KR20210010166A - System and method for processing unmanned flight vehicle leaving formation in cluster flight - Google Patents

Abstract

According to one embodiment of the present invention, a system for processing an unmanned aerial vehicle leaving formation during cluster flight comprises: a plurality of unmanned aerial vehicles; and a ground control system (GCS) controlling flight of each of the plurality of unmanned aerial vehicles. Each of the plurality of unmanned aerial vehicles includes: a wireless communication unit including a first communication module communicating with adjacent unmanned aerial vehicles and a second communication module communicating with the ground control system; a sensor unit including sensors necessary for performing a target search task; and a flight control unit performing a collision avoidance process stored in an internal memory when another unmanned aerial vehicle adjacent within a certain distance is sensed by the sensor unit and performing flight control to switch a direction different from a direction of a currently set flight path based on flight history information of the adjacent unmanned aerial vehicle.

Description

Processing system and method of unmanned aerial vehicle leaving formation during cluster flight {SYSTEM AND METHOD FOR PROCESSING UNMANNED FLIGHT VEHICLE LEAVING FORMATION IN CLUSTER FLIGHT}

Embodiments of the present invention relate to an unmanned aerial vehicle, and more particularly, to a system and method for processing an unmanned aerial vehicle that deviates from formation during a swarm flight.

In recent years, as the technology of unmanned aerial vehicles develops rapidly, the demand for them has exploded around the world. The unmanned aerial vehicle is an unmanned aerial vehicle that can be controlled by wireless radio waves through remote control or automatic control without a pilot on board, and is generally called a drone, and is equipped with a camera, sensor, ultrasonic equipment, communication system, and the like.

The unmanned aerial vehicle was started for military use, but in recent years, it has been widely used for various purposes such as high altitude shooting and product delivery, pesticide spraying, air quality measurement, forest fire monitoring and extinguishing, communication, disaster environment response, research and development, etc. It was reborn as an inexpensive Kidult product, so that even individuals can purchase it without burden.

In this situation, in recent years, due to the rapid development of communication and computing technology, multiple unmanned aerial vehicles form a formation rather than simply flying a single unmanned aerial vehicle, and thus, it is suitable for swarm flight that performs special and complex missions such as disaster relief and reconnaissance. There is an active research on the Korean market.

However, when performing swarm flight using the conventional unmanned aerial vehicle as described above, the precision of GPS is low, and there is a high possibility of collision between adjacent unmanned aerial vehicles in a situation where a plurality of unmanned aerial vehicles are simultaneously controlled in a narrow space. When a collision occurs between unmanned aerial vehicles, there is a problem of economic loss due to damage of the unmanned aerial vehicle, as well as enormous disruption to work performed through swarm flight. In addition, according to the prior art, since the unmanned aerial vehicle in which the problem has occurred is left without joining (returning) to the crowded flight line, there is a problem such as an accident in which the unmanned aerial vehicle falls or collides, injuring people or destroying facilities. .

As a related prior art, there is Korean Patent Application Publication No. 10-2019-0014418 (name of invention: cluster driving control system and method, publication date: 2019.02.12).

An embodiment of the present invention not only enables autonomous missions through information sharing through wireless communication between unmanned aerial vehicles, but also prevents collisions of unmanned aerial vehicles during the mission by introducing artificial intelligence model learning technology. It provides a system and method for handling unmanned aerial vehicles that are out of formation during possible swarm flight.

The problem to be solved by the present invention is not limited to the problem(s) mentioned above, and another problem(s) not mentioned will be clearly understood by those skilled in the art from the following description.

The processing system of an unmanned aerial vehicle leaving formation during a swarm flight according to an embodiment of the present invention includes a plurality of unmanned aerial vehicles and a ground control system (GCS) for controlling the flight of each of the plurality of unmanned aerial vehicles, and the plurality of unmanned aerial vehicles Each of the aircraft includes a wireless communication unit including a first communication module for performing communication with other adjacent unmanned aerial vehicles, and a second communication module for performing communication with the ground control system; A sensor detection unit including sensors necessary to perform a task of searching for a target; And when another unmanned aerial vehicle adjacent within a certain distance is detected by the sensor detection unit, based on the collision avoidance process stored in the internal memory and flight history information of the adjacent other unmanned aerial vehicle received through the first communication module. , And a flight control unit for performing flight control to switch to a direction different from the direction of the currently set flight path.

