Method and system for positioning agricultural area including forest, and storage medium

Abstract

The invention provides a positioning method and system for an agricultural area containing a forest and a computer storage medium, and the method comprises the steps: S1, obtaining a satellite signal of a satellite system, carrying out the positioning of the agricultural area based on the satellite signal, and obtaining a first positioning map relative to a system coordinate system, the first positioning map comprises a first area and a second area, the first area corresponds to a forest area, and the second area corresponds to other areas except the first area in the agricultural area; s2, three-dimensional point cloud data obtained by scanning the forest area through the laser radar are obtained, and a second positioning map relative to the system coordinate system is obtained based on the three-dimensional point cloud data; and S3, fusing the second positioning map into the first region of the first positioning map to obtain a third positioning map, so that the agricultural automation equipment performs agricultural operation on the agricultural region based on the third positioning map. According to the positioning method of the agricultural area containing the forest, the forest area can be accurately positioned.

Description

Technical Field

[0001] This invention relates to the field of agricultural automation, and in particular to a method, system, and storage medium for locating agricultural areas including forests. Background Technology

[0002] Automating agricultural operations, such as fertilization, weeding, harvesting, and inspection, can greatly improve efficiency and save manpower.

[0003] However, during operation, when encountering forests, the agricultural automation equipment will lose signal and be unable to carry out automated operations due to the obstruction of signals by the trees, resulting in blind spots. Summary of the Invention

[0004] To address the aforementioned problems in the prior art, the present invention aims to provide a method for locating agricultural areas including forests, which can accurately locate forest areas.

[0005] To address the aforementioned problems, a first aspect of the present invention provides a method for locating an agricultural area containing a forest, the method comprising:

[0006] Step S1: Obtain satellite signals from the satellite system, locate the agricultural area based on the satellite signals, and obtain a first positioning map relative to the system coordinate system. The first positioning map includes a first area and a second area. The first area corresponds to the forest area, and the second area corresponds to other areas outside the first area in the agricultural area.

[0007] Step S2: Obtain three-dimensional point cloud data obtained by scanning the forest area with lidar, and obtain a second positioning map relative to the system coordinate system based on the three-dimensional point cloud data;

[0008] Step S3: Integrate the second positioning map into the first area of ​​the first positioning map to obtain a third positioning map, so that agricultural automation equipment can perform agricultural operations on the agricultural area based on the third positioning map.

[0009] Furthermore, each tree in the forest is equipped with an electronic tag, which stores a unique identification code corresponding to the tree, and the electronic tag can emit radio frequency signals that can be received by a radio frequency reader;

[0010] Step S2 includes:

[0011] Step S21: Obtain three-dimensional point cloud data obtained by scanning the forest area with lidar, and obtain radio frequency signals from each tree;

[0012] Step S22: Based on the radio frequency signal, determine the identity of each tree in the three-dimensional point cloud data;

[0013] Step S23: Process the three-dimensional point cloud data to calculate the distance and azimuth of each tree relative to the origin of the system coordinate system;

[0014] Step S24: Determine the second positioning map based on the distance and azimuth of all trees.

[0015] Further, step S23 includes:

[0016] The three-dimensional point cloud data is projected horizontally to form two-dimensional point cloud data.

[0017] The two-dimensional point cloud data is clustered to form multiple point clusters, and each point cluster corresponds one-to-one with the identity of a different tree, with each point cluster representing a tree.

[0018] Shape fitting is performed on the point cluster to find the center of the tree; the shape fitting is either ellipse fitting or circle fitting.

[0019] The distance and azimuth of the tree's center relative to the origin of the system coordinate system are calculated to represent the distance and azimuth of the tree relative to the origin of the system coordinate system.

[0020] Further, step S23 includes:

[0021] The tree recognition model processes the 3D point cloud data to identify each tree in the forest and calculates the distance and azimuth of each tree relative to the origin of the system coordinate system.

[0022] Furthermore, the tree recognition model is obtained by labeling the trees in the 3D point cloud data samples and performing deep learning on the labeled 3D point cloud data samples.

[0023] Furthermore, step S2 also includes:

[0024] Step S25: Identify the intensity and angle of the radio frequency signal of the tree. Based on the correspondence between the intensity and angle of the radio frequency signal and the distance and azimuth of the tree relative to the system coordinate system, determine the distance and azimuth of the tree relative to the origin of the system coordinate system.

