Cloud of the area to be pruned cut After clustering, the area to be pruned is generated. cut , in the area to be trimmed Areas cut Perform pruning path planning to generate the operation trajectory of the pruning manipulator; The operation trajectory is sent to the control module, and the control module controls the pruning robot to perform automatic pruning of the plants to be pruned.

Images