The flight control unit determines whether there is an error in hardware of the unmanned aerial vehicle based on the sensing data detected by the sensor detection unit, and if there is no abnormality as a result of the determination, loads and automatically executes a return command program from the internal memory, and the Flight can be controlled to return to the original formation or take-off station, depending on the automatic execution of the return command program.

When there is an abnormality as a result of the determination, the flight control unit loads a fall command program from the internal memory and automatically executes it, and according to the automatic execution of the fall command program, the flight control unit includes a fall accident prevention device including an airbag or parachute mounted on the unmanned aerial vehicle. You can make it work.

The flight control unit derives calculation information including a relative distance with the adjacent other unmanned aerial vehicle and a flight direction and relative approach speed of the adjacent other unmanned aerial vehicle based on the flight history information, and transfers the computation information to the collision avoidance process. By applying, flight control may be performed to switch to a direction different from the direction of the currently set flight path.

The flight controller considers at least one of the remaining battery capacity of the unmanned aerial vehicle in the mission, the available mission flight distance according to the remaining battery capacity, the flight environment including weather conditions, and the flight area condition including the altitude limit condition, Flight control may be performed so that a corresponding unmanned aerial vehicle in the mission is moved to an undiscovered area or the least searched area among the mission areas.

The processing system of the unmanned aerial vehicle departing from formation during a swarm flight according to an embodiment of the present invention is a flight according to the flight control of the flight controller for collision avoidance when another unmanned aerial vehicle adjacent within a certain distance is detected by the sensor detection unit. AI Big, which accumulates and stores history information, analyzes the accumulated flight history information to identify the cause of adjacent flights or collisions, learns the result of the determination, and provides learning data so that the same accident does not occur during subsequent flights. It may further include a data server.

A method of processing a formation departure unmanned aerial vehicle during a swarm flight according to an embodiment of the present invention includes the steps of: detecting whether a sensor detection unit of the unmanned aerial vehicle is adjacent to another unmanned aerial vehicle within a predetermined distance; Receiving flight history information of the other unmanned aerial vehicle when the wireless communication unit of the unmanned aerial vehicle is adjacent to the other unmanned aerial vehicle; And performing, by the flight control unit of the unmanned aerial vehicle, on the basis of the collision avoidance process stored in the internal memory and the flight history information, to switch to a direction different from the direction of the currently set flight path.

A method of processing an unmanned aerial vehicle leaving formation during a swarm flight according to an embodiment of the present invention comprises: determining, by the flight controller, whether or not there is a hardware abnormality of the unmanned aerial vehicle based on sensing data detected by the sensor detection unit; If there is no abnormality as a result of the determination, the flight control unit loading and automatically executing a return command program from the internal memory; And controlling, by the flight controller, a flight to return to the original formation or take-off station according to the automatic execution of the return command program.

The processing method of an unmanned aerial vehicle leaving formation during a swarm flight according to an embodiment of the present invention includes the steps of, when there is an abnormality as a result of the determination, the flight controller loading and automatically executing a fall command program from the internal memory; And operating, by the flight control unit, a fall accident prevention device including an airbag or parachute mounted on a corresponding unmanned aerial vehicle according to the automatic execution of the fall command program.

The processing method of the unmanned aerial vehicle departing from formation during a swarm flight according to an embodiment of the present invention includes the remaining battery capacity of the unmanned aerial vehicle on which the flight controller is on a mission, a possible mission flight distance according to the remaining battery capacity, a flight environment including weather conditions, and In consideration of at least one of the flight area conditions including the altitude limit condition, further comprising the step of performing flight control so that the corresponding unmanned aerial vehicle on the mission moves to the undiscovered area or the least searched area among the mission areas divided into a plurality of pieces. can do.

In the method of processing an unmanned aerial vehicle leaving formation during a swarm flight according to an embodiment of the present invention, when another unmanned aerial vehicle adjacent within a certain distance is detected by the sensor detection unit, the AI big data server is used for the flight control unit for collision avoidance. Accumulating and storing flight history information according to flight control; Analyzing, by the AI big data server, the accumulated flight history information to determine the cause of adjacent flights or collisions; And providing, by the IA big data server, learning a result of determining the cause of the adjacent flight or collision so that the same accident does not occur during subsequent flights.

