CN110398978A - One kind herding path planning system based on Forage-Livestock Balance model degree - Google Patents
One kind herding path planning system based on Forage-Livestock Balance model degree Download PDFInfo
- Publication number
- CN110398978A CN110398978A CN201910332547.4A CN201910332547A CN110398978A CN 110398978 A CN110398978 A CN 110398978A CN 201910332547 A CN201910332547 A CN 201910332547A CN 110398978 A CN110398978 A CN 110398978A
- Authority
- CN
- China
- Prior art keywords
- forage
- path planning
- planning system
- livestock
- balance 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.)
- Pending
Links
- 244000144972 livestock Species 0.000 claims abstract description 14
- 230000000153 supplemental effect Effects 0.000 claims abstract description 6
- 244000144980 herd Species 0.000 claims description 24
- 238000004891 communication Methods 0.000 claims description 4
- 241001465754 Metazoa Species 0.000 claims description 2
- 230000005611 electricity Effects 0.000 claims 1
- 230000008450 motivation Effects 0.000 claims 1
- 244000144977 poultry Species 0.000 claims 1
- 239000000523 sample Substances 0.000 claims 1
- 230000000694 effects Effects 0.000 abstract description 3
- 238000009304 pastoral farming Methods 0.000 description 40
- 238000000034 method Methods 0.000 description 14
- 241001494479 Pecora Species 0.000 description 11
- 244000144992 flock Species 0.000 description 7
- 230000004888 barrier function Effects 0.000 description 6
- 238000011156 evaluation Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 238000009826 distribution Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 244000025254 Cannabis sativa Species 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000004387 environmental modeling Methods 0.000 description 2
- 230000005389 magnetism Effects 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000003252 repetitive effect Effects 0.000 description 2
- 239000002028 Biomass Substances 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 241000894007 species Species 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
- G05D1/0808—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
Landscapes
- Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
One kind herding path planning system based on Forage-Livestock Balance model degree, belongs to technical field of livestock husbandry, and herding path planning system based on Forage-Livestock Balance model degree includes that control section, flight algorithm are communicated with software and hardware;Control section includes order and data receiver radio station, data volatilization radio station, GPS module, supplemental functionality, inertial sensor, geomagnetic sensor, height sensor, engine speed sensor, power module, attitude algorithm and control CPU, ground control station, PWM, driver for isolating receives and return data radio station module, three-axis gyroscope, three axis accelerometer, twin shaft high-precision tilt angle meter, absolute value barometer and steering engine, attitude algorithm and control CPU acquire the operating rate of engine in real time, ground control station adjusts the revolving speed of engine as needed, it is starting point by setting final goal node, morning be can achieve from livestock shed, the effect of livestock shed is returned at night.
Description
Technical field
Present invention relates particularly to one kind to herd path planning system based on Forage-Livestock Balance model degree.
Background technique
Herded based on Forage-Livestock Balance model degree need to use automatic control in path planning software systems, software front and back is opened
The relevant technologies such as hair, the communication of flight algorithm, software and hardware.
Summary of the invention
Grassland resources caused by overgrazing, which is seriously degenerated, has become animal husbandry economy development and grassland ecology balance
Major obstacle.Different grazing strength to soil property, COMMUNITY CHARACTERISTICS structure and biomass and species diversity and productivity all
There are different degrees of influences.Adequately and reasonably using Natural Grassland Resource, to maintain the sustainable development of grassland ecosystem,
It avoids overgrazing, and provides flock of sheep spatial and temporal distributions information in real time, effectively to promote herding already for livestock management department
Ji development, it is proposed that scientific rotation grazing route, instructs herdsman's conservative distribution of burden.
Science of programming rotation grazing route is broadly divided into two parts: estimating different grassland column grazing intensities first;Then into
Row rotation grazing route planning, core are to avoid the column that grazing intensity is more than stocking rate.
The purpose of the application is in view of the problems of the existing technology, to provide one kind based on Forage-Livestock Balance model degree and herd road
Diameter planning system.