[0025] A second aspect of the present invention provides a positioning system for an agricultural area including a forest, the positioning system comprising:

[0026] Navigation systems are used to acquire satellite signals from satellite systems;

[0027] LiDAR is used to scan forest areas to obtain three-dimensional point cloud data.

[0028] A signal processing system, comprising:

[0029] The first positioning module is used to acquire satellite signals from the satellite system, locate the agricultural area based on the satellite signals, and obtain a first positioning map relative to the system coordinate system. The first positioning map includes a first area and a second area. The first area corresponds to the forest area, and the second area corresponds to other areas outside the first area in the agricultural area.

[0030] The second positioning module is used to acquire three-dimensional point cloud data obtained by the lidar scanning the forest area, and to obtain a second positioning map relative to the system coordinate system based on the three-dimensional point cloud data.

[0031] The fusion module is used to integrate the second positioning map into a first area of ​​the first positioning map to obtain a third positioning map, so that agricultural automation equipment can perform agricultural operations on the agricultural area based on the third positioning map.

[0032] Furthermore, the positioning system also includes:

[0033] Electronic tags are used to be attached to each tree in a forest. Each electronic tag stores a unique identification code corresponding to that tree and is capable of emitting radio frequency signals.

[0034] An RFID reader / writer, wherein the RFID reader / writer is used to receive RFID signals from the electronic tag;

[0035] Specifically, the second positioning module is used to acquire three-dimensional point cloud data obtained by scanning the forest area with lidar, and to acquire radio frequency signals from each tree; based on the radio frequency signals, to determine the identity of each tree in the three-dimensional point cloud data; to process the three-dimensional point cloud data and calculate the distance and azimuth angle of each tree relative to the origin of the system coordinate system; and to determine the second positioning map based on the distance and azimuth angle of all trees.

[0036] Furthermore, the electronic tag can be an active tag or a passive tag.

[0037] A third aspect of the present invention provides a computer-readable storage medium storing at least one instruction or at least one program, the at least one instruction or at least one program being loaded and executed by a processor to implement the method for locating an agricultural area containing a forest as described in any of the preceding claims.

[0038] Due to the above technical solution, the present invention has the following beneficial effects:

[0039] According to an embodiment of the present invention, a positioning method for an agricultural area including a forest region involves, based on received satellite signals, forming a clearer second region in an open area of ​​the agricultural region within a first positioning map, and forming a less clear first region in a forest area within the agricultural region within a forested area within the first positioning map. Based on received radar scan results, a clearer second positioning map is formed in the forested area. The less clear first region in the first positioning map is then replaced by the second positioning map to obtain a third positioning map.

[0040] The third positioning map includes the second area of ​​the first positioning map and the second positioning map, facilitating seamless integration of agricultural automation equipment into open and forested areas. The agricultural automation equipment performs automated operations in open areas based on the second area of ​​the first positioning map, and performs automated operations in forested areas based on the second positioning map. Attached Figure Description

[0041] To more clearly illustrate the technical solutions of the present invention, the accompanying drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0042] Figure 1 This is a flowchart of a method for locating an agricultural area containing a forest according to an embodiment of the present invention;

[0043] Figure 2 yes Figure 1 A flowchart of a specific embodiment of step 2 in the process;

[0044] Figure 3 This is a schematic diagram of a positioning system for an agricultural area containing a forest, according to an embodiment of the present invention. Detailed Implementation

[0045] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, apparatus, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0047] To make the objectives, technical solutions, and advantages disclosed in the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the embodiments of the present invention and are not intended to limit the embodiments of the present invention. The acquisition, storage, use, and processing of data in the technical solutions of the embodiments of the present invention all comply with the relevant provisions of national laws and regulations.

[0048] The following describes a method for locating agricultural areas containing forests according to an embodiment of the present invention.

[0049] like Figure 1 As shown, the method for locating agricultural areas including forests in an embodiment of the present invention includes:

[0050] Step S1: Obtain satellite signals from the satellite system, locate the agricultural area based on the satellite signals, and obtain a first positioning map relative to the system coordinate system. The first positioning map includes a first region and a second region. The first region corresponds to the forest area, and the second region corresponds to other areas outside the first region in the agricultural area.