Details of other embodiments are included in the detailed description and accompanying drawings.

According to an embodiment of the present invention, not only can autonomous missions be performed through information sharing through wireless communication between unmanned aerial vehicles, but also collision accidents of unmanned aerial vehicles during missions can be prevented by introducing artificial intelligence model learning technology. Can be prevented.

1 is a conceptual diagram schematically showing a processing system of an unmanned aerial vehicle leaving a formation during a swarm flight according to an embodiment of the present invention.
2 is a block diagram illustrating a detailed configuration of the unmanned aerial vehicle of FIG. 1.
3 is a view showing a comparison of the positional relationship between unmanned aerial vehicles in a mission according to an embodiment of the present invention.
4 is a diagram showing a geometrical relationship used for calculating collision time of unmanned aerial vehicles in an embodiment of the present invention.
5 is a block diagram illustrating a system for processing an unmanned aerial vehicle leaving a formation during a swarm flight according to another embodiment of the present invention.
6 is a flowchart illustrating a method of processing a formation departure unmanned aerial vehicle during a swarm flight according to an embodiment of the present invention.
7 and 8 are flowcharts illustrating a flight control method according to the presence or absence of a hardware error of an unmanned aerial vehicle in an embodiment of the present invention.
9 is a flowchart illustrating a method of processing an unmanned aerial vehicle leaving a formation during a swarm flight according to another embodiment of the present invention.

Advantages and/or features of the present invention, and a method of achieving them will become apparent with reference to the embodiments described later in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but will be implemented in a variety of different forms, only these embodiments make the disclosure of the present invention complete, and common knowledge in the technical field to which the present invention pertains. It is provided to completely inform the scope of the invention to those who have, and the invention is only defined by the scope of the claims. The same reference numerals refer to the same elements throughout the specification.

In addition, a preferred embodiment of the present invention to be implemented below is already provided in each system functional configuration in order to efficiently describe the technical components constituting the present invention, or system functions commonly provided in the technical field to which the present invention belongs. The configuration will be omitted as much as possible, and a functional configuration that should be additionally provided for the present invention will be mainly described. If a person of ordinary skill in the art to which the present invention belongs will be able to easily understand the functions of components previously used among functional configurations that are not shown below and are omitted, the configuration omitted as described above. The relationship between the elements and the components added for the present invention will also be clearly understood.

In addition, in the following description, "transmission", "communication", "transmission", "receive" of a signal or information, and other terms with similar meanings refer to direct transmission of signals or information from one component to another. Not only that, but it includes things that are passed through other components. In particular, "transmitting" or "transmitting" a signal or information to a component indicates the final destination of the signal or information and does not imply a direct destination. The same is true for "reception" of signals or information.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a conceptual diagram schematically showing a processing system of an unmanned aerial vehicle leaving formation during a swarm flight according to an embodiment of the present invention, and FIG. 2 is a block diagram showing a detailed configuration of the unmanned aerial vehicle 110 of FIG. 1 to be.

1 and 2, the processing system 100 of an unmanned aerial vehicle leaving formation during a swarm flight according to an embodiment of the present invention includes a plurality of unmanned aerial vehicles 110, and each of the plurality of unmanned aerial vehicles 110 It may be configured to include a ground control system 120 to control the flight.

The unmanned aerial vehicle 110 is an unmanned aerial vehicle in the form of an airplane or helicopter capable of flying and controlling by induction of radio waves, and is generally known as a drone. However, in the present invention, the unmanned aerial vehicle 110 may be understood as a concept including not only the drone but also sky lanterns using the drone as a power source.

The unmanned aerial vehicle 110 may perform a role of performing photographing for obtaining an image while flocking through a photographing target region using GPS location information. Here, the GPS location information may be understood as a concept including Real Time Kinematic (RTK)-GPS-based location information.

The RTK-GPS-based location information means accurate coordinates of a current location determined in real time through a synthesis of coordinates acquired through a GPS satellite and location correction data transmitted from the ground control system 120.

By using the RTK-GPS-based location information, the unmanned aerial vehicle 110 can check its own exact location information through information provided by GPS satellites and base stations while minimizing location errors that may occur in conventional GPS. . Accordingly, the unmanned aerial vehicle 110 may perform a mission while performing a swarm flight based on precise coordinate information acquired according to high-precision position recognition.

