CN110456814B - Triphibian unmanned aerial vehicle cluster control method and system and unmanned aerial vehicle - Google Patents
Triphibian unmanned aerial vehicle cluster control method and system and unmanned aerial vehicle Download PDFInfo
- Publication number
- CN110456814B CN110456814B CN201910588158.8A CN201910588158A CN110456814B CN 110456814 B CN110456814 B CN 110456814B CN 201910588158 A CN201910588158 A CN 201910588158A CN 110456814 B CN110456814 B CN 110456814B
- Authority
- CN
- China
- Prior art keywords
- unmanned aerial
- aerial vehicle
- triphibian
- data
- abnormal
- 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.)
- Active
Links
Images
Classifications
-
- 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 triphibian unmanned aerial vehicle cluster control method, a triphibian unmanned aerial vehicle cluster control system and an unmanned aerial vehicle, wherein the method comprises the steps of collecting designated data; forming a communication network through ZigBee; acquiring the traveling data of a single triphibian unmanned aerial vehicle; and determining an abnormal unmanned aerial vehicle or a normal unmanned aerial vehicle according to the traveling data, wherein the abnormal unmanned aerial vehicle transmits the designated data to the normal unmanned aerial vehicle along the communication network. The system is used for executing the method. Unmanned aerial vehicle, its characterized in that rolls wing, sensor group, operation controller and power supply including structure body, crawler-type. The embodiment of the invention executes the collection task by collecting the specified data; a communication network is formed by ZigBee to realize data intercommunication in a regional range; acquiring the traveling data of a single triphibian unmanned aerial vehicle to independently judge individuals; and determining an abnormal unmanned aerial vehicle or a normal unmanned aerial vehicle according to the traveling data, wherein the abnormal unmanned aerial vehicle transmits data to the normal unmanned aerial vehicle along a communication network so as to realize backup.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to a triphibian unmanned aerial vehicle cluster control method and system and an unmanned aerial vehicle.
Background
Unmanned aerial vehicle can replace the people to carry out dangerous operation, and the utility is very high, and simultaneously, the function that solitary unmanned aerial vehicle can carry out is limited relatively, carries out unmanned aerial vehicle's control through the cluster and with executive function's mode, can enlarge unmanned aerial vehicle's application range, reduces the intervention of people, can reduce the cost of operation.
One of the functions that the unmanned aerial vehicle can realize is the collection of data, for example, the environment of activities such as polar region scientific investigation is relatively bad, the work risk coefficient is higher, and the operation of the unmanned aerial vehicle in the storm has very high real-time requirement on return voyage management. While scientists have paid much attention to return intelligence, the occurrence of data loss incidents is uncertain. For example, for a disaster relief unmanned aerial vehicle, if emergency data is lost, the situation of trapped people cannot be reflected in time, even more accidents occur, various information of the trapped people cannot be obtained in time and accurately, and a correct decision cannot be made, so that emergency rescue cannot be carried out in time or evacuation directions are misled, life rescue is possibly delayed, and therefore an unmanned aerial vehicle group resistant to severe weather environment is required to complete a data acquisition task which does not fail as much as possible.
Disclosure of Invention
Embodiments of the present invention aim to address, at least to some extent, one of the technical problems in the related art. Therefore, the invention aims to provide a triphibian unmanned aerial vehicle cluster control method, a triphibian unmanned aerial vehicle cluster control system and an unmanned aerial vehicle.
The technical scheme adopted by the invention is as follows:
in a first aspect, an embodiment of the present invention provides a triphibian unmanned aerial vehicle cluster control method, including: collecting specified data; forming a communication network through ZigBee; acquiring the traveling data of a single triphibian unmanned aerial vehicle; and determining an abnormal unmanned aerial vehicle or a normal unmanned aerial vehicle according to the traveling data, wherein the abnormal unmanned aerial vehicle transmits the designated data to the normal unmanned aerial vehicle along the communication network.
Preferably, the data of marcing includes the electric quantity, the electric quantity is less than the electric quantity threshold value, and the unmanned aerial vehicle of triphibian that corresponds is unusual unmanned aerial vehicle.
Preferably, the traveling data includes a geomagnetic vector, an acceleration vector, and an angle vector, values and/or variation values of the geomagnetic vector, the acceleration vector, and the angle vector exceed a collision threshold, and the corresponding triphibian unmanned aerial vehicle is an abnormal unmanned aerial vehicle.
