KR20200071566A - Method and apparatus for determining an expected flight time for a plurality of drones, computer readable recording medium - Google Patents

Abstract

Provided is a method of automatically determining a new expected flight time for a plurality of drones comprising: a step of, in relation to a preset expected flight time, calculating a flight risk degree for each of the plurality of drones; a step of determining whether to allow the flight of the plurality of drones based on each flight risk degree of each of the plurality of drones calculated for each of the plurality of drones; a step of, when it is determined not to allow the flight of the plurality of drones, calculating each expected flight risk degree for each of the plurality of drones in each of a plurality of future hours distanced at a certain time interval; and a step of determining a new expected flight time for the plurality of drones based on the expected flight risk degree calculated for each of the plurality of drones for each of the future hours.

Description

METHOD AND APPARATUS FOR DETERMINING AN EXPECTED FLIGHT TIME FOR A PLURALITY OF DRONES, COMPUTER READABLE RECORDING MEDIUM}

The present disclosure relates to flight scheduling of multiple drones, and more particularly, to adjustment of flight scheduling of multiple drones used for structure safety check.

Plants, buildings, and structures such as various facilities are all subject to aging over time, and the occurrence of abnormalities due to the aging may directly affect the safety of many people. Therefore, for all structures, safety checks and consequent maintenance processing must be performed continuously. However, many of the structures are in difficult or inaccessible places for human access, so if a person climbs the structure directly and conducts safety checks for them, it is costly and time consuming and may lead to safety accidents. However, these problems are hindering continuous and timely structure safety checks and maintenance.

In response to this problem, in recent years, a case in which a safety check for a corresponding structure is performed by using one or more drones (multicopters) to photograph/image each part of the structure and analyze the result of the shooting. The use of such a drone has an advantage of increasing safety and efficiency related to safety inspection and maintenance of a structure, and enabling quick response in the event of an abnormality.

In order to perform a safety check on a structure by using a drone, a plurality of drones of various standards are simultaneously flying (and photographed or photographed) and data obtained therefrom (for example, a photo/video taking result for each part of the structure, etc.) ) Is required to repeat the process of collecting and monitoring periodically. However, drones are not always permitted to fly, and the specifications of each drone (e.g., weight, number of propellers, flight capability, wind resistance, etc.), weather factors (e.g. wind speed, wind direction, rainy weather, etc.), flight path, and Depending on a number of factors, such as the nature of the structure, there are times when the flight is allowed or not. Therefore, in order to initiate simultaneous flight of multiple drones for safety inspection of structures, it is necessary to first determine whether all drones are allowed to fly at that time, taking into account these various factors, so far, usually the administrator directly intervenes. This decision has been made manually.

According to this conventional method, if, at a certain point in time, the administrator determines that the drones are not allowed to fly at that time, the flight scheduling of these drones, i.e., attempts to fly the drones at a certain time again (i.e., allow flight) Whether or not to retry the decision of whether or not to decide) should be decided only at the manager's discretion, which not only puts a constant burden on the manager, but also may damage the timeliness of the safety inspection of the structure and eventually cause an accident.

Therefore, when a structure safety check is performed using a plurality of drones, a method of automatically scheduling the flight of the plurality of drones, i.e., at what time the next flight attempt will be made, is required. .

According to one feature of the present disclosure, a method is provided for automatically determining new flight prediction times for a plurality of drones. The method of the present disclosure includes: calculating a flight risk for each of the plurality of drones in relation to a preset flight prediction time; Determining whether to allow the plurality of drones to fly, based on each of the flight risks calculated for each of the plurality of drones; If it is determined that the plurality of drones are not allowed to fly, calculating a predicted risk of each flight for each of the plurality of drones at each of the plurality of future times separated by a predetermined time interval; And for each of the future times, determining a new flight prediction time for the plurality of drones based on each of the estimated flight risks calculated for each of the plurality of drones.

According to an embodiment of the present disclosure, the step of calculating the predicted risk of each flight for each of the plurality of drones at each of the future times includes: weather forecast information for each of the future times, and specifications of each drone And calculating at least one of the drone flight path information and the estimated risk of the flight for each drone.

According to an embodiment of the present disclosure, the weather prediction information includes wind speed prediction information, and information about the standard of each drone may include a maximum wind resistance of each drone.

According to an embodiment of the present disclosure, the step of calculating the expected risk of each flight for each of the plurality of drones at each of the future times includes: the wind speed prediction information for each of the future times and the maximum of each drone Calculating wind speed flight risk of each drone based on wind resistance; Calculating a path flight risk of each drone according to the flight path of each drone; Obtaining a weighted sum of the wind speed flight risk and the path flight risk for each drone; And determining an expected risk of final flight of each drone according to each weighted sum for each drone.

According to an embodiment of the present disclosure, the plurality of drones is for performing a safety check on the structure while flying around a predetermined structure, and the risk of flying the wind speed of each drone is the above for each future time The wind speed prediction information is determined as a ratio of the maximum wind resistance of each drone, and the path flight risk of each drone reaches the structure at a point closest to the structure on the flight path of each drone. The interval may be determined as a ratio of the value minus a predetermined reference distance to the predetermined reference distance.

According to an embodiment of the present disclosure, the step of determining a new flight prediction time for the plurality of drones may include, among the future times, all of the estimated final flight risk calculated for each of the plurality of drones is below a predetermined threshold. And, it may include the step of determining the future time