As shown in FIG. 2, the unmanned aerial vehicle 110 may include a wireless communication unit 210, a sensor detection unit 220, a flight control unit 230, and a main control unit 240.

The wireless communication unit 210 is used for wireless communication between unmanned aerial vehicles 110 in mission, and a first communication module 211 for communicating with other adjacent unmanned aerial vehicles 110, and the ground control system ( 120) may be configured to include a second communication module 212 for performing communication.

The first communication module 211 serves to enable wireless communication between unmanned aerial vehicles 100 that are adjacent to each other during a mission, and the wireless communication content through the first communication module 211 includes a flight status. Information and search progress information may be included.

That is, according to an embodiment of the present invention, when the unmanned aerial vehicles 110 in a mission are adjacent to each other, flight status information including a location, flight speed, etc. between each other through the first communication module 211, and a mission It is possible to enable more efficient autonomous search by enabling the sharing of search progress information including whether to search for an area or whether to search for a target, and furthermore, it is possible to enable collision avoidance.

The second communication module 212 provides information generated by the unmanned aerial vehicle 110 during a mission, that is, information about a specific object detection, a specific function abnormality, or information of the unmanned aerial vehicle 110 such as the remaining battery capacity. Reports to 120, and serves to receive the command from the ground control system 120 in the unmanned aerial vehicle 110.

To this end, according to an embodiment of the present invention, the second communication module 212 is set to have a wider communication range than the first communication module 211, and the second communication module 212 can communicate with each other. For the unmanned aerial vehicle 110 that is further away from the ground control system 120 than the range, the first communication module 211 is used to report to the adjacent unmanned aerial vehicle 110 located closer to the ground control system 120 You can repeat the process of communicating the matter. Accordingly, from the ground control system 120 to the unmanned aerial vehicle 110 located within the communication range of the second communication module 212, finally to the ground control system 120 through the second communication module 212 Can report information.

The sensor detection unit 220 may include sensors necessary to perform a task of searching for a target. The sensor detection unit 220 is composed of sensors necessary for a search mission of the unmanned aerial vehicle 110, and may be configured to include an electro-optical sensor, an infrared sensor, and a GPS sensor, although not shown in the drawing.

The electro-optical sensor is a sensor that measures and detects an electromagnetic wave, ie, a near-infrared ray and a visible ray, and a reflected wave that returns to the air.

The infrared ray sensor is a sensor that detects physical or stoichiometric quantities such as temperature, pressure, and radiation intensity using infrared light and converts it into an electric quantity capable of signal processing, and is generally mounted on the unmanned aerial vehicle 110 and used. It becomes.

The GPS sensor allows the real-time location of the unmanned aerial vehicle 110 in the mission to be confirmed by the other unmanned aerial vehicle 110 or the ground control system 120, and serves to be utilized when avoiding a collision, which will be described later.

On the other hand, the sensor detection unit 220 may be configured to further include a speed sensor or an acceleration sensor to measure the real-time speed of the unmanned aerial vehicle 110 in the mission.

When another unmanned aerial vehicle 110 adjacent within a certain distance is detected by the sensor detection unit 220, the flight control unit 230 performs a collision avoidance process stored in the internal memory and the first communication module 211. Flight control may be performed to switch to a direction different from the direction of the currently set flight path based on the flight history information of the adjacent other unmanned aerial vehicle 110 received through.

That is, the flight control unit 230 is based on the flight history information of the other unmanned aerial vehicle 110 adjacent to the unmanned aerial vehicle 110 and the relative distance with the other adjacent unmanned aerial vehicle 110 and the adjacent other unmanned aerial vehicle 110 It is possible to perform flight control so as to derive computational information including a flight direction and a relative approach speed, and apply the computational information to the collision avoidance process to switch to a direction different from the direction of the currently set flight path.

Here, the collision avoidance process may include a program for processing a process of avoiding a collision by autonomously changing directions when the unmanned aerial vehicles 110 in a mission approach within a predetermined interval.

That is, according to the collision avoidance process, it is determined whether the unmanned aerial vehicles 110 approached within a certain interval through sharing of location information and speed information between each other through the first communication module 211, and If it is determined that the flight control can be performed so that the direction can be changed autonomously. In addition, according to the collision avoidance process, flight control may be performed so that the unmanned aerial vehicles 110 avoid collision by additionally considering collision time.

