CN112042415A - Equipment for controlling unmanned aerial vehicle to carry out plant pruning - Google Patents
Equipment for controlling unmanned aerial vehicle to carry out plant pruning Download PDFInfo
- Publication number
- CN112042415A CN112042415A CN202010964674.9A CN202010964674A CN112042415A CN 112042415 A CN112042415 A CN 112042415A CN 202010964674 A CN202010964674 A CN 202010964674A CN 112042415 A CN112042415 A CN 112042415A
- Authority
- CN
- China
- Prior art keywords
- trimming
- plant
- unmanned aerial
- aerial vehicle
- model
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/60—Type of objects
- G06V20/64—Three-dimensional objects
- G06V20/653—Three-dimensional objects by matching three-dimensional models, e.g. conformal mapping of Riemann surfaces
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
Abstract
The invention discloses a device for controlling an unmanned aerial vehicle to carry out plant pruning, which comprises a memory, a processor and a communication interface, wherein the processor is used for calling an executable program code stored in the memory to execute the following steps: controlling a scanning unmanned aerial vehicle to scan and obtain a 3D model of a plant; comparing the 3D model with library models stored in a database, planning a trimming route of the plant according to a difference area of the 3D model exceeding the library models and generating trimming route information; wherein, prune the route information including rough cut route information and fine cut route information, control communication interface with rough cut route information and fine cut route information transmit respectively to rough cut unmanned aerial vehicle and fine cut unmanned aerial vehicle, control rough cut unmanned aerial vehicle and carry out the first pruning to the plant, control fine cut unmanned aerial vehicle again and carry out the second pruning to the plant. The invention has the advantages of avoiding the danger of high-altitude trimming by manpower, improving the trimming precision and improving the trimming efficiency.
Description
Technical Field
The invention relates to the field of pruning, in particular to a device for controlling an unmanned aerial vehicle to prune plants.
Background
Most of the existing plant pruning is carried out by a robot walking on land, mainly aiming at the plant with lower height, and the pruning precision is lower, so that the model needing to be pruned cannot be obtained.
During the process of pruning the plants, the higher plants are also often needed to be pruned. At present, the plant with higher height is trimmed in a mode of manual lifting, the requirement on personnel engaged in high-altitude trimming of the plant is higher, the plant is trimmed in a mode of manual lifting, the risk is higher, the plant is trimmed in a mode of manual lifting, a series of inspections are needed to be made before the plant is trimmed, and therefore the trimming efficiency of the great reduction of the plant is trimmed in a mode of manual lifting.
Because the plant is pruned by the manual lifting mode, the pruning personnel observe and prune the plant through human eyes, the human eyes cannot accurately observe the plant, and the working personnel can be greatly limited in the process of pruning the plant at high altitude, so that the pruning precision is low, and the plant shape which is not required can not be pruned.
Disclosure of Invention
The invention aims to solve the problems of danger caused by high-altitude trimming, low efficiency and low precision of the high-altitude trimming, and provides a trimming method based on an unmanned aerial vehicle and equipment for controlling the unmanned aerial vehicle to trim plants.
The purpose of the invention is realized by the following technical scheme:
a pruning method based on an unmanned aerial vehicle comprises the following steps:
scanning a plant to be trimmed by a scanning unmanned aerial vehicle to obtain a 3D model of the plant;
comparing the 3D model with library models stored in a database, planning a trimming route of the plant according to a difference area of the 3D model exceeding the library models through comparing the library models with the 3D model, and generating trimming route information;
the trimming route information comprises rough trimming route information and fine trimming route information, the rough trimming route information and the fine trimming route information are respectively transmitted to the rough trimming unmanned aerial vehicle and the fine trimming unmanned aerial vehicle, the plant is firstly trimmed by the rough trimming unmanned aerial vehicle for the first time, and then the plant is trimmed by the fine trimming unmanned aerial vehicle for the second time, so that the new form of the plant is trimmed.
Preferably, the step of planning the pruning route of the plant according to the difference value of the 3D model exceeding the library model comprises:
dividing the 3D model into a plurality of original model layer structures with the same height H, obtaining the outline of each original model layer structure, comparing the outline of each original model layer structure with the outline of a library model layer structure, obtaining a difference area of the 3D model exceeding the outline of the library model layer structure, and planning the trimming route of the plant according to the difference area.
The 3D model is divided into a plurality of original model layer structures and the library model layer structures of the library model to be compared, the difference value area between the outline of each layer of original model layer structure and the library model layer structure of the library model is obtained, and therefore the trimming route of the plant is planned, the planned trimming route is more accurate, and the required new plant form is trimmed conveniently.
Preferably, the planning of the pruning route of the plant further comprises:
according to the depth of the difference area, if the depth of the difference area is larger than D1, dividing the difference area into a plurality of pruning areas, and generating corresponding pruning routes according to the plurality of pruning areas.
If the depth of the difference area is greater than D1, the difference area is divided into a plurality of trimming areas, so that when the depth of the difference area is too deep, the area can be trimmed through repeated trimming, and the trimming precision is improved, so that a required new plant form can be trimmed.
Preferably, the method further comprises: and selecting the rough-cutting unmanned aerial vehicle with the corresponding height H and suitable for the trimming cutter according to the height H of the original model layer structure at each time. The difference area can be trimmed more quickly and accurately by selecting the rough trimming unmanned aerial vehicle corresponding to the applicable trimming cutter.
Preferably, the method further comprises:
and obtaining the 3D model structure of the plant in the rough shearing or fine shearing process through the scanning unmanned aerial vehicle according to a preset time interval. The 3D model structure of the plant can be obtained timely through the preset time interval in the process of rough cutting or fine cutting, the trimming condition can be known timely, so that a corresponding trimming improvement scheme can be made timely when problems occur in the trimming process, and errors are avoided in the trimming process.
Preferably, the method further comprises:
the rough cutting unmanned aerial vehicle and the fine cutting unmanned aerial vehicle are arranged, and the camera of the rough cutting unmanned aerial vehicle acquires image information of a trimming process in real time. Through knowing in real time the fine trimming unmanned aerial vehicle and the image information of fine trimming unmanned aerial vehicle in the pruning process, be convenient for in time make corresponding pruning improvement scheme when the pruning in-process goes wrong, avoid appearing the error in the pruning process to improve the precision of pruning the plant, be convenient for prune out required plant new morphology.