Preferably, the travel data includes positioning information, and the standby travel route is executed according to the positioning information and the electric quantity.
Preferably, the executing the alternate travel route includes: and transforming the triphibian state of the triphibian unmanned aerial vehicle.
In a second aspect, an embodiment of the present invention provides a cluster control system for triphibian unmanned aerial vehicles, including a triphibian unmanned aerial vehicle and a cluster controller, where the triphibian unmanned aerial vehicle includes a data acquisition module, a ZigBee module and a sensor module, where the data acquisition module collects specified data; forming a communication network by ZigBee modules of different triphibian unmanned planes; acquiring the traveling data of a single unmanned aerial vehicle through a sensor module; and the cluster controller determines an abnormal unmanned aerial vehicle or a normal unmanned aerial vehicle according to the traveling data, and the abnormal unmanned aerial vehicle transmits the specified data to the normal unmanned aerial vehicle along the communication network.
Preferably, the triphibian unmanned aerial vehicle comprises a power supply, the traveling data comprises the electric quantity of the power supply, the electric quantity is lower than an electric quantity threshold value, and the cluster controller marks that the corresponding triphibian unmanned aerial vehicle is an abnormal unmanned aerial vehicle.
Preferably, the travel data include a geomagnetic vector, an acceleration vector, and an angle vector, values and/or variation values of the geomagnetic vector, the acceleration vector, and the angle vector exceed a collision threshold, and the triphibian unmanned aerial vehicle corresponding to the cluster controller is marked as an abnormal unmanned aerial vehicle.
Preferably, the travel data comprise positioning information, the cluster controller formulates a standby travel route according to the positioning information and the electric quantity, and the triphibian unmanned aerial vehicle executes the standby travel route.
Preferably, the executing the alternate travel route includes: transform triphibious unmanned aerial vehicle's triphibious state.
In a third aspect, an embodiment of the present invention provides a triphibian unmanned aerial vehicle, including a structural body, a tracked rolling wing, a sensor group, an operation controller, and a power source, where the power source is connected to the tracked rolling wing, the sensor group is connected to the operation controller, and the structural body is configured to accommodate the tracked rolling wing, the sensor group, the operation controller, and the power source.
Preferably, the crawler-type roller wing comprises crawler belts, a crawler belt transmission structure, fan blades arranged between the crawler belts and a rotating structure connected with the fan blades.
Preferably, the operation controller changes the track belt transmission speed and the fan blade angle according to the value output by the sensor.
The embodiment of the invention has the beneficial effects that:
the embodiment of the invention executes the collection task by collecting the specified data; a communication network is formed by ZigBee to realize data intercommunication in a regional range; acquiring the traveling data of a single triphibian unmanned aerial vehicle to independently judge individuals; and determining an abnormal unmanned aerial vehicle or a normal unmanned aerial vehicle according to the traveling data, wherein the abnormal unmanned aerial vehicle transmits data to the normal unmanned aerial vehicle along a communication network so as to realize backup.
Drawings
Fig. 1 is a flow chart of an embodiment of a triphibian drone cluster control method;
fig. 2 is a connection diagram of one embodiment of a triphibian drone cluster control system;
fig. 3 is a schematic structural diagram of the triphibian unmanned aerial vehicle.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
Example 1.
The embodiment provides a triphibian unmanned aerial vehicle cluster control method as shown in fig. 1, which includes the following steps:
s1, collecting specified data;
s2, forming a communication network through ZigBee;
s3, acquiring the traveling data of a single triphibian unmanned aerial vehicle;
s4, determining an abnormal unmanned aerial vehicle or a normal unmanned aerial vehicle according to the traveling data, and transmitting the designated data to the normal unmanned aerial vehicle by the abnormal unmanned aerial vehicle along the communication network.
The triphibian unmanned aerial vehicle is called as the unmanned aerial vehicle for short, and specifically, designated data is acquired through various sensors and other data acquisition equipment carried by the unmanned aerial vehicle; wherein the sensor may comprise a temperature sensor, a humidity sensor, an infrared sensor, etc., and the data acquisition device comprises, for example, a camera, a scanning radar, etc. In this embodiment, it is only necessary to use these instruments for their own functions rather than to modify them, and therefore, the types of sensors and data acquisition devices used to acquire the specified data are not further described.
ZigBee lies in for wireless technology's such as wifi and bluetooth difference, and ZigBee can realize communication network's ad hoc network, can improve the security of the data transfer among the communication process, and can calculate mutual distance according to the intensity of ZigBee signal, is favorable to when individual unmanned aerial vehicle locate function is not effective, calculates the position of unmanned aerial vehicle that became invalid through the position of other unmanned aerial vehicle.