More specifically, according to the collision avoidance process, the position identified from the GPS sensor provided in each unmanned aerial vehicle 110 in order to determine the position and moving speed of the two adjacent unmanned aerial vehicles 100, and a speed sensor or acceleration The moving speed determined from the sensor may be shared and recognized through the first communication module 211.

In this case, the collision avoidance process may calculate the moving speed by using the location information for each time determined from the GPS sensor even if the speed sensor or the acceleration sensor is not provided in the unmanned aerial vehicle 110. Here, the information on the location and movement speed may be transmitted to the ground control system 120 through the second communication module 212 as needed.

In this way, the unmanned aerial vehicle 110 is configured to autonomously avoid collision by using the location information and movement speed information shared with each other through the first communication module 211, but Fig. 3(a) As shown in, when two adjacent unmanned aerial vehicles 110 face each other and fly in an approaching direction, as shown in (b) of FIG. 3, compared to the case where two adjacent unmanned aerial vehicles 110 cross each other Since the collision time may be relatively shortened and it may be difficult to avoid normal collisions, collision avoidance between the two unmanned aerial vehicles 110 may be more safely and accurately configured through calculation of the collision time.

The calculation process of the collision time will be described in detail with reference to Equations 1 to 3 below. In the collision avoidance process, the collision time may be calculated from a geometric relationship using a position and a moving speed between two adjacent unmanned aerial vehicles 110.

That is, when the positions of the adjacent two unmanned aerial vehicles 110 are respectively P1 and P2, and the moving speeds V1 and V2, the relative distance Pr and the relative speed Vr between the two unmanned aerial vehicles 110 are in the following equation (1). Can be obtained by

[Equation 1]

Further, the relative approach speed Vr between the two unmanned aerial vehicles 110 can be obtained by the following equation (2) from the geometrical relationship shown in FIG.

[Equation 2]

Therefore, the collision time tc between the two unmanned aerial vehicles 110 can be calculated by the following equation (3) representing the relationship between time, speed and distance.

[Equation 3]

In addition, the collision avoidance process may perform a process of changing the direction of the unmanned aerial vehicles 110 at risk of collision. That is, when the collision time calculated by Equations 1 to 3 becomes less than the reference time required for collision avoidance, the collision avoidance process can perform flight control to switch the directions of the two unmanned aerial vehicles 110. have.

At this time, the reference time required for the collision avoidance may be set based on the maneuverability and turn rate of the unmanned aerial vehicle 110, and since it is a parameter related to the information update frequency of the unmanned aerial vehicle 110, the mission environment, the unmanned aerial vehicle 110 It is desirable to set an appropriate value through simulation in consideration of the performance of the vehicle 110 and the like.

Meanwhile, the flight control unit 230 may determine whether or not there is a hardware abnormality of the unmanned aerial vehicle 110 based on sensing data detected by the sensor detection unit 220. That is, the flight control unit 230 may determine whether there is an abnormality in the hardware of the unmanned aerial vehicle 110 based on sensing data including location information and moving speed of the unmanned aerial vehicle 110.

When it is determined that there is no abnormality in the hardware of the unmanned aerial vehicle 110, the flight controller 230 may load and automatically execute a return command program from the internal memory of the unmanned aerial vehicle 110. The flight control unit 230 may control the flight to return to the original formation or take-off station according to the automatic execution of the return command program.

On the other hand, when it is determined that the hardware of the unmanned aerial vehicle 110 is abnormal, the flight control unit 230 may load and automatically execute a fall command program from the internal memory of the unmanned aerial vehicle 110. The flight control unit 230 may operate a fall accident prevention device including an airbag or parachute mounted on the unmanned aerial vehicle 110 according to the automatic execution of the fall command program.

Accordingly, according to an embodiment of the present invention, it is possible not only to prevent a fall accident of the unmanned aerial vehicle 110, but also to prevent an accident that injures a person or destroys a facility by colliding with a person or facility during a fall.

The flight control unit 230 considers at least one of a remaining battery capacity of the unmanned aerial vehicle 110 in a mission, a possible mission flight distance according to the remaining battery capacity, a flight environment including weather conditions, and a flight area state including an altitude limit condition. Thus, it is possible to perform flight control so that the unmanned aerial vehicle 110 in the mission moves to an undiscovered area or the least searched area among the mission areas divided into a plurality of pieces.