Preferably, the rough-cutting unmanned aerial vehicle trims downwards from the top end of the plant, trims downwards from the top end of the plant when trimming to the lower end of the plant, and thus trims repeatedly. The rough-cut unmanned aerial vehicle is provided with the top end of the plant is trimmed downwards, the top end of the plant is trimmed downwards when the plant is trimmed to the lower end, and therefore the plant is trimmed repeatedly.
Preferably, the method further comprises:
and after trimming is finished, carrying out 3D scanning once every 20 to 30 days by the scanning unmanned aerial vehicle to obtain a 3D comparison model of the plant, and comparing the change of the 3D comparison model according to the 3D comparison model obtaining time to obtain the growth information of the plant. The scanning unmanned aerial vehicle acquires the 3D contrast model of the plant, changes of the 3D contrast model acquired at each time are compared, growth information of the plant is obtained, the plant can be trimmed in time through the obtained growth information of the plant, and overhaul of the plant is avoided.
Preferably, the pruning cycle information of the plant is generated according to the growth information of the plant. The plant can be trimmed in time by generating trimming cycle information of the plant, and the plant is prevented from being overhauled.
Preferably, a work schedule table of the unmanned aerial vehicle is generated according to the trimming cycle information of the plants. By generating the work schedule of the unmanned aerial vehicle, the unmanned aerial vehicle can be optimally assigned to trim, and the unmanned aerial vehicle can also trim plants according to the work schedule, so that the utilization rate of the unmanned aerial vehicle is improved.
An apparatus for controlling a drone for plant pruning, comprising: the device comprises a memory, a processor and a communication interface, wherein the memory is used for storing executable program codes and data, the communication interface is used for the device to carry out communication interaction with the unmanned aerial vehicle, and the processor is used for calling the executable program codes stored in the memory and executing the following steps:
controlling a scanning unmanned aerial vehicle to scan the plant to be trimmed through the communication interface to obtain a 3D model of the plant;
comparing the 3D model with library models stored in a database of the memory, planning a trimming route of the plant according to a difference area of the 3D model exceeding the library models through comparing the library models with the 3D model, and generating trimming route information;
the trimming route information comprises rough trimming route information and fine trimming route information, the communication interface is controlled to transmit the rough trimming route information and the fine trimming route information to the rough trimming unmanned aerial vehicle and the fine trimming unmanned aerial vehicle respectively, the rough trimming unmanned aerial vehicle is controlled to perform first trimming on the plant, and then the fine trimming unmanned aerial vehicle is controlled to perform second trimming on the plant, so that a new form of the plant is trimmed.
Preferably, the way for the processor to plan the pruning route of the plant according to the difference value of the 3D model exceeding the library model comprises:
dividing the 3D model into a plurality of original model layer structures with the same height H, obtaining the outline of each original model layer structure, comparing the outline of each original model layer structure with the outline of a library model layer structure, obtaining a difference area of the 3D model exceeding the outline of the library model layer structure, and planning the trimming route of the plant according to the difference area.
Preferably, the manner of the processor planning the trimming route of the plant according to the difference region includes:
according to the depth of the difference area, if the depth of the difference area is larger than D1, dividing the difference area into a plurality of pruning areas, and generating corresponding pruning routes according to the plurality of pruning areas.
Preferably, the processor is further configured to call the executable program code stored in the memory, and perform the following steps:
and selecting the rough-cutting unmanned aerial vehicle with the corresponding height H and suitable for the trimming cutter according to the height H of the original model layer structure at each time.
Preferably, the processor is further configured to call the executable program code stored in the memory, and perform the following steps:
and controlling the scanning unmanned aerial vehicle to acquire the 3D model structure of the plant in the rough shearing or fine shearing process according to a preset time interval.
Preferably, the processor is further configured to call the executable program code stored in the memory, and perform the following steps:
and controlling the camera arranged on the rough cutting unmanned aerial vehicle and the fine cutting unmanned aerial vehicle to acquire image information of the trimming process in real time.
Preferably, the rough-cutting unmanned aerial vehicle trims downwards from the top end of the plant, trims downwards from the top end of the plant when trimming to the lower end of the plant, and thus trims repeatedly.
Preferably, the processor is further configured to call the executable program code stored in the memory, and perform the following steps:
and after the trimming is finished, controlling the scanning unmanned aerial vehicle to perform 3D scanning once every 20 to 30 days to obtain a 3D comparison model of the plant, and comparing the change of the 3D comparison model according to the 3D comparison model obtaining time to obtain the growth information of the plant.
Preferably, the processor is further configured to call the executable program code stored in the memory, and perform the following steps:
and generating pruning cycle information of the plant according to the growth information of the plant.
Preferably, the processor is further configured to call the executable program code stored in the memory, and perform the following steps:
and generating a work schedule of the unmanned aerial vehicle according to the trimming period information of the plants.
The invention has the following beneficial effects: the method comprises the steps of obtaining a 3D model of a plant by controlling a scanning unmanned aerial vehicle, planning a trimming route and generating trimming route information by comparing the 3D model with a database model in a database, transmitting the trimming route information to a rough-cutting unmanned aerial vehicle and a fine-cutting unmanned aerial vehicle, controlling the rough-cutting unmanned aerial vehicle to perform first trimming on the plant to obtain a primary form of the plant, and controlling the fine-cutting unmanned aerial vehicle to perform second trimming on the primary form of the plant to obtain a final form of the plant. The plants are trimmed by controlling different unmanned aerial vehicles, so that the danger of manual high-altitude trimming is avoided, the trimming route planned is more accurate in shape selection and trimming compared with manual shape selection and trimming, the rough trimming unmanned aerial vehicle is used for carrying out first trimming, and the fine trimming unmanned aerial vehicle is used for carrying out second trimming, so that the trimming accuracy is further improved, and the new shape of the trimmed plants is consistent with the required new shape of the plants. Through controlling a scanning unmanned aerial vehicle, a rough cutting unmanned aerial vehicle, a fine cutting unmanned aerial vehicle to realize pruning the plant jointly, can be under the prerequisite of guaranteeing the pruning precision further improvement pruning efficiency.