[0051] In agricultural areas, non-forested areas are relatively open and receive better satellite signals, making the second region in the first positioning map clearer. In agricultural areas, forested areas provide significant obstruction and receive poorer satellite signals, making the first region in the first positioning map blurry.

[0052] Step S2: Obtain three-dimensional point cloud data obtained by scanning the forest area with lidar, and obtain a second positioning map relative to the system coordinate system based on the three-dimensional point cloud data.

[0053] The first and second positioning maps are relative to a system coordinate system, which facilitates the fusion of the first and second positioning maps.

[0054] LiDAR can scan forest areas well and does not rely on satellite signals, enabling precise positioning of forest areas. This makes the overall second positioning map relatively clear, which facilitates automated agricultural equipment to avoid interference from trees in the forest for automated operations.

[0055] Step S3: Integrate the second positioning map into the first area of ​​the first positioning map to obtain the third positioning map, so that agricultural automation equipment can carry out agricultural operations in the agricultural area based on the third positioning map.

[0056] In other words, a third positioning map is obtained by replacing the blurred first area in the first positioning map with the second positioning map. The third positioning map then includes the second area of ​​the first positioning map and the second positioning map itself. Agricultural automation equipment performs automated operations in open areas based on the second area of ​​the first positioning map, and performs automated operations in forested areas based on the second positioning map.

[0057] The above method for locating agricultural areas including forests is based on receiving satellite signals. It creates a clearer second region in the open areas of the agricultural area and a less clear first region in the forested areas of the first location map. Based on received radar scan results, a clearer second location map is created in the forested areas. This second location map is then used to replace the less clear first region in the first location map, resulting in a third location map.

[0058] The third positioning map includes the second area of ​​the first positioning map and the second positioning map, facilitating seamless integration of agricultural automation equipment into open and forested areas. The agricultural automation equipment performs automated operations in open areas based on the second area of ​​the first positioning map, and performs automated operations in forested areas based on the second positioning map.

[0059] In some embodiments of the present invention, each tree in the forest is equipped with an electronic tag, which stores a unique identification code for the corresponding tree and can emit radio frequency signals that can be received by a radio frequency reader.

[0060] like Figure 2 As shown, step S2 includes: step S21, acquiring three-dimensional point cloud data obtained by scanning the forest area with lidar, and acquiring radio frequency signals from each tree; step S22, determining the identity of each tree in the three-dimensional point cloud data based on the radio frequency signals; step S23, processing the three-dimensional point cloud data to calculate the distance and azimuth angle of each tree relative to the origin of the system coordinate system; step S24, determining the second positioning map based on the distance and azimuth angle of all trees.

[0061] The electronic tags and RFID readers are based on Radio Frequency Identification (RFID) technology. An electronic tag consists of an antenna and a chip. The RFID reader receives and decodes the radio frequency signals emitted by the electronic tag's antenna, identifying the tree's identity information stored in the tag's chip. Each electronic tag corresponds one-to-one with a tree.

[0062] In step S2, the lidar scans the forest area to form three-dimensional point cloud data, and acquires the three-dimensional point cloud data and the radio frequency signal emitted by the electronic tag of each tree; based on the radio frequency signal, the identity of each tree is identified; the three-dimensional point cloud data is processed, and the distance and azimuth of each tree relative to the origin of the system coordinate system are calculated by combining the tree identification (identification of trees with different identities); the second positioning map is determined based on the distance and azimuth of all trees.

[0063] This allows for the acquisition of a more accurate second location map. Moreover, even in environments where tree features are sparse (such as forests where trees are very similar and have no obvious differences), each tree can still be accurately identified.

[0064] Step S23 is implemented in two ways as follows.

[0065] The first method involves projecting the 3D point cloud data horizontally to form a 2D point cloud data; clustering the 2D point cloud data to form multiple point clusters, ensuring that each point cluster corresponds one-to-one with a unique tree, with each cluster representing a tree; performing shape fitting on the point clusters to find the center of the tree, with the shape fitting being either an ellipse or a circle; and calculating the distance and azimuth of the tree's center relative to the origin of the system coordinate system to represent the distance and azimuth of the tree relative to the origin of the system coordinate system.

[0066] Each dot cluster corresponds one-to-one with the identified different tree identities. The combination of shape recognition and radio frequency identification increases the accuracy of tree identification.