The purpose of the application solves by the following technical programs:
One kind herding path planning system based on Forage-Livestock Balance model degree, which is characterized in that described to be based on Forage-Livestock Balance mould
It includes that control section, flight algorithm are communicated with software and hardware that type degree, which herds path planning system,;
The control section include order and data receiver radio station, data volatilization radio station, GPS module, supplemental functionality,
Inertial sensor, geomagnetic sensor, height sensor, engine speed sensor, power module, attitude algorithm and control CPU,
Ground control station, PWM, driver for isolating receives and return data radio station module, three-axis gyroscope, three axis accelerometer, twin shaft
High-precision tilt angle meter, absolute value barometer and steering engine, the attitude algorithm and control CPU acquire the work speed of engine in real time
Degree, the ground control station adjust the revolving speed of engine as needed, and the attitude algorithm and control CPU carry out the reality of each sensing
When resolve and according to control algolithm output pwm signal, the reception and return data radio station module are postbacked for ground control;
The software and hardware communication includes that locating collar described in locating collar can send positioning signal to earth station, ground in real time
It stands and livestock position signal is sent to unmanned plane in real time, unmanned plane controls flight path according to Intelligent flight algorithm, passes through sound
Livestock is rushed into destination.
Further, a kind of that path planning system, the power module and each module are herded based on Forage-Livestock Balance model degree
It is connected.
Further, a kind of that path planning system, the data receiver radio station, data are herded based on Forage-Livestock Balance model degree
Volatilization radio station, GPS module are connected with serial ports 1, serial ports 2 and serial ports 3 respectively.
Further, a kind of to herd path planning system based on Forage-Livestock Balance model degree, the inertial sensor, earth magnetism pass
Sensor, height sensor are in parallel with interface 1.
Further, a kind of that path planning system, the engine speed sensor are herded based on Forage-Livestock Balance model degree
It is connected with interface 2.
Further, a kind of that path planning system is herded based on Forage-Livestock Balance model degree, the supplemental functionality with connect
Mouth 3 is connected.
Further, a kind of that path planning system, the PWM and driver for isolating phase are herded based on Forage-Livestock Balance model degree
Connection.
Further, a kind of that path planning system, the attitude algorithm and control CPU are herded based on Forage-Livestock Balance model degree
It is integrated on one piece of mainboard with each serial ports, interface and power supply.
Further, a kind of that path planning system, the steering engine real-time control aircraft are herded based on Forage-Livestock Balance model degree
Flight attitude, realize closed-loop control.
Further, a kind of to herd path planning system based on Forage-Livestock Balance model degree, the control section is also wrapped
Upload link is included, for each sensing data, resolving posture and control data to be had selection or all send back ground control in real time
System station.
The application has the following advantages compared with prior art:
(1) the application is starting point by setting final goal node, can achieve morning from livestock shed, returns at night
The effect of livestock shed.
(2) the application can achieve maximum coverage rate, so that flock of sheep track is uniformly distributed in grass by algorithm optimization
), the smallest repetitive rate is combined, the number that can look for food to avoid the same area excessively causes to be distributed overgrazing.
(3) the application can refer to that previous cycle marks overgrazing by unmanned plane with avoiding barrier, the barrier
Region.
(4) since the application application scenarios are prairie or grassland, no road, building mark etc. are i.e. without considering road
Net constraint.
Detailed description of the invention
Attached drawing 1 is this system unmanned aerial vehicle control system block diagram;
Attached drawing 2 is that the application herds route planning schematic diagram.
Specific embodiment
To facilitate the understanding of the present invention, the present invention is described more fully below with reference to relevant drawings, attached drawing
In give several embodiments of the invention, but the present invention can be realized by different forms, however it is not limited to text institute
The embodiment of description, opposite, it theses embodiments are provided so that more thorough and comprehensive to present disclosure.
Need to illustrate when, when element is referred to as " being fixedly arranged on " another element, it can directly on the other element
There may also be elements placed in the middle, and when an element is considered as " connection " another element, it can be directly to separately
One element may be simultaneously present centering elements, term as used herein "vertical", "horizontal", "left" and "right"
And similar statement is for illustrative purposes only.
Unless otherwise defined, all technical and scientific terms used herein and belong to technical field of the invention
The meaning that technical staff usually connects is identical, and term knowledge as used herein in the specification of the present invention is in order to describe to have
The purpose of the embodiment of body, it is not intended that in the limitation present invention, term " and or " used herein includes one or more phases
Any and all combinations of the listed item of pass.