Drawings
FIG. 1 is an overall scheme flow diagram of an embodiment of the present invention;
fig. 2 is a flow chart of transmission of trimming route information according to an embodiment of the present invention;
FIG. 3 is a flow chart of the steps of pruning a route according to an embodiment of the present invention;
FIG. 4 is a flow chart of the steps of pruning a route according to an embodiment of the present invention;
FIG. 5 is a schematic plan view of a 3D model according to an embodiment of the invention;
FIG. 6 is a schematic plan view of the library model of an embodiment of the present invention;
FIG. 7 is a schematic diagram of a hierarchical planning of a pruning route according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of a pruned route partition plan according to an embodiment of the present invention;
FIG. 9 is a flow chart of an embodiment of the present invention for generating a work shift table;
fig. 10 is a schematic structural diagram of an apparatus for controlling an unmanned aerial vehicle to perform plant pruning according to an embodiment of the present invention.
Detailed Description
The following describes preferred embodiments of the present invention and those skilled in the art will be able to realize the invention by using the related art in the following and will more clearly understand the innovative features and the advantages brought by the present invention.
As shown in fig. 1-9, there is provided a trimming method based on a drone, comprising the steps of:
s1, scanning a plant to be trimmed by a scanning unmanned aerial vehicle to obtain a 3D model of the plant;
s2, comparing the 3D model with a library model stored in a database, and comparing the library model with the 3D model;
s3, planning a trimming route of the plant according to the difference area of the 3D model exceeding the library model and generating trimming route information;
and S4, the trimming route information comprises rough trimming route information and fine trimming route information, the rough trimming route information and the fine trimming route information are respectively transmitted to the rough trimming unmanned aerial vehicle and the fine trimming unmanned aerial vehicle, the rough trimming unmanned aerial vehicle firstly trims the plant for the first time, and then the fine trimming unmanned aerial vehicle trims the plant for the second time, so that the new form of the plant is trimmed.
The method comprises the steps that a 3D model of a plant is obtained through the scanning unmanned aerial vehicle, then a trimming route is planned through comparison between the 3D model and a database model in a database, trimming route information is generated, the trimming route information is transmitted to the rough cutting unmanned aerial vehicle and the fine cutting unmanned aerial vehicle, the plant is trimmed for the first time through the rough cutting unmanned aerial vehicle to obtain a primary form of the plant, and then the fine cutting unmanned aerial vehicle trims the primary form of the plant for the second time to obtain a final form of the plant. The plants are trimmed through the unmanned aerial vehicle, so that the danger of manual high-altitude trimming is avoided, the planned trimming route is more accurate compared with manual shape selection trimming, the rough trimming unmanned aerial vehicle is used for carrying out first trimming, and the fine trimming unmanned aerial vehicle is used for carrying out second trimming, so that the trimming accuracy is further improved, and the new shape of the trimmed plants is consistent with the required new shape of the plants. Through a method that scanning unmanned aerial vehicle, a rough cut unmanned aerial vehicle, a fine cut unmanned aerial vehicle realize pruning the plant jointly, need not to change the restriction that pruning cutter also does not have artifical pruning like this, consequently, can further improvement under the prerequisite of guaranteeing the pruning precision prune efficiency like this.
In the embodiment of the invention, models of a plurality of plants are stored in the database, the 3D model is compared with the plurality of plant models in the database, one plant model closest to the 3D model is selected as the plant model to be trimmed, then the 3D model is compared with the selected plant model, the area exceeding the selected plant model is a difference area, finally, the trimming route of the plant is planned through the shape of the difference area, and trimming route information is generated. The plant can be accurately pruned through the pruning route information, and the pruning accuracy is guaranteed. In an embodiment of the present invention, the rough cutting path is a path for trimming a convex portion of the plant, i.e. a path beyond the selected plant model, and the fine cutting path is a path for trimming a concave portion of the plant or trimming a position with a fine portion, i.e. a path for trimming a concave structure or trimming a position with a fine position. The rough cutting route is trimmed through a rough cutting unmanned aerial vehicle, and the fine cutting route is trimmed through a fine cutting unmanned aerial vehicle.
In an embodiment of the invention, the trimming cutter arranged on the rough-cutting unmanned aerial vehicle is an electric saw, and the saw blade of the electric saw comprises a chain saw blade, a bar saw blade, a circular saw blade and the like, preferably, the chain saw blade, and large-area branches can be trimmed more conveniently through the chain saw blade. Of course, the pruning cutter can also be a chain cutter head, a circular saw blade and the like which are directly arranged on the rough-cutting unmanned aerial vehicle, and the chain cutter head is preferred, so that large-area branches can be pruned more conveniently through the chain cutter head.
In an embodiment of the present invention, the trimming tool disposed on the fine trimming drone is an electric saw, a saw blade of the electric saw is a circular saw blade, or the like, and the saw blade on the electric saw on the fine trimming drone is relatively smaller than the saw blade on the rough trimming drone so as to trim the concave portion and the fine portion, thereby improving the trimming accuracy. Of course, the trimming tool may also be a circular saw blade, a strip saw blade, or the like directly disposed on the fine trimming drone, and is preferably a circular saw blade by which a fine part on the plant can be trimmed more precisely.
In an embodiment of the present invention, as shown in fig. 7, in step S3, the step of planning the pruning route of the plant according to the difference value of the 3D model exceeding the library model includes:
dividing the 3D model into a plurality of original model layer structures with the same height H, obtaining the outline of each original model layer structure, comparing the outline of each original model layer structure with the outline of a library model layer structure, obtaining a difference area of the 3D model exceeding the outline of the library model layer structure, and planning the trimming route of the plant according to the difference area. The 3D model is divided into a plurality of original model layer structures and the library model layer structures of the library model to be compared, the difference value area between the outline of each original model layer structure and the library model layer structure of the library model is obtained, and therefore the trimming route of the plant is planned, the planned trimming route is more accurate, and the trimming is also more accurate through the trimming route so as to trim the needed new plant form.