The main control unit 240 may control overall operations of the unmanned aerial vehicle 110, that is, the wireless communication unit 210, the sensor detection unit 220, and the flight control unit 230.

The ground control system 120 may play a role of controlling the flight of the unmanned aerial vehicle 110 and analyzing information obtained from the unmanned aerial vehicle 110.

Specifically, the ground control system 120 performs communication with the unmanned aerial vehicles 110 on the mission, but the unmanned aerial vehicle through communication with the second communication module 212 provided in the unmanned aerial vehicle 110 At the same time as transmitting a command related to the search mission to the aircraft 110, it is possible to receive flight information and search information transmitted from the unmanned aerial vehicle 110.

The ground control system 120 plays a role of overall control of the flight of the unmanned aerial vehicle 110, and basically, a change of direction or mission completion or battery for collision avoidance and search location change of the unmanned aerial vehicle 110 It is possible to perform the same functions as the flight control unit 230 provided in the unmanned aerial vehicle 110, such as returning to the ground control system 120 of the unmanned aerial vehicle 110 due to a lack of remaining amount.

The ground control system 120 is the unmanned aerial vehicle 110 when autonomous flight of the unmanned aerial vehicle 110 becomes impossible due to an unexpected situation such as an abnormal occurrence of the first communication module 211 provided in the unmanned aerial vehicle 110 Can be controlled in lieu of (110) flight.

5 is a block diagram illustrating a system for processing an unmanned aerial vehicle leaving a formation during a swarm flight according to another embodiment of the present invention.

5, a processing system 500 of an unmanned aerial vehicle leaving formation during a swarm flight according to another embodiment of the present invention includes a plurality of unmanned aerial vehicles 510, a ground control system 520, and an AI big data server 530. It can be configured to include.

In another embodiment of the present invention, the processing system 500 of the unmanned aerial vehicle leaving the formation during the swarm flight includes the same components except for the system 100 of FIG. 1 and the AI big data server 530 . Therefore, in this embodiment, descriptions of the unmanned aerial vehicle 510 and the ground control system 520 will be omitted, and the AI big data server 530 will be described in detail.

When the AI big data server 530 detects another unmanned aerial vehicle 510 adjacent within a certain distance by the sensor detection unit (refer to 220 in Fig. 2), the flight control unit for collision avoidance (refer to 230 in Fig. 2) ), it is possible to collect big data by accumulating and storing flight history information according to flight control.

The AI big data server 530 may analyze the accumulated flight history information (big data) to determine the cause of adjacent flights or collisions. The AI big data server 530 may learn the result of determining the cause of the adjacent flight or collision, and generate learning data based on the learning result, and to prevent the same accident from occurring during subsequent flight, other unmanned aerial vehicles The learning data may be provided to 510 and/or the ground control system 520.

The apparatus described above may be implemented as a hardware component, a software component, and/or a combination of a hardware component and a software component. For example, the devices and components described in the embodiments include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), It can be implemented using one or more general purpose computers or special purpose computers, such as a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications executed on the operating system. In addition, the processing device may access, store, manipulate, process, and generate data in response to the execution of software. For the convenience of understanding, although it is sometimes described that one processing device is used, one of ordinary skill in the art, the processing device is a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that it may include. For example, the processing device may include a plurality of processors or one processor and one controller. In addition, other processing configurations are possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of these, configuring the processing unit to behave as desired or processed independently or collectively. You can command the device. Software and/or data may be interpreted by a processing device or to provide instructions or data to a processing device, of any type of machine, component, physical device, virtual equipment, computer storage medium or device. , Or may be permanently or temporarily embodyed in a transmitted signal wave. The software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

6 is a flowchart illustrating a method of processing a formation departure unmanned aerial vehicle during a swarm flight according to an embodiment of the present invention.

The method of processing the formation departure unmanned aerial vehicle during a swarm flight described here is only one embodiment of the present invention, and various steps may be added as necessary, and the following steps may also be performed by changing the order. Therefore, the present invention is not limited to each step and its sequence described below. This may be similarly applied to the following other embodiments.

1 and 6, in step 610, the sensor detection unit 220 of the unmanned aerial vehicle 110 may detect whether another unmanned aerial vehicle 110 is adjacent within a predetermined distance.