Embodiment one
As shown in Figure 1, a kind of herd path planning system based on Forage-Livestock Balance model degree, which is characterized in that described to be based on
It includes that control section, flight algorithm are communicated with software and hardware that Forage-Livestock Balance model degree, which herds path planning system,;
The control section include order and data receiver radio station, data volatilization radio station, GPS module, supplemental functionality,
Inertial sensor, geomagnetic sensor, height sensor, engine speed sensor, power module, attitude algorithm and control CPU,
Ground control station, PWM, driver for isolating receives and return data radio station module, three-axis gyroscope, three axis accelerometer, twin shaft
High-precision tilt angle meter, absolute value barometer and steering engine, the attitude algorithm and control CPU acquire the work speed of engine in real time
Degree, the ground control station adjust the revolving speed of engine as needed, and the attitude algorithm and control CPU carry out the reality of each sensing
When resolve and according to control algolithm output pwm signal, the reception and return data radio station module are postbacked for ground control;
The software and hardware communication includes that locating collar described in locating collar can send positioning signal to earth station, ground in real time
It stands and livestock position signal is sent to unmanned plane in real time, unmanned plane controls flight path according to Intelligent flight algorithm, passes through sound
Livestock is rushed into destination.
Further, a kind of that path planning system, the power module and each module are herded based on Forage-Livestock Balance model degree
It is connected.
Further, a kind of that path planning system, the data receiver radio station, data are herded based on Forage-Livestock Balance model degree
Volatilization radio station, GPS module are connected with serial ports 1, serial ports 2 and serial ports 3 respectively.
Further, a kind of to herd path planning system based on Forage-Livestock Balance model degree, the inertial sensor, earth magnetism pass
Sensor, height sensor are in parallel with interface 1.
Further, a kind of that path planning system, the engine speed sensor are herded based on Forage-Livestock Balance model degree
It is connected with interface 2.
Further, a kind of that path planning system is herded based on Forage-Livestock Balance model degree, the supplemental functionality with connect
Mouth 3 is connected.
Further, a kind of that path planning system, the PWM and driver for isolating phase are herded based on Forage-Livestock Balance model degree
Connection.
Further, a kind of that path planning system, the attitude algorithm and control CPU are herded based on Forage-Livestock Balance model degree
It is integrated on one piece of mainboard with each serial ports, interface and power supply.
Further, a kind of that path planning system, the steering engine real-time control aircraft are herded based on Forage-Livestock Balance model degree
Flight attitude, realize closed-loop control.
Further, a kind of to herd path planning system based on Forage-Livestock Balance model degree, the control section is also wrapped
Upload link is included, for each sensing data, resolving posture and control data to be had selection or all send back ground control in real time
System station.
Embodiment two
As shown in Fig. 2, a kind of method that the present embodiment specifically illustrates programme path, a kind of rotation grazing route planning method, institute
State rotation grazing route planning method the following steps are included:
S1: different grassland column grazing intensities are estimated first;
S2: and then rotation grazing route planning is carried out, core is to avoid the column that grazing intensity is more than stocking rate;
S3: carrying out environmental modeling, that is, actual physical space be abstracted into the abstract space that algorithm is capable of handling, real
Now mutual mapping;
S4: then carrying out route searching, in conjunction with the traversal formula optimum path problems and continuous domain range within the scope of discrete domain
Effective combination of interior traversal formula path planning problem selection path planning algorithm;
S5: finally carrying out path smooth, for further processing with smoothly become a practicable path.
Further, a kind of rotation grazing route planning method, in step sl, the estimation of the grazing intensity is put based on flock of sheep
Herd space-time trajectory data, including longitude and latitude, acquisition time, pin numbers field information.
Further, a kind of rotation grazing route planning method, the estimation of the grazing intensity the following steps are included:
S11: each grassland version of different time sections is obtained using distributed grazing intensity evaluation method first, in accordance with some cycles
The grazing intensity of block;
S12: finally, the grassland column that grazing intensity is greater than stocking rate is labeled as overgrazing column.
Further, a kind of rotation grazing route planning method, in step s 11, the distribution grazing intensity evaluation method
Thought be that will clean and pretreated track data of herding carries out basic cluster, for obtained k cluster (k grassland edition
Block), it calculates separately its real area and counts track data point number (being converted into sheep number of elements) in cluster, pass through cluster area and the cluster
The ratio between interior sheep number of elements obtains corresponding grazing intensity.
Further, a kind of rotation grazing route planning method, the final goal node of the rotation grazing route planning are starting point.
Further, a kind of rotation grazing route planning method, the rotation grazing route planning is without considering road network.