In the embodiment of the invention, the height H is set according to the length of the trimming cutter head of the trimming cutter on the rough trimming unmanned aerial vehicle, so that when the rough trimming unmanned aerial vehicle trims the plant, the excess length of the branches on the original model layer structure of each layer can be trimmed at one time, and the trimming precision and the trimming efficiency are improved.
In the embodiment of the invention, the original model layer structures with the same height can be arranged firstly, and then the rough-cutting unmanned aerial vehicle with the trimming cutter heads with corresponding lengths can be selected according to the original model layer structures.
In an embodiment of the invention, the length of the trimming head is greater than or equal to the height H. Therefore, the rough cutting unmanned aerial vehicle can be used for trimming the lengths of the branches which are excessive on the structure of each layer of original model at one time. Thereby improving the trimming efficiency.
In an embodiment of the present invention, the height H is preferably 0.3 to 0.6 m, and such a height is selected to facilitate the unmanned aerial vehicle to carry the pruning tool, and to facilitate the rough-cutting unmanned aerial vehicle to prune the length of the branch that is added to the plant corresponding to each layer of the original model layer structure at one time.
In the embodiment of the invention, when the height of the difference area is greater than H1, the difference area is divided into a plurality of original model layer structures with the same height H, then the trimming parts corresponding to the original model layer structures of each layer are trimmed by the rough-cutting unmanned aerial vehicle and the fine-cutting unmanned aerial vehicle, and the trimming parts can be trimmed more finely by trimming the plants in layers, so that the trimming accuracy is improved.
In the embodiment of the present invention, the height H1 is 0.6 m, the plant is layered and pruned when the difference area is greater than 0.6 m, and if the difference area is less than 0.6 m, a rough-cutting unmanned aerial vehicle with a pruning head length of 0.6 m can be completely selected for pruning, and no layering is required, so that the 3D model is layered only when the pruning part is greater than 0.6 m.
In the example of step S3 of the present invention, as shown in fig. 3, 5 to 7, the 3D model is compared with the library model to obtain a difference region of the 3D model exceeding the library model, the height of the difference region is 1.8 meters, if trimming is directly performed without layering the heights of the difference area, trimming accuracy and flight of the unmanned aerial vehicle are affected, therefore, the difference area is divided into three layers of original model layer structures, the height of each layer of the original model layer structure is 0.6 m, of course, the difference area can also be divided into a plurality of original model layer structures according to actual conditions, then, comparing each layer of original model layer structure with the corresponding library model layer structure to obtain a difference region of each layer of original model layer structure exceeding the library model layer structure, and finally, pruning branches on the plants corresponding to the parts, needing pruning, of the original model layer structures on each layer through the pruning route.
In an embodiment of the present invention, as shown in fig. 8, the step S3 of planning the pruning route of the plant further includes:
according to the depth of the difference area, if the depth of the difference area is larger than D1, dividing the difference area into a plurality of pruning areas, and generating corresponding pruning routes according to the plurality of pruning areas.
If the depth of the difference area is greater than D1, the difference area is divided into a plurality of trimming areas, so that when the depth of the difference area is too deep, the area can be trimmed through repeated trimming, and the trimming precision is improved, so that a required new plant form can be trimmed.
In the embodiment of the invention, when the depth of the difference area is too deep, the trimming cutter on the rough-trimming unmanned aerial vehicle may affect the trimming of the unmanned aerial vehicle due to too long trimmed branches, and the too long trimmed branches may also affect the flight of multiple unmanned aerial vehicles, so that the difference area needs to be divided into multiple trimming areas for trimming. Avoid rough cut unmanned aerial vehicle with fine cut unmanned aerial vehicle receives the influence to influence pruning precision and pruning efficiency.
In an embodiment of the present invention, if the depth of the difference area is greater than 0.4 m, the difference area is divided into a plurality of trimming areas.
In the embodiment of the invention, the depth of each trimming area is preferably 0.2 to 0.4 meter, the difference area is divided into a plurality of trimming areas with the depths of 0.2 to 0.4 meter, so that the rough cutting unmanned aerial vehicle and the fine cutting unmanned aerial vehicle can trim conveniently, and the difference areas are finely layered, so that the trimming accuracy can be improved.
In the example of step S3 of the present invention, as shown in fig. 4 to 6 and 8, the 3D model is compared with the library model to obtain a difference region where the 3D model exceeds the library model, where the depth of a part of the difference region is 0.4 m, and if the part is not trimmed in a partition, the trimming precision and the flight of the drone are affected, so that the part is divided into two trimming regions, each of which has a depth of 0.2 m, and then a trimming route is planned, and the part is trimmed back and forth once by the rough-cut drone according to the planned trimming route, thereby improving the trimming precision.
In an embodiment of the present invention, the method further includes selecting, according to the height H of the original model layer structure each time, a rough-cutting unmanned aerial vehicle having an appropriate trimming cutter with a corresponding height H. The difference area can be trimmed more quickly and accurately by selecting the rough trimming unmanned aerial vehicle corresponding to the applicable trimming cutter. In an embodiment of the invention, the method further comprises:
and obtaining the 3D model structure of the plant in the rough shearing or fine shearing process through the scanning unmanned aerial vehicle according to a preset time interval. The 3D model structure of the plant can be obtained timely through the preset time interval in the process of rough cutting or fine cutting, the trimming condition can be known timely, so that a corresponding trimming improvement scheme can be made timely when problems occur in the trimming process, and errors are avoided in the trimming process.
In an embodiment of the present invention, the method step S4 further includes:
acquiring a 3D model structure of the plant in the rough shearing or fine shearing process by the scanning unmanned aerial vehicle every 5 to 10 minutes, and comparing the 3D model structure with a library model in a database;
if an error occurs in comparison with the library model, selecting a new model which is closest to the selected model, planning a new trimming route of the plant according to a difference area of the 3D model structure exceeding the new model, generating new trimming route information, and respectively transmitting the new trimming route information to the rough trimming unmanned aerial vehicle and the fine trimming unmanned aerial vehicle;
and if the database model is compared with the database model without error, pruning according to the original pruning route.
Therefore, the pruning route can be corrected in time, and the problem that the scheme cannot be improved in time due to errors in the pruning process is avoided.