While the unmanned aerial vehicle is traveling (i.e., flying, walking on the road, and walking on the water surface), it is necessary to generate data related to movement/driving, and the process of collecting the data is a common technique in the art, and the present embodiment is not described in detail with respect to a general data acquisition process, but is described with respect to the principle and manner of acquiring specific data. The travel data includes: the power supply comprises electric quantity, positioning information, a geomagnetic vector, an acceleration vector and an angle vector, wherein the electric quantity is the capacity of the power supply/battery; the positioning information is a specific coordinate obtained based on a GPS or a Beidou system; the geomagnetic vector is a vector of the earth's magnetic field.
The processing for travel data includes:
when an unmanned aerial vehicle electric quantity is less than the electric quantity threshold value, the unmanned aerial vehicle that corresponds is unusual unmanned aerial vehicle, and its purpose is in preventing that the electric quantity is not enough to lead to advancing the condition of function or the unable normal function of data acquisition function, this kind of exception appears promptly, then carries out the transmission and the backup of data.
The value and/or the change value of earth magnetism vector, acceleration vector and angle vector surpass the collision threshold value, and the unmanned aerial vehicle of triphibian that corresponds is unusual unmanned aerial vehicle, and when the collision accident takes place, then it can't continue to carry out the task to lead to unmanned aerial vehicle very probably, need return to the air this moment or make it stop in the original place and wait for the rescue, and because when and after the collision accident takes place, unmanned aerial vehicle's state can change, consequently, can judge unmanned aerial vehicle's state according to the change of foretell parameter and trend of change.
In order to arrange the return flight of the unmanned aerial vehicle, the current position needs to be known, the current position can be known through positioning information, the destination of the return flight is known, the path, namely the standby travelling route, can be obtained through simple calculation, the calculation of the specific straight path and the calculation of the complex route can be realized according to a digital map of a third party or a map carried by the third party, and the specific path calculation can be processed by adopting a preset algorithm.
Considering the influence of changes of different environments, for example, stormy weather is not suitable for flying, the original state can be changed into a land traveling mode or a water traveling mode; alternatively, when the water area is limited, the water travel mode may be changed to the flight mode or the land travel mode, that is, the triphibian state may be changed.
Example 2.
This embodiment provides a triphibian unmanned aerial vehicle cluster control system as shown in fig. 2, includes:
the unmanned triphibian comprises a cluster controller 2 and a triphibian unmanned aerial vehicle 1, wherein the triphibian unmanned aerial vehicle comprises a data acquisition module 11, a ZigBee module 12, a power supply 14 and a sensor module 13, and the data acquisition module 13 collects specified data; forming a communication network by ZigBee modules 12 of different triphibian unmanned planes; acquiring the traveling data of a single unmanned aerial vehicle through a sensor module 13; the cluster controller 2 determines an abnormal unmanned aerial vehicle or a normal unmanned aerial vehicle according to the traveling data, and the abnormal unmanned aerial vehicle transmits the designated data to the normal unmanned aerial vehicle along the communication network.
Wherein, the cluster controller 2 may be arranged on the unmanned aerial vehicle; also can set up subaerial, can be through artificial mode direct control unmanned aerial vehicle promptly. At this time, at least one of the drones is provided with a long-range communication device (e.g., a communication interface based on satellite communication), and the drone provided with the long-range communication device is used as a long plane and the other drones are used as wing planes.
Example 3.
The embodiment is specifically used for explaining the structure of the triphibian unmanned aerial vehicle and implementation details of a specific cluster control flow under real conditions.
The triphibian unmanned aerial vehicle shown in fig. 3 comprises a structure body, crawler-type rolling wings, a sensor group, an operation controller and a power source, wherein the power source is connected with the crawler-type rolling wings, the sensor group is connected with the operation controller, and the structure body is used for accommodating the crawler-type rolling wings, the sensor group, the operation controller and the power source.
The structure body is ordinary bearing structure, specifically can be the cuboid, and the wing is rolled to the crawler-type, rolls the wing for short, and the symmetry sets up in the both sides of cuboid, and the crawler-type rolls the wing and includes track strip, track strip transmission structure, sets up flabellum between the track strip and the rotating-structure of connecting the flabellum. The principle of operation lies in that the fan blades move back and forth through the track strips (relative to a reference object, one direction in the horizontal direction is taken as the front, a specific reference object can be the bottom of the structure body), the angle of the fan blades in the moving process is changed through the rotating structure, the track strips are in transmission, the air flow can be changed from the front to the bottom due to the different angles of the fan blades between the upper layer and the lower layer of the track strips, namely the air in front of operation is guided into the lower part, and therefore the lift force is provided to achieve flight.