Further, a kind of rotation grazing route planning method, the rotation grazing route planning include that flock of sheep track is uniformly distributed in
Grassland principle and avoid the same area look for food number excessively cause be distributed overgrazing principle.
Further, a kind of rotation grazing route planning method, the rotation grazing route planning further include avoiding barrier principle, i.e.,
Refer to that pastoral area domain is already expired in previous cycle mark.
Further, a kind of the characteristics of rotation grazing route planning method, the traversal formula optimum path problems be starting point only
One, final goal node is starting point.
Further, a kind of the characteristics of rotation grazing route planning method, the traversal formula path planning problem be require it is most short
Path go covering workspace every nook and cranny.
The application has the following advantages compared with prior art:
(1) the application is starting point by setting final goal node, can achieve morning from livestock shed, returns at night
The effect of livestock shed.
(2) the application can achieve maximum coverage rate, so that flock of sheep track is uniformly distributed in grass by algorithm optimization
), the smallest repetitive rate is combined, the number that can look for food to avoid the same area excessively causes to be distributed overgrazing.
(3) the application can refer to that previous cycle marks overgrazing by unmanned plane with avoiding barrier, the barrier
Region.
(4) since the application application scenarios are prairie or grassland, no road, building mark etc. are i.e. without considering road
Net constraint.
It is specifically described the principle of the application below, this method first step needs to estimate different grassland column grazing intensities, puts
The estimation for herding intensity is based on flock of sheep and herds space-time trajectory data, including longitude and latitude, acquisition time, pin numbers field information.It is first
First the grazing intensity of each grassland column of different time sections is obtained using distributed grazing intensity evaluation method according to some cycles.Most
Afterwards, the grassland column that grazing intensity is greater than stocking rate is labeled as overgrazing column.
Distributed grazing intensity evaluation method thought is will to clean to carry out basic gather with pretreated track data of herding
Class calculates separately its real area and counts the (folding of data point number in track in cluster for obtained k cluster (k grassland column)
It is combined into sheep number of elements), corresponding grazing intensity is obtained by the ratio between cluster area and sheep number of elements in the cluster.,
Rotation grazing route planning is carried out below, and rotation grazing route planning is actually to push science to herdsman according to the fixed cycle
Reasonably herd route.In rotation grazing route planning, its main feature is that: first, final goal node is starting point, i.e. morning from canopy
Hair is irised out, returns to livestock shed at night;Second, maximum coverage rate, so that flock of sheep track is uniformly distributed in grassland;And it is the smallest heavy
Multiple rate avoids the same area number of looking for food from excessively causing to be distributed overgrazing;Third, avoiding barrier refer here to previous cycle
Pastoral area domain is already expired in mark;4th, grassland is without road, building etc., i.e., without considering road network.
Based on the above feature, environmental modeling is carried out first, that is, actual physical space is abstracted into algorithm to locate
The abstract space of reason realizes mutual mapping.Then route searching is carried out, in conjunction with the optimal road of traversal formula within the scope of discrete domain
Traversal formula path planning within the scope of diameter problem (its main feature is that starting point is unique, final goal node is starting point) and continuous domain
Effective combination of problem (its main feature is that shortest path is required to go to cover the every nook and cranny of workspace) selection path planning algorithm.
Finally carry out path smooth, for further processing with smoothly become a practicable path.
Above embodiments are only to illustrate the technical idea of the application, and the protection scope of the application cannot be limited with this, all
According to the technical idea provided by the invention, any changes made on the basis of the technical scheme each falls within the scope of the present invention
Within;The technology that the application is not directed to can be realized by the prior art.
Claims (10)
1. one kind herds path planning system based on Forage-Livestock Balance model degree, which is characterized in that described to be based on Forage-Livestock Balance model
It includes that control section, flight algorithm are communicated with software and hardware that degree, which herds path planning system,;
The control section includes order and data receiver radio station, data volatilization radio station, GPS module, supplemental functionality, inertia
Sensor, geomagnetic sensor, height sensor, engine speed sensor, power module, attitude algorithm and control CPU, ground
Control station, PWM, driver for isolating receive and return data radio station module, three-axis gyroscope, three axis accelerometer, twin shaft are high-precision
Inclinometer, absolute value barometer and steering engine are spent, the attitude algorithm and control CPU acquire the operating rate of engine in real time,
The ground control station adjusts the revolving speed of engine as needed, and the attitude algorithm and control CPU carry out the real-time of each sensing
It resolves and is postbacked according to control algolithm output pwm signal, the reception and return data radio station module for ground control;
The software and hardware communication includes that locating collar described in locating collar can send positioning signal to earth station in real time, and earth station will
Livestock position signal is sent to unmanned plane in real time, and unmanned plane controls flight path according to Intelligent flight algorithm, by sound by domestic animal
Poultry rushes to destination.