In an embodiment of the present invention, the method step S4 further includes:
the rough cutting unmanned aerial vehicle and the fine cutting unmanned aerial vehicle are arranged, and the camera of the rough cutting unmanned aerial vehicle acquires image information of a trimming process in real time. Through knowing in real time the fine trimming unmanned aerial vehicle and the image information of fine trimming unmanned aerial vehicle in the pruning process, be convenient for in time make corresponding pruning improvement scheme when the pruning in-process goes wrong, avoid appearing the error in the pruning process to improve the precision of pruning the plant, be convenient for prune out required plant new morphology.
In an embodiment of the present invention, the camera is a high definition camera, and the method step S4 further includes:
sending the acquired image information to a display terminal through wireless modules on the rough cutting unmanned aerial vehicle and the fine cutting unmanned aerial vehicle, and judging whether an error occurs in the trimming process through manually knowing the image information in real time;
when an error occurs, the trimming work of the rough trimming unmanned aerial vehicle and the fine trimming unmanned aerial vehicle is manually suspended;
and when no error occurs, pruning according to the original pruning route.
Therefore, errors can be corrected in time, and the situation that the scheme cannot be improved in time due to the errors in the pruning process is avoided.
In an embodiment of the present invention, the rough-cutting unmanned aerial vehicle cuts downward from the top end of the plant, and cuts downward from the top end of the plant when cutting to the lower end of the plant, so as to repeatedly cut. The rough-cut unmanned aerial vehicle is provided with the top end of the plant is trimmed downwards, the top end of the plant is trimmed downwards when the plant is trimmed to the lower end, and therefore the plant is trimmed repeatedly.
In an embodiment of the present invention, the rough cutting drone in step S4 is trimmed from the top of the plant downwards by arranging the trimming cutter on the rough cutting drone transversely. This facilitates pruning of more shoots.
In an embodiment of the present invention, the rough-cut drone in step S4 is trimmed downward from the top end of the plant by a circle of trimming around the top end of the plant and then by a circle of downward trimming. Therefore, redundant branches on the plant can be trimmed more accurately, and the flying of the rough-cutting unmanned aerial vehicle cannot be influenced in the process of trimming the branches.
In the embodiment of the present invention, the rough-cut unmanned aerial vehicle in step S4 prunes from the top layer to the bottom layer of the prototype layer structure corresponding to each plant. Through pruning from top to bottom, can avoid the influence of the upper tree branch of plant rough cut unmanned aerial vehicle's flight to improve pruning efficiency.
In an embodiment of the present invention, as shown in fig. 9, the method further includes step S5:
and after trimming is finished, carrying out 3D scanning once every 20 to 30 days by the scanning unmanned aerial vehicle to obtain a 3D comparison model of the plant, and comparing the change of the 3D comparison model according to the 3D comparison model obtaining time to obtain the growth information of the plant. The scanning unmanned aerial vehicle acquires the 3D contrast model of the plant, changes of the 3D contrast model acquired at each time are compared, growth information of the plant is obtained, the plant can be trimmed in time through the obtained growth information of the plant, and overhaul of the plant is avoided. In an embodiment of the present invention, the scanning drone may scan every 10 to 20 days to obtain the 3D contrast model of the plant, so as to obtain more growth information of the plant. Of course, the scanning drone may scan every 20 to 30 days to obtain the 3D contrast model of the plant, so as to obtain the growth information of the plant.
In the embodiment of the present invention, as shown in fig. 9, step S6 is further included, generating trimming cycle information of the plant according to the growth information of the plant. The plant can be trimmed in time by generating trimming cycle information of the plant, and the plant is prevented from being overhauled.
In the embodiment of the present invention, as shown in fig. 9, the method further includes step S7, generating a work shift schedule of the rough cutting drone and the fine cutting drone according to the trimming cycle information of the plant. By generating the work schedule of the unmanned aerial vehicle, the unmanned aerial vehicle can be optimally assigned to trim, and the unmanned aerial vehicle can also trim plants according to the work schedule, so that the utilization rate of the unmanned aerial vehicle is improved.
As another embodiment of the present invention, as shown in fig. 1 to 9, a trimming method based on an unmanned aerial vehicle includes the following steps:
s1, scanning a plurality of plants to be pruned by manually operating a scanning unmanned aerial vehicle to obtain a 3D model of each plant;
s2, manually modeling the 3D model of each plant to obtain a comparison model, and comparing the comparison model with the 3D model;
s3, planning a trimming route of the plant according to the difference area of the 3D model exceeding the new model and generating trimming route information;
and S4, transmitting the trimming route information to a trimming unmanned aerial vehicle, and trimming the plants through the trimming unmanned aerial vehicle.
The scanning unmanned aerial vehicle is manually controlled to obtain a 3D model of a plurality of plants to be pruned, a comparison model is obtained by manually modeling the 3D model of each plant, a difference area can be obtained by comparing the 3D model with the comparison model, a pruning route is planned through the difference area, so that the pruning route is more accurate compared with the comparison of the 3D model with a library model stored in a database, and the comparison model is obtained by manually modeling, so that the plant can be pruned into any shape without being limited to the library model stored in the database.
In the embodiment of the invention, the scanning unmanned aerial vehicle is connected with the remote control device and the display terminal through the wireless module, and the storage device is arranged in the current terminal. The display terminal can be a mobile phone, a computer, a display screen and the like, and the storage device can be a RAM, a ROM, a hard disk, a floppy disk, a magnetic tape, a magnetic core memory, a bubble memory and the like.
In the embodiment of the invention, as shown in fig. 2, the trimming unmanned aerial vehicle comprises a rough trimming unmanned aerial vehicle and a fine trimming unmanned aerial vehicle, and the trimming efficiency is improved by trimming the plant by the two unmanned aerial vehicles.
In an embodiment of the present invention, as shown in fig. 2, in steps S3 and S4, the trimming route information includes rough trimming route information and fine trimming route information, the rough trimming route information and the fine trimming route information are respectively transmitted to the rough trimming unmanned aerial vehicle and the fine trimming unmanned aerial vehicle, the plant is trimmed for the first time by the rough trimming unmanned aerial vehicle, and then the plant is trimmed for the second time by the fine trimming unmanned aerial vehicle, so as to trim a new shape of the plant.