Next, in step 620, the wireless communication unit 210 of the unmanned aerial vehicle 110 may receive flight history information of the other unmanned aerial vehicle 110 when the other unmanned aerial vehicle 110 is adjacent.

Next, in step 630, the flight controller 230 of the unmanned aerial vehicle 110 is based on the collision avoidance process and the flight history information stored in the internal memory of the unmanned aerial vehicle 110, the currently set flight path Flight control can be performed to switch in a direction different from that of.

7 and 8 are flowcharts illustrating a flight control method according to the presence or absence of a hardware error of an unmanned aerial vehicle in an embodiment of the present invention.

2, 7 and 8, the flight control unit 230 of the unmanned aerial vehicle 110 in step 710 is based on the sensing data sensed by the sensor detection unit 220, the unmanned aerial vehicle ( 110) can be determined whether there is a hardware error.

If there is no abnormality as a result of the determination (in the "Yes" direction of 720), the flight control unit 230 may load and automatically execute a return command program from the internal memory of the unmanned aerial vehicle 110 in step 730.

Next, in step 740, the flight control unit 230 may control the flight to return to the original formation or take-off station according to the automatic execution of the return command program.

On the other hand, if there is an abnormality as a result of the determination (in the "No" direction of 720), process A may be performed.

That is, in step 810, the flight control unit 230 may load and automatically execute a fall command program from the internal memory of the unmanned aerial vehicle 110.

Next, in step 820, the flight control unit 230 may operate a fall accident prevention device including an airbag or parachute mounted on the unmanned aerial vehicle 110 according to the automatic execution of the fall command program.

9 is a flowchart illustrating a method of processing an unmanned aerial vehicle leaving a formation during a swarm flight according to another embodiment of the present invention.

Referring to FIGS. 5 and 9, in step 910, the sensor detection unit of the unmanned aerial vehicle 510 (refer to 220 of FIG. 2) may detect whether another unmanned aerial vehicle 510 is adjacent within a predetermined distance.

Next, in step 920, the AI big data server 530 may accumulate and store flight history information according to flight control of the flight controller (refer to 230 of FIG. 2) for collision avoidance.

Next, in step 930, the AI big data server 530 analyzes the accumulated flight history information to determine the cause of adjacent flights or collisions.

Next, in step 940, the IA big data server 530 may learn the result of determining the cause of the adjacent flight or collision, and provide the learning data so that the same accident does not occur during subsequent flights.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc. alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the embodiment, or may be known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CDROMs and DVDs, and magnetic-optical media such as floptical disks. And hardware devices specially configured to store and execute program instructions such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of the program instructions include not only machine language codes such as those produced by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. The hardware device described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

As described above, although the embodiments have been described by the limited embodiments and drawings, various modifications and variations are possible from the above description by those of ordinary skill in the art. For example, the described techniques are performed in a different order from the described method, and/or components such as a system, structure, device, circuit, etc. described are combined or combined in a form different from the described method, or other components Alternatively, even if substituted or substituted by an equivalent, an appropriate result can be achieved.

Therefore, other implementations, other embodiments, and equivalents to the claims fall within the scope of the following claims.

110, 510: unmanned aerial vehicle
120, 520: ground control system
210: wireless communication unit
211: first communication module
212: second communication module
220: sensor detection unit
230: flight control
240: main control unit
530: AI Big Data Server

Claims (11)