[0067] Therefore, based on the shape of the trees, each tree can be accurately identified, and the distance and azimuth of each tree in the forest relative to the origin of the system coordinate system can be calculated.

[0068] The second method involves processing the 3D point cloud data using a tree recognition model to identify each tree in the forest and calculate the distance and azimuth of each tree relative to the origin of the system coordinate system.

[0069] This method uses an intelligent tree recognition model to identify each tree in the forest and calculates the distance and azimuth of each tree relative to the origin of the system coordinate system. This method is highly efficient and accurate.

[0070] Optionally, the tree recognition model can be obtained by labeling trees in a 3D point cloud data sample and then performing deep learning on the labeled 3D point cloud data sample. The learning model used for deep learning can be YOLO.

[0071] In some embodiments of the present invention, such as Figure 2 As shown, step S2 further includes: step S25, identifying the intensity and angle of the radio frequency signal of the tree, and determining the distance and azimuth of the tree relative to the origin of the system coordinate system based on the correspondence between the intensity and angle of the radio frequency signal and the distance and azimuth of the tree relative to the system coordinate system.

[0072] In other words, the lidar identifies trees and calculates the distance and azimuth of each tree relative to the origin of the system coordinate system, then matches these values ​​with the radio frequency (RF) signals emitted by the corresponding electronic tags for each tree. By identifying the intensity and angle of the tree's RF signals, the distance and azimuth of that tree relative to the origin of the system coordinate system are determined.

[0073] During actual operation, agricultural automation equipment accurately determines the distance and azimuth of trees relative to the origin of the system coordinate system based on the intensity and angle of the identified radio frequency signals, making it easier to avoid interference from trees and carry out operations in forest areas more accurately.

[0074] The following describes a positioning system for an agricultural area including a forest, according to an embodiment of the present invention.

[0075] like Figure 3 As shown, the positioning system 1000 for an agricultural area including a forest in this embodiment of the invention includes: a navigation system 1001, a lidar 1002, and a signal processing system 1003.

[0076] The navigation system 1001 is used to acquire satellite signals from the satellite system. The lidar 1002 is used to scan the forest area to obtain three-dimensional point cloud data. The signal processing system 1003 includes a first positioning module, a second positioning module, and a fusion module. The first positioning module acquires satellite signals from the satellite system, positions the agricultural area based on the satellite signals, and obtains a first positioning map relative to the system coordinate system. The first positioning map includes a first region and a second region. The first region corresponds to the forest area, and the second region corresponds to other areas within the agricultural area outside the first region.

[0077] It should be noted that the signal processing system 1003 provided in the above embodiments is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the signal processing system 1003 provided in the above embodiments and the corresponding method embodiments belong to the same concept, and the specific implementation process can be found in the corresponding method embodiments, which will not be repeated here.

[0078] Furthermore, the positioning system 1000 also includes an electronic tag 1004 and an RFID reader 1005. The electronic tag 1004 is used to be attached to each tree in the forest. The electronic tag stores a unique identification code for the corresponding tree and can emit radio frequency signals. The RFID reader 1005 is used to receive the radio frequency signals from the electronic tag. Specifically, the second positioning module is used to acquire three-dimensional point cloud data obtained by scanning the forest area with a lidar sensor, and to acquire radio frequency signals from each tree; based on the radio frequency signals, it determines the identity of each tree in the three-dimensional point cloud data; it processes the three-dimensional point cloud data to calculate the distance and azimuth angle of each tree relative to the origin of the system coordinate system; and it determines a second positioning map based on the distance and azimuth angle of all trees.

[0079] Optionally, the electronic tag 1004 can be an active tag or a passive tag.

[0080] One embodiment of the present invention also provides a computer-readable storage medium. The computer-readable storage medium stores at least one instruction or at least one program, which is loaded and executed by a processor to implement the method for locating an agricultural area containing a forest as described above.

[0081] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method of locating an agricultural area comprising a forest, characterized in that, The positioning method comprises: Step S1, acquiring satellite signals of a satellite system, positioning an agricultural area based on the satellite signals, and obtaining a first positioning map relative to a system coordinate system, the first positioning map comprising a first area and a second area, the first area corresponding to a forest area, and the second area corresponding to other areas outside the first area in the agricultural area; Step S2, acquiring three-dimensional point cloud data obtained by scanning the forest area by a laser radar, and obtaining a second positioning map relative to the system coordinate system based on the three-dimensional point cloud data; Step S3, integrating the second positioning map into the first area of the first positioning map to obtain a third positioning map, so that an agricultural automation device performs agricultural work on the agricultural area based on the third positioning map.