The precision of pruning can be further improved by pruning the plants twice, and the pruning cutter does not need to be replaced by arranging two unmanned aerial vehicles, so that the pruning efficiency can be improved on the premise of ensuring the pruning precision.
In an embodiment of the present invention, as shown in fig. 7, in step S3, the step of planning the pruning route of the plant according to the difference value of the 3D model exceeding the library model includes:
when the height of the difference region is more than 0.6 m;
dividing the 3D model into a plurality of original model layer structures with the same height of 0.4-0.6 m according to the height of the difference region, obtaining the outline of each original model layer structure, comparing the outline of each original model layer structure with the outline of the library model layer structure of the library model, obtaining the difference region of the outline of the 3D model exceeding the library model layer structure, and planning the trimming route of the plant according to the difference region.
When the height of the difference region is less than 0.6 m;
and the pruning route of the plant is directly planned through the difference area without layering the difference area.
The 3D model is divided into a plurality of original model layer structures and the library model layer structures of the library model to be compared, the difference value area between the outline of each original model layer structure and the library model layer structure of the library model is obtained, and therefore the trimming route of the plant is planned, the planned trimming route is more accurate, and the trimming is more accurate through the trimming route so as to trim the needed new plant form conveniently
In another embodiment of the present invention, in step S4, the trimming route information includes rough trimming route information and fine trimming route information, the rough trimming route information and the fine trimming route information are transmitted to the trimming drone, and the drone performs a first rough trimming and a second fine trimming on the plant, so as to obtain the rough trimming route information and the fine trimming route information. The unmanned aerial vehicle can be used for roughly shearing and finely shearing the plants, so that the number of the unmanned aerial vehicles can be saved, and multiple plants can be sheared simultaneously.
In an embodiment of the present invention, the first rough cutting is performed by a rough cutting tool provided on the unmanned aerial vehicle, and the second fine cutting is performed by a fine cutting tool provided on the unmanned aerial vehicle. Through set up different pruning cutters on pruning unmanned aerial vehicle, can be more accurate prune the plant.
In an embodiment of the present invention, as shown in fig. 8, the fine shearing tool and the rough shearing tool may be the same tool, but the fine shearing tool is smaller than the rough shearing tool to facilitate the second fine shearing.
In an embodiment of the present invention, in step S3, the planning of the pruning route of the plant further includes:
when the depth of the difference region is greater than 0.4 m;
dividing the difference area into a plurality of pruning areas with the depth of 0.2 to 0.4 according to the depth of the difference area, and generating corresponding pruning routes according to the plurality of pruning areas;
when the depth of the difference region is less than 0.4 m;
and the trimming route of the plant is directly planned through the difference area without partitioning the difference area.
The area is trimmed through repeated back-and-forth trimming, so that the trimming precision is improved, and a required new plant form is trimmed.
The embodiment of the invention also provides equipment for controlling the unmanned aerial vehicle to trim plants. The device for controlling the unmanned aerial vehicle to plant trimming can be used for executing the unmanned aerial vehicle-based trimming method provided by the embodiment. As shown in fig. 10, the apparatus for controlling a drone to perform plant pruning may include at least: memory 10, at least one processor 20, for example a CPU (central processing unit), and at least one communication interface 30, communication interface 30 may be used to establish a communication connection between the device and the drone, so that the device and the drone perform information interaction. Wherein the memory 10, processor 20, and communication interface 30 may be communicatively coupled via one or more buses. Those skilled in the art will appreciate that the configuration of the apparatus shown in fig. 10 is not intended to limit embodiments of the present invention, and may be a bus configuration, a star configuration, a combination of more or fewer components than those shown, or a different arrangement of components.
The memory 10 may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 10 may optionally be at least one memory device located remotely from the processor 20. Memory 10 may be used to store executable program code and data and embodiments of the present invention are not limited in this respect.
In the apparatus for controlling a drone to prune a plant shown in fig. 10, the processor 20 may be configured to call the executable program code stored in the memory 10 to perform the following steps:
controlling the scanning unmanned aerial vehicle to scan the plant to be trimmed through the communication interface 30 to obtain a 3D model of the plant;
comparing the 3D model with a library model stored in a database of the memory 10, planning a trimming route of a plant according to a difference area of the 3D model exceeding the library model through comparing the library model with the 3D model, and generating trimming route information;
wherein, should prune route information and include rough cut route information and fine cut route information, control communication interface 30 transmits rough cut route information and fine cut route information to rough cut unmanned aerial vehicle and fine cut unmanned aerial vehicle respectively, controls the rough cut unmanned aerial vehicle earlier and carries out the first pruning to the plant, controls the fine cut unmanned aerial vehicle again and carries out the second pruning to the plant to prune out the new attitude of plant.
Optionally, the way that the processor 20 plans the pruning route of the plant according to the difference value of the 3D model exceeding the library model may include:
divide into a plurality of former model layer structures that have the same height H with this 3D model, acquire the profile of every layer of former model layer structure, compare the profile of every layer of former model layer structure with the profile of the library model layer structure of this library model, acquire the difference region that this 3D model surpassed the profile of this library model layer structure, plan the route of pruning of plant according to this difference region.
Optionally, the way that the processor 20 plans the trimming route of the plant according to the difference region may include:
and according to the depth of the difference area, if the depth of the difference area is greater than D1, dividing the difference area into a plurality of pruning areas, and generating corresponding pruning routes according to the plurality of pruning areas.
Optionally, the processor 20 may be further configured to call the executable program code stored in the memory 10, and perform the following steps:
and selecting the rough-cutting unmanned aerial vehicle with the corresponding height H and suitable for the trimming cutter according to the height H of the original model layer structure each time.
Optionally, the processor 20 may be further configured to call the executable program code stored in the memory 10, and perform the following steps:
and controlling the scanning unmanned aerial vehicle to acquire the 3D model structure of the plant in the rough shearing or fine shearing process according to a preset time interval.
Optionally, the processor 20 may be further configured to call the executable program code stored in the memory 10, and perform the following steps:
the control sets up and obtains the image information of pruning process in real time at rough cut unmanned aerial vehicle and smart camera of cutting unmanned aerial vehicle.