The driving structure of the crawler-type rolling wing comprises a crawler belt transmission structure and a rotating structure of fan blades, and can be composed of an inner sleeve rotating wheel, an outer sleeve rotating wheel and an inner pull wire and an outer pull wire. The fan blade is characterized in that the inner stay wire comprises two wires and corresponding inner stay wire holes, the distance between the inner stay wire holes is small, the outer stay wire comprises two wires and corresponding outer stay wire holes, and the distance between the outer stay wire holes is large. The inner runner pulls the inner stay wire fixed on the fan blade through the inner teeth of the runner, the outer runner pulls the outer stay wire fixed on the fan blade through the outer teeth of the runner, and the angle of the fan blade can be changed by changing the phase difference between the inner runner and the outer runner. The tension of the stay wire can be changed by changing the master-slave relationship between the front and the rear rotating wheels. The stay wires on the upper layer are in a tight state in an air running state, the stay wires on the lower layer are in a loose state, and a guide rail can be arranged to limit the freedom of the fan blades. The stay wires on the lower layer are in a tight state and the stay wires on the upper layer are in a loose state in a water surface running state, and the guide rails limit the freedom of the fan blades. The pull wires on the lower layer are in a semi-tight state and the pull wires on the upper layer are in a semi-loose state in a ground running state, and the guide rails limit the freedom of the fan blades. The travelling speed of the crawler can be changed by changing the common rotating speed of the inner rotating wheel and the outer rotating wheel.
The structure body comprises a lifting frame, and the purpose of the lifting frame is to prevent the rolling wings from sticking to the ground, so that a foundation is provided for lifting. Similarly, the bottom of the lifting frame is provided with a structure for providing buoyancy, so that the lifting frame can float on the water surface, and particularly can be a hollow plastic piece. And the walking on the ground can be realized only by the normal transmission of the crawler belt. The lifting frame has the functions of lifting and falling, and also has the function of dynamic counterweight balance; the elevating frame comprises a plurality of legs, the length of the legs of the elevating frame can be properly adjusted according to the advancing speed of the crawler belt and the gravity center of the unmanned aerial vehicle, so that the problems of rotation momentum generated by unidirectional rotation of the crawler belt and unequal left and right load loads are solved, the higher the rotation speed of the crawler belt is, the larger the difference between the length of the elevating frame and the length of the elevating frame is, and the stable running characteristic of the water surface and the ground in the air is ensured; the specific lifting sequence and lifting degree of the feet can obtain data according to experiments and write the data into the corresponding control chip.
The sensor group includes:
pressure sensor, it sets up in the bottom of structure body for pressure measurement can judge whether unmanned aerial vehicle is in ground according to pressure.
The humidity sensor or the liquid probe is arranged at the bottom of the structure body or the buoyancy structure and used for judging whether the unmanned aerial vehicle is positioned on the water surface or not according to the humidity and/or the hydraulic strength;
the collision early warning device consists of a 3-axis magnetic sensor, a 3-axis angle sensor and a 3-axis acceleration sensor.
Regarding the flow of determining abnormality:
if the electric quantity is lower than the electric quantity threshold value, the corresponding unmanned aerial vehicle can be judged to be abnormal;
when the number of the 3-axis sensors exceeds 1/3 within 1/3 seconds and repeatedly changes more than 1/3 occur, collision is determined to exist, and data are ensured not to be lost through the ZigBee communication network. The collision threshold value is time, the number of axes, the value of the axis direction and the variation of the value, and belongs to an interval between a maximum value and a minimum value; the specific collision threshold can be set according to requirements.
Possible collision accidents are: collision of the unmanned aerial vehicle with the unmanned aerial vehicle; collision of the unmanned aerial vehicle with the ground; collision of the unmanned aerial vehicle with the water surface; collision of the unmanned aerial vehicle with the flying bird; the unmanned aerial vehicle encounters collision in unexpected scenes such as severe weather, volcanic eruption, terrorists and the like.