2. The method of locating an agricultural area comprising a forest according to claim 1, characterized in that, Each tree in the forest is provided with an electronic tag, the electronic tag storing a unique identification code corresponding to the tree, and the electronic tag being capable of emitting a radio frequency signal receivable by a radio frequency reader; The step S2 comprises: Step S21, acquiring three-dimensional point cloud data obtained by scanning the forest area by a laser radar, and acquiring radio frequency signals from each tree; Step S22, determining the identity of each tree in the three-dimensional point cloud data based on the radio frequency signals; Step S23, processing the three-dimensional point cloud data to calculate the distance and azimuth of each tree relative to the origin of the system coordinate system; Step S24, determining the second positioning map based on the distance and azimuth of all trees.

3. The method of locating an agricultural area comprising a forest according to claim 2, characterized in that, The step S23 comprises: projecting the three-dimensional point cloud data in a horizontal direction to form two-dimensional point cloud data; clustering the two-dimensional point cloud data to form a plurality of point clusters, and making the point clusters one-to-one correspond to the determined identities of different trees, each point cluster representing a tree; performing shape fitting on the point clusters to find the center of the tree, the shape fitting being elliptical fitting or circular fitting; calculating the distance and azimuth of the center of the tree relative to the origin of the system coordinate system to represent the distance and azimuth of the tree relative to the origin of the system coordinate system.

4. The method of locating an agricultural area comprising a forest of claim 2, wherein, The step S23 comprises: processing the three-dimensional point cloud data through a tree identification model to identify each tree in the forest, and calculating the distance and azimuth of each tree relative to the origin of the system coordinate system.

5. The method of locating an agricultural area comprising a forest of claim 4, wherein, The tree identification model is obtained by labeling trees in a three-dimensional point cloud data sample and performing deep learning on the labeled three-dimensional point cloud data sample.

6. The method of locating an agricultural area comprising a forest of claim 2, wherein, The step S2 further comprises: Step S25, identifying the strength and angle of the radio frequency signal of the tree, and determining the distance and azimuth of the tree relative to the origin of the system coordinate system based on the correspondence between the strength and angle of the radio frequency signal and the distance and azimuth of the tree relative to the system coordinate system.

7. A positioning system for an agricultural area comprising a forest, characterized in that The positioning system comprises: a navigation system for acquiring satellite signals of a satellite system; a laser radar for acquiring three-dimensional point cloud data obtained by scanning a forest area; a signal processing system, the signal processing system comprising: The first positioning module is configured to acquire satellite signals of a satellite system, position an agricultural area based on the satellite signals, and obtain a first positioning map relative to a system coordinate system, the first positioning map including a first area and a second area, the first area corresponding to a forest area, and the second area corresponding to other areas outside the first area in the agricultural area. The second positioning module is configured to acquire three-dimensional point cloud data obtained by scanning the forest area by a laser radar, and obtain a second positioning map relative to the system coordinate system based on the three-dimensional point cloud data. The fusion module is configured to fuse the second positioning map into the first area of the first positioning map to obtain a third positioning map, so that an agricultural automation device performs agricultural operations on the agricultural area based on the third positioning map.

8. The positioning system of an agricultural area comprising a forest according to claim 7, characterized in that, The positioning system further includes: An electronic tag configured to be arranged on each tree in the forest, the electronic tag storing a unique identification code corresponding to the tree, and the electronic tag being capable of emitting a radio frequency signal. A radio frequency reader-writer configured to receive the radio frequency signal from the electronic tag. The second positioning module is specifically configured to acquire three-dimensional point cloud data obtained by scanning the forest area by a laser radar, and acquire the radio frequency signal from each tree; determine the identity of each tree in the three-dimensional point cloud data based on the radio frequency signal; process the three-dimensional point cloud data to calculate the distance and azimuth angle of each tree relative to the origin of the system coordinate system; and determine the second positioning map based on the distance and azimuth angle of all trees.

9. The positioning system of an agricultural area comprising a forest according to claim 8, characterized in that, The electronic tag is an active tag or a passive tag.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by the processor to implement the positioning method of the agricultural area containing the forest according to any one of claims 1-6.

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