Optionally, the rough-cut unmanned aerial vehicle is pruned downwards from the top end of the plant, pruned downwards from the top end of the plant when pruning to the lower end of the plant, and pruned repeatedly.
Optionally, the processor 20 may be further configured to call the executable program code stored in the memory 10, and perform the following steps:
control scanning unmanned aerial vehicle carries out once 3D scanning every 20 to 30 days after the pruning completion and obtains the 3D contrast model of plant, obtains the change of time contrast this 3D contrast model according to this 3D contrast model, acquires the growth information of plant.
Optionally, the processor 20 may be further configured to call the executable program code stored in the memory 10, and perform the following steps:
and generating pruning cycle information of the plants according to the growth information of the plants.
Optionally, the processor 20 may be further configured to call the executable program code stored in the memory 10, and perform the following steps:
and generating a work scheduling list of each unmanned aerial vehicle according to the trimming period information of the plants.
By implementing the equipment shown in fig. 10, plants are trimmed by controlling different unmanned aerial vehicles, so that the risk of trimming at high altitude manually is avoided, the planned trimming route is more accurate than manual shape selection trimming, the rough trimming unmanned aerial vehicle is used for carrying out first trimming, and the fine trimming unmanned aerial vehicle is used for carrying out second trimming, so that the trimming accuracy is further improved, and the new shape of the trimmed plants is consistent with the required new shape of the plants. Through controlling a scanning unmanned aerial vehicle, a rough cutting unmanned aerial vehicle, a fine cutting unmanned aerial vehicle to realize pruning the plant jointly, can be under the prerequisite of guaranteeing the pruning precision further improvement pruning efficiency.
The foregoing is a more detailed description of the present invention in connection with specific preferred embodiments thereof, and it is not intended that the specific embodiments of the present invention be limited to these descriptions. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (5)
1. An apparatus for controlling a drone to perform plant pruning, the apparatus comprising a memory for storing executable program code and data, a processor and a communication interface for the apparatus to communicatively interact with the drone, the processor being configured to invoke the executable program code stored in the memory to perform the steps of:
controlling a scanning unmanned aerial vehicle to scan the plant to be trimmed through the communication interface to obtain a 3D model of the plant;
comparing the 3D model with library models stored in a database of the memory, planning a trimming route of the plant according to a difference area of the 3D model exceeding the library models through comparing the library models with the 3D model, and generating trimming route information;
the trimming route information comprises rough trimming route information and fine trimming route information, the communication interface is controlled to transmit the rough trimming route information and the fine trimming route information to a rough trimming unmanned aerial vehicle and a fine trimming unmanned aerial vehicle respectively, the rough trimming unmanned aerial vehicle is controlled to perform first trimming on the plant, and then the fine trimming unmanned aerial vehicle is controlled to perform second trimming on the plant, so that a new form of the plant is trimmed;
the processor is further configured to call the executable program code stored in the memory to perform the following steps: controlling the scanning unmanned aerial vehicle to acquire a 3D model structure of the plant in the rough shearing or fine shearing process according to a preset time interval;
the processor is further configured to call the executable program code stored in the memory to perform the following steps: and controlling the camera arranged on the rough cutting unmanned aerial vehicle and the fine cutting unmanned aerial vehicle to acquire image information of the trimming process in real time.
2. The apparatus of claim 1, wherein the rough-cut drone is trimmed downward from the top of the plant, and then from the top of the plant to the lower end of the plant, and the rough-cut drone is trimmed downward from the top of the plant, so that the trimming is repeated.
3. The apparatus of claim 1, wherein the processor is further configured to invoke the executable program code stored in the memory to perform the steps of:
and after the trimming is finished, controlling the scanning unmanned aerial vehicle to perform 3D scanning once every 20 to 30 days to obtain a 3D comparison model of the plant, and comparing the change of the 3D comparison model according to the 3D comparison model obtaining time to obtain the growth information of the plant.
4. The apparatus of claim 3, wherein the processor is further configured to invoke the executable program code stored in the memory to perform the steps of:
and generating pruning cycle information of the plant according to the growth information of the plant.
5. The apparatus of claim 4, wherein the processor is further configured to invoke the executable program code stored in the memory to perform the steps of:
and generating a work schedule of the unmanned aerial vehicle according to the trimming period information of the plants.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010964674.9A CN112042415A (en) | 2018-08-14 | 2018-08-14 | Equipment for controlling unmanned aerial vehicle to carry out plant pruning |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010964674.9A CN112042415A (en) | 2018-08-14 | 2018-08-14 | Equipment for controlling unmanned aerial vehicle to carry out plant pruning |
| CN201810923062.8A CN108901431B (en) | 2018-08-14 | 2018-08-14 | Equipment for controlling unmanned aerial vehicle to carry out plant pruning |
Related Parent Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810923062.8A Division CN108901431B (en) | 2018-08-14 | 2018-08-14 | Equipment for controlling unmanned aerial vehicle to carry out plant pruning |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112042415A true CN112042415A (en) | 2020-12-08 |
Family
ID=64405459
Family Applications (3)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010965181.7A Withdrawn CN112052814A (en) | 2018-08-14 | 2018-08-14 | Equipment for controlling unmanned aerial vehicle to carry out plant pruning |
| CN202010964674.9A Withdrawn CN112042415A (en) | 2018-08-14 | 2018-08-14 | Equipment for controlling unmanned aerial vehicle to carry out plant pruning |
| CN201810923062.8A Active CN108901431B (en) | 2018-08-14 | 2018-08-14 | Equipment for controlling unmanned aerial vehicle to carry out plant pruning |
Family Applications Before (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010965181.7A Withdrawn CN112052814A (en) | 2018-08-14 | 2018-08-14 | Equipment for controlling unmanned aerial vehicle to carry out plant pruning |
Family Applications After (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810923062.8A Active CN108901431B (en) | 2018-08-14 | 2018-08-14 | Equipment for controlling unmanned aerial vehicle to carry out plant pruning |
Country Status (1)
| Country | Link |
|---|---|
| CN (3) | CN112052814A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115088500A (en) * | 2022-08-25 | 2022-09-23 | 中化现代农业有限公司 | Pruning system for fruit trees and using method |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110301248A (en) * | 2019-07-30 | 2019-10-08 | 南京林业大学 | A kind of intelligent cutting system and method based on unmanned plane |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104641965A (en) * | 2015-03-11 | 2015-05-27 | 叶葵 | Road greening equipment and use method thereof |
| CN105009959A (en) * | 2015-06-18 | 2015-11-04 | 滁州市瑞景园林建设有限公司 | Hedge training and pruning method used for garden landscaping |
| CN105052573A (en) * | 2015-07-22 | 2015-11-18 | 闫胜昝 | Vehicle-mounted type rapid trimming device of highway green plants |
| CN107404848A (en) * | 2015-01-20 | 2017-11-28 | 埃尔瓦有限公司 | System and method for trimming plant |
| CN206776143U (en) * | 2017-03-31 | 2017-12-22 | 王亮 | A kind of road separator greening shearing device |
| CN108243761A (en) * | 2018-01-24 | 2018-07-06 | 广东容祺智能科技有限公司 | The tree potted landscape clipping device and pruning method of a kind of unmanned plane |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070173974A1 (en) * | 2006-01-25 | 2007-07-26 | Chyi-Yeu Lin | Device and method for interacting with autonomous robot |
| US9994498B2 (en) * | 2009-07-29 | 2018-06-12 | The United States Of America As Represented By The Secretary Of The Navy | Renewable high density turbine and diesel fuels from sesquiterpenes |
| CN104221732B (en) * | 2014-09-29 | 2016-09-21 | 华南理工大学 | A kind of branch prunes the method pulverized robot and prune broken branch |
| US9516806B2 (en) * | 2014-10-10 | 2016-12-13 | Irobot Corporation | Robotic lawn mowing boundary determination |
| CN105881543A (en) * | 2014-11-26 | 2016-08-24 | 李书申 | Humanoid intelligent robot and working method thereof |
| CN105710045B (en) * | 2016-03-15 | 2019-01-25 | 上海交通大学 | The system and method for green plant phenotype and sorting |
| CN105794502B (en) * | 2016-04-12 | 2018-09-25 | 山东国兴智能科技有限公司 | A kind of full-automatic branch pruning machine people and pruning method |
| DE102016219457A1 (en) * | 2016-10-07 | 2018-04-12 | Mbda Deutschland Gmbh | Method and system for the defense against threat missiles in the form of controllable unmanned small aircraft |
-
2018
- 2018-08-14 CN CN202010965181.7A patent/CN112052814A/en not_active Withdrawn
- 2018-08-14 CN CN202010964674.9A patent/CN112042415A/en not_active Withdrawn
- 2018-08-14 CN CN201810923062.8A patent/CN108901431B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107404848A (en) * | 2015-01-20 | 2017-11-28 | 埃尔瓦有限公司 | System and method for trimming plant |
| CN104641965A (en) * | 2015-03-11 | 2015-05-27 | 叶葵 | Road greening equipment and use method thereof |
| CN105009959A (en) * | 2015-06-18 | 2015-11-04 | 滁州市瑞景园林建设有限公司 | Hedge training and pruning method used for garden landscaping |
| CN105052573A (en) * | 2015-07-22 | 2015-11-18 | 闫胜昝 | Vehicle-mounted type rapid trimming device of highway green plants |
| CN206776143U (en) * | 2017-03-31 | 2017-12-22 | 王亮 | A kind of road separator greening shearing device |
| CN108243761A (en) * | 2018-01-24 | 2018-07-06 | 广东容祺智能科技有限公司 | The tree potted landscape clipping device and pruning method of a kind of unmanned plane |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115088500A (en) * | 2022-08-25 | 2022-09-23 | 中化现代农业有限公司 | Pruning system for fruit trees and using method |
| CN115088500B (en) * | 2022-08-25 | 2022-11-18 | 中化现代农业有限公司 | Pruning system for fruit trees and using method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108901431A (en) | 2018-11-30 |
| CN112052814A (en) | 2020-12-08 |
| CN108901431B (en) | 2020-11-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108901431B (en) | Equipment for controlling unmanned aerial vehicle to carry out plant pruning | |
| CN110754204B (en) | Lawn three-dimensional pattern trimming robot system and method | |
| CN102854884B (en) | The method that the weather information of aerial vehicle trajectory is provided to flight management system | |
| CN107314772B (en) | Unmanned aerial vehicle self-learning waypoint track flight method and system thereof | |
| CN103412574B (en) | Job management device of unmanned helicopter | |
| CN109035869A (en) | The generation method and device in unmanned plane course line | |
| CN110301248A (en) | A kind of intelligent cutting system and method based on unmanned plane | |
| CN103592947A (en) | Farm-oriented aerial vehicle safe operation flight monitoring device and control algorithm thereof | |
| CN109005997A (en) | Air-ground coordination operation orchard trimmer based on independent navigation | |
| JP2022527029A (en) | Systems, equipment, and methods for remote-controlled robots | |
| CN205670261U (en) | Unmanned vehicle makes a return voyage system and unmanned vehicle thereof | |
| JP6656038B2 (en) | Grape cultivation management method | |
| CN108243761A (en) | The tree potted landscape clipping device and pruning method of a kind of unmanned plane | |
| CN113538660A (en) | Power transmission and transformation project acceptance method based on BIM and point cloud measurement | |
| CN113375674A (en) | Curve path generation method, device and equipment and readable storage medium | |
| CN105159290A (en) | Lawn trimming system and robot based on Internet of Things | |
| CN108646672B (en) | Automatic matching method and system for numerical control punching | |
| CN109032180A (en) | A kind of pruning method based on unmanned plane | |
| CN107730103B (en) | Spatial data processing flow control method | |
| CN112180987A (en) | Cooperative operation method, system, device, computer equipment and storage medium | |
| CN206178480U (en) | Unmanned aerial vehicle is pruned to intelligence based on machine vision | |
| CN110889596B (en) | Construction plan scheduling method and system for railway engineering line | |
| US20220405690A1 (en) | Information processing apparatus, information processing method, and storage medium | |
| CN114815879A (en) | Numbering method, system, storage medium and equipment | |
| DE102004031933A1 (en) | Computer-aided planning process for a travel plan |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20201208 |