Including a plurality of unmanned aerial vehicles, and a ground control system (GCS) for controlling the flight of each of the plurality of unmanned aerial vehicles,
Each of the plurality of unmanned aerial vehicles
A wireless communication unit including a first communication module performing communication with other adjacent unmanned aerial vehicles, and a second communication module performing communication with the ground control system;
A sensor detection unit including sensors necessary to perform a task of searching for a target; And
When another unmanned aerial vehicle adjacent within a certain distance is detected by the sensor detection unit, based on the collision avoidance process stored in the internal memory and flight history information of the adjacent other unmanned aerial vehicle received through the first communication module, Flight control unit that performs flight control to switch to a direction different from the currently set flight path direction
The processing system of the unmanned aerial vehicle leaving the formation during swarm flight, characterized in that it comprises a.
The method of claim 1,
The flight control unit
Based on the sensing data sensed by the sensor detection unit, it is determined whether there is a hardware error of the unmanned aerial vehicle, and if there is no abnormality as a result of the determination, a return command program is loaded from the internal memory and automatically executed, and the return command program A system for processing unmanned aerial vehicles leaving formation during swarm flight, characterized in that flight control is performed to return to the original formation or take-off station according to automatic execution.
The method of claim 2,
The flight control unit
When there is an abnormality as a result of the determination, a fall command program is loaded from the internal memory and automatically executed, and according to the automatic execution of the fall command program, a fall accident prevention device including an airbag or a parachute mounted on a corresponding unmanned aerial vehicle is operated. The handling system of unmanned aerial vehicles leaving the formation during swarm flight.
The method of claim 1,
The flight control unit
Based on the flight history information, calculation information including the relative distance with the adjacent other unmanned aerial vehicle, the flight direction and relative approach speed of the adjacent other unmanned aerial vehicle is derived, and the computational information is applied to the collision avoidance process, A system for processing unmanned aerial vehicles leaving formation during swarm flight, characterized in that flight control is performed to switch to a direction different from the direction of the set flight path.
The method of claim 1,
The flight control unit
In consideration of at least one of the remaining battery capacity of the unmanned aerial vehicle in the mission, the possible mission flight distance according to the remaining battery capacity, the flight environment including weather conditions, and the flight area condition including the altitude limit condition, the US A system for processing an unmanned aerial vehicle leaving formation during a swarm flight, characterized in that it performs flight control to move the unmanned aerial vehicle in the mission to a search area or the least searched area.
The method of claim 1,
When another unmanned aerial vehicle adjacent to a certain distance is detected by the sensor detection unit, flight history information according to flight control of the flight control unit for collision avoidance is accumulated and stored, and the accumulated flight history information is analyzed to fly adjacent Or, an AI big data server that identifies the cause of the collision and learns the result of the identification to provide learning data so that the same accident does not occur during subsequent flights
The processing system of the unmanned aerial vehicle leaving the formation during swarm flight, characterized in that it further comprises.
Detecting whether another unmanned aerial vehicle is adjacent within a predetermined distance by a sensor detection unit of the unmanned aerial vehicle;
Receiving flight history information of the other unmanned aerial vehicle when the wireless communication unit of the unmanned aerial vehicle is adjacent to the other unmanned aerial vehicle; And
Performing flight control so that the flight controller of the unmanned aerial vehicle switches to a direction different from the direction of the currently set flight path based on the collision avoidance process and the flight history information stored in the internal memory
A method of processing an unmanned aerial vehicle leaving the formation during a swarm flight, comprising: a.
The method of claim 7,
Determining, by the flight control unit, whether or not there is an error in hardware of the unmanned aerial vehicle based on sensing data detected by the sensor detection unit;
If there is no abnormality as a result of the determination, the flight control unit loading and automatically executing a return command program from the internal memory; And
The flight control step of controlling the flight to return to the original formation or take-off station according to the automatic execution of the return command program
Processing method of the formation departure unmanned aerial vehicle during swarm flight, characterized in that it further comprises.
The method of claim 8,
If there is an abnormality as a result of the determination, the flight control unit loading and automatically executing a fall command program from the internal memory; And
The flight control unit operating a fall accident prevention device including an airbag or parachute mounted on a corresponding unmanned aerial vehicle according to the automatic execution of the fall command program
Processing method of the formation departure unmanned aerial vehicle during swarm flight, characterized in that it further comprises.
The method of claim 7,
The flight control unit is divided into a plurality by considering at least one of the remaining battery capacity of the unmanned aerial vehicle in mission, the available mission flight distance according to the remaining battery capacity, a flight environment including weather conditions, and a flight area state including an altitude limit condition. Performing flight control so that the unmanned aerial vehicle in the mission is moved to the undiscovered area or the least searched area among the mission areas
Processing method of the formation departure unmanned aerial vehicle during swarm flight, characterized in that it further comprises.
The method of claim 7,
When another unmanned aerial vehicle adjacent within a certain distance is detected by the sensor detection unit,
An AI big data server accumulating and storing flight history information according to flight control of the flight controller for collision avoidance;
Analyzing, by the AI big data server, the accumulated flight history information to determine the cause of adjacent flights or collisions; And
The IA big data server learning the result of determining the cause of the adjacent flight or collision and providing learning data so that the same accident does not occur during subsequent flights.
Processing method of the formation departure unmanned aerial vehicle during swarm flight, characterized in that it further comprises.

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