2. according to claim 1 herd path planning system based on Forage-Livestock Balance model degree, it is characterised in that: the electricity
Source module is connected with each module.
3. according to claim 1 herd path planning system based on Forage-Livestock Balance model degree, it is characterised in that: the number
It is connected respectively with serial ports 1, serial ports 2 and serial ports 3 according to reception radio station, data volatilization radio station, GPS module.
4. according to claim 1 herd path planning system based on Forage-Livestock Balance model degree, it is characterised in that: described used
Property sensor, geomagnetic sensor, height sensor are in parallel with interface 1.
5. according to claim 1 herd path planning system based on Forage-Livestock Balance model degree, it is characterised in that: the hair
Motivation speed probe is connected with interface 2.
6. according to claim 1 herd path planning system based on Forage-Livestock Balance model degree, it is characterised in that: described auxiliary
Functional module is helped to be connected with interface 3.
7. according to claim 1 herd path planning system based on Forage-Livestock Balance model degree, it is characterised in that: described
PWM is connected with driver for isolating.
8. according to claim 1 herd path planning system based on Forage-Livestock Balance model degree, it is characterised in that: the appearance
State resolves and control CPU is integrated on one piece of mainboard with each serial ports, interface and power supply.
9. according to claim 1 herd path planning system based on Forage-Livestock Balance model degree, it is characterised in that: the rudder
The flight attitude of machine real-time control aircraft realizes closed-loop control.
10. according to claim 1 herd path planning system based on Forage-Livestock Balance model degree, it is characterised in that: described
The control section further includes uploading link, for each sensing data, resolving posture and control data to be had selection or whole
Ground control station is sent back in real time.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910332547.4A CN110398978A (en) | 2019-04-24 | 2019-04-24 | One kind herding path planning system based on Forage-Livestock Balance model degree |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910332547.4A CN110398978A (en) | 2019-04-24 | 2019-04-24 | One kind herding path planning system based on Forage-Livestock Balance model degree |
Publications (1)
Publication Number | Publication Date |
---|---|
CN110398978A true CN110398978A (en) | 2019-11-01 |
Family
ID=68322934
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201910332547.4A Pending CN110398978A (en) | 2019-04-24 | 2019-04-24 | One kind herding path planning system based on Forage-Livestock Balance model degree |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN110398978A (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114070862A (en) * | 2021-10-15 | 2022-02-18 | 中国科学院地理科学与资源研究所 | Livestock raising control method and system based on Internet of things and readable storage medium |
Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102902276A (en) * | 2012-10-12 | 2013-01-30 | 大连理工大学 | Flying control system based on polarized light sensor |
CN106527491A (en) * | 2016-11-21 | 2017-03-22 | 南京航空航天大学 | Control system for fixed-wing unmanned aerial vehicle and horizontal and lateral flight track control method |
CN106647754A (en) * | 2016-12-20 | 2017-05-10 | 安徽农业大学 | Path planning method for orchard tracked robot |
CN107229289A (en) * | 2017-07-31 | 2017-10-03 | 内蒙古智牧溯源技术开发有限公司 | A kind of unmanned plane grazing management system |
CN107291102A (en) * | 2017-07-31 | 2017-10-24 | 内蒙古智牧溯源技术开发有限公司 | A kind of unmanned plane grazing system |
CN107505833A (en) * | 2017-08-01 | 2017-12-22 | 南京理工大学 | A kind of flight control system and method based on embedded OS |
CN107728642A (en) * | 2017-10-30 | 2018-02-23 | 北京博鹰通航科技有限公司 | A kind of UAV Flight Control System and its method |
CN108207653A (en) * | 2018-01-31 | 2018-06-29 | 佛山市神风航空科技有限公司 | A kind of grazing system based on unmanned plane |
CN109376810A (en) * | 2018-08-29 | 2019-02-22 | 内蒙古智牧溯源技术开发有限公司 | Livestock based on clustering overgrazing method for early warning by stages |