The unmanned aerial vehicle loads various data acquisition components and parts and corresponding data processor, and these data acquisition components and parts collect various primitive data. The data processing may then perform signal processing on the raw data: signal enhancement, signal segmentation, signal restoration, etc.; the signals can be subjected to characteristic processing, useful information is derived from the filter circuit, and the most useful characteristic is found from a plurality of characteristics so as to reduce the difficulty of subsequent data processing; different characteristics can be identified by adopting a template matching method, and corresponding data acquisition components can be informed to execute corresponding functions, for example, if an infrared sensor detects infrared signs, a camera can be informed to execute shooting.
Regarding the required control software of unmanned aerial vehicle operation, the required hardware condition of data acquisition components and parts operation and software condition, belong to the conventional technique in this technical field, this embodiment does not carry out further improvement, consequently, does not carry out further explanation.
While the preferred embodiments of the present invention have been illustrated and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (3)
1. A triphibian unmanned aerial vehicle cluster control method is characterized by comprising the following steps:
collecting specified data through a data acquisition module, wherein the data acquisition module is arranged in the triphibian unmanned aerial vehicle;
forming a communication network through ZigBee;
acquiring the traveling data of a single triphibian unmanned aerial vehicle; the traveling data comprises electric quantity, the electric quantity is lower than an electric quantity threshold value, the corresponding triphibian unmanned aerial vehicle is marked as an abnormal unmanned aerial vehicle through a cluster controller, and the cluster controller is arranged in the triphibian unmanned aerial vehicle;
determining, by the cluster controller, an abnormal unmanned aerial vehicle or a normal unmanned aerial vehicle according to traveling data, the traveling data including a geomagnetic vector, an acceleration vector, and an angle vector, values and/or variation values of the geomagnetic vector, the acceleration vector, and the angle vector exceeding a collision threshold value, the corresponding triphibian unmanned aerial vehicle being the abnormal unmanned aerial vehicle, wherein the traveling data includes positioning information, executing a standby traveling route according to the positioning information and the electric quantity, the executing the standby traveling route including: transforming the triphibian state of the triphibian unmanned aerial vehicle;
and the abnormal unmanned aerial vehicle transmits the specified data to the normal unmanned aerial vehicle along the communication network.
2. A triphibian unmanned aerial vehicle cluster control system is characterized by comprising a triphibian unmanned aerial vehicle and a cluster controller, wherein the triphibian unmanned aerial vehicle comprises a data acquisition module, a ZigBee module and a sensor module,
the data acquisition module collects specified data, and the data acquisition module is arranged in the triphibian unmanned aerial vehicle;
forming a communication network by ZigBee modules of different triphibian unmanned planes;
acquiring the traveling data of a single unmanned aerial vehicle through a sensor module; the triphibian unmanned aerial vehicle comprises a power supply, the traveling data comprises the electric quantity of the power supply, the electric quantity is lower than an electric quantity threshold value, the cluster controller marks the corresponding triphibian unmanned aerial vehicle as an abnormal unmanned aerial vehicle, and the cluster controller is arranged in the triphibian unmanned aerial vehicle;
the cluster controller determines an abnormal unmanned aerial vehicle or a normal unmanned aerial vehicle according to traveling data, the traveling data comprises a geomagnetic vector, an acceleration vector and an angle vector, values and/or variation values of the geomagnetic vector, the acceleration vector and the angle vector exceed a collision threshold value, the corresponding triphibian unmanned aerial vehicle is the abnormal unmanned aerial vehicle, the traveling data comprises positioning information, the cluster controller formulates a standby traveling route according to the positioning information and the electric quantity, the triphibian unmanned aerial vehicle executes the standby traveling route, and the executing standby traveling route comprises: transforming the triphibious state of the triphibious unmanned aerial vehicle; and the abnormal unmanned aerial vehicle transmits the specified data to the normal unmanned aerial vehicle along the communication network.