-
2019
- 2019-04-24 CN CN201910332547.4A patent/CN110398978A/en active Pending
Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102902276A (en) * | 2012-10-12 | 2013-01-30 | 大连理工大学 | Flying control system based on polarized light sensor |
CN106527491A (en) * | 2016-11-21 | 2017-03-22 | 南京航空航天大学 | Control system for fixed-wing unmanned aerial vehicle and horizontal and lateral flight track control method |
CN106647754A (en) * | 2016-12-20 | 2017-05-10 | 安徽农业大学 | Path planning method for orchard tracked robot |
CN107229289A (en) * | 2017-07-31 | 2017-10-03 | 内蒙古智牧溯源技术开发有限公司 | A kind of unmanned plane grazing management system |
CN107291102A (en) * | 2017-07-31 | 2017-10-24 | 内蒙古智牧溯源技术开发有限公司 | A kind of unmanned plane grazing system |
CN107505833A (en) * | 2017-08-01 | 2017-12-22 | 南京理工大学 | A kind of flight control system and method based on embedded OS |
CN107728642A (en) * | 2017-10-30 | 2018-02-23 | 北京博鹰通航科技有限公司 | A kind of UAV Flight Control System and its method |
CN108207653A (en) * | 2018-01-31 | 2018-06-29 | 佛山市神风航空科技有限公司 | A kind of grazing system based on unmanned plane |
CN109376810A (en) * | 2018-08-29 | 2019-02-22 | 内蒙古智牧溯源技术开发有限公司 | Livestock based on clustering overgrazing method for early warning by stages |
Non-Patent Citations (1)
Title |
---|
文雯;周丁扬;李广泳;赵文武;曹军骥;: "基于牧民放牧行为的青海湖流域放牧路线研究――以刚察县为例", 干旱区资源与环境, no. 07, 15 July 2016 (2016-07-15), pages 95 - 99 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114070862A (en) * | 2021-10-15 | 2022-02-18 | 中国科学院地理科学与资源研究所 | Livestock raising control method and system based on Internet of things and readable storage medium |
CN114070862B (en) * | 2021-10-15 | 2022-09-16 | 中国科学院地理科学与资源研究所 | Livestock raising control method and system based on Internet of things and readable storage medium |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Namani et al. | Smart agriculture based on IoT and cloud computing | |
Blender et al. | Managing a mobile agricultural robot swarm for a seeding task | |
US10356743B2 (en) | System and method for wireless location | |
Rovira-Más et al. | Stereo vision three-dimensional terrain maps for precision agriculture | |
CN107436604B (en) | Controlling planning method is intelligently decomposed in carrying robot path under a kind of intelligent environment | |
Park et al. | Forestry monitoring system using lora and drone | |
CN107734457A (en) | Wisdom parking ground navigation system and method | |
CN107092270A (en) | Realize method, the apparatus and system of formation flight | |
CN107249167A (en) | Indoor comprehensive locating platform and localization method | |
Bayram et al. | Tracking wildlife with multiple UAVs: System design, safety and field experiments | |
Randall et al. | LuxTrace: Indoor positioning using building illumination | |
CN106871893A (en) | Distributed INS/UWB tight integrations navigation system and method | |
CN113848208B (en) | Plant phenotype platform and control system thereof | |
Xu et al. | A modular agricultural robotic system (MARS) for precision farming: Concept and implementation | |
CN106200680A (en) | A kind of unmanned plane cluster management system and control method thereof | |
Ghosh et al. | ARREST: A RSSI based approach for mobile sensing and tracking of a moving object | |
CN109933423A (en) | A kind of more satellite resource planing methods being performed in unison with complex task | |
CN110398978A (en) | One kind herding path planning system based on Forage-Livestock Balance model degree | |
CN106932801A (en) | It is a kind of for the hand-held earth station of unmanned plane and surveying and drawing location method | |
CN109270949A (en) | A kind of UAV Flight Control System | |
Jia | [Retracted] Intelligent Garden Planning and Design Based on Agricultural Internet of Things | |
CN108981695A (en) | A kind of carriage navigation system based on ROS | |
CN110190891A (en) | The monitoring data acquisition method and system of farmland quality low-altitude remote sensing and earth horizon sensor | |
Petkovic et al. | IoT devices VS. drones for data collection in agriculture | |
CN113280815B (en) | Unmanned aerial vehicle bee colony room-entering positioning system |
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 |