3. The utility model provides a triphibian unmanned aerial vehicle, its characterized in that rolls wing, sensor group, operation controller and power supply motor including structure body, crawler-type, the crawler-type rolls the wing and includes crawler belt, track transmission structure, sets up flabellum between the crawler belt and connects the rotating-structure of flabellum, the power supply motor is connected track transmission structure, the sensor group is connected the operation controller, the structure body is used for acceping the crawler-type rolls wing, sensor group, operation controller and power supply motor, the operation controller is according to numerical value change crawler belt transmission speed and flabellum angle of sensor output.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910588158.8A CN110456814B (en) | 2019-07-02 | 2019-07-02 | Triphibian unmanned aerial vehicle cluster control method and system and unmanned aerial vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910588158.8A CN110456814B (en) | 2019-07-02 | 2019-07-02 | Triphibian unmanned aerial vehicle cluster control method and system and unmanned aerial vehicle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110456814A CN110456814A (en) | 2019-11-15 |
| CN110456814B true CN110456814B (en) | 2022-09-27 |
Family
ID=68481916
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910588158.8A Active CN110456814B (en) | 2019-07-02 | 2019-07-02 | Triphibian unmanned aerial vehicle cluster control method and system and unmanned aerial vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110456814B (en) |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104702656A (en) * | 2014-06-09 | 2015-06-10 | 贵州贵航飞机设计研究所 | Method for duplicating flight data of unmanned aerial vehicles by aid of cloud storage technologies |
| CN106569504A (en) * | 2015-10-09 | 2017-04-19 | 内蒙古信源信息技术有限公司 | Apparatus for realizing device information acquisition in remote area through Beidou unmanned gyroplanes and data exchanging method |
| US10137984B1 (en) * | 2016-02-23 | 2018-11-27 | State Farm Mutual Automobile Insurance Company | Systems and methods for operating drones in response to an incident |
| CN106406349B (en) * | 2016-10-28 | 2019-11-19 | 易瓦特科技股份公司 | UAV Flight Control method and system |
| CN106919183B (en) * | 2016-12-20 | 2019-12-13 | 北京理工大学 | unified control's multi-functional unmanned aerial vehicle group |
| CN108303995B (en) * | 2018-03-02 | 2023-08-25 | 三峡大学 | Substation inspection unmanned aerial vehicle flight safety system and use method |
| CN109186684A (en) * | 2018-10-15 | 2019-01-11 | 上海交大智邦科技有限公司 | Unmanned plane equipment monitoring system and method |
-
2019
- 2019-07-02 CN CN201910588158.8A patent/CN110456814B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN110456814A (en) | 2019-11-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20210149398A1 (en) | Velocity control for an unmanned aerial vehicle | |
| US10599149B2 (en) | Salient feature based vehicle positioning | |
| CN103078673B (en) | A kind of dedicated unmanned Helicopter System being applicable to mountain area electrical network and patrolling and examining | |
| EP3500903B1 (en) | Systems and methods of unmanned aerial vehicle flight restriction for stationary and moving objects | |
| EP3123260B1 (en) | Selective processing of sensor data | |
| CN108298043B (en) | Intelligent life saving equipment on water based on unmanned aerial vehicle and life buoy linkage | |
| US11294398B2 (en) | Personal security robotic vehicle | |
| CN103863948B (en) | A kind of crane works in coordination with the Navigation Control Unit of carrying and the method for Navigation Control | |
| EP3855276A1 (en) | Multi-sensor environmental mapping | |
| CN106774436A (en) | The control system and method for the rotor wing unmanned aerial vehicle tenacious tracking target of view-based access control model | |
| CN203219298U (en) | Unmanned helicopter system special for inspecting electric grid in mountain area | |
| CN106373332A (en) | Vehicle-mounted intelligent alarm method and device | |
| CN104199455A (en) | Multi-rotor craft based tunnel inspection system | |
| CN106898249B (en) | A kind of map constructing method for earthquake-stricken area communication failure region | |
| CN206719342U (en) | A kind of crawler belt scout car based on unmanned aerial vehicle platform | |
| CN110989673A (en) | Autonomous tracking take-off and landing system of rotor unmanned aerial vehicle mobile platform and control method | |
| CN113111704B (en) | Airport pavement disease foreign matter detection method and system based on deep learning | |
| JP2019196150A (en) | System, method, and program for identifying safe landing area, and storage medium for storing the program | |
| CN107783119A (en) | Apply the Decision fusion method in obstacle avoidance system | |
| CN108803633A (en) | A kind of unmanned plane low latitude monitoring system based on mobile communications network | |
| CN109848996A (en) | Extensive three-dimensional environment map creating method based on figure optimum theory | |
| CN112783181A (en) | Multi-rotor unmanned aerial vehicle cluster vision landing method based on fuzzy control | |
| CN110456814B (en) | Triphibian unmanned aerial vehicle cluster control method and system and unmanned aerial vehicle | |
| CN113568427A (en) | Method and system for unmanned aerial vehicle to land mobile platform independently | |
| CN204347617U (en) | Aircraft thrown in by a kind of wireless remote control lifesaving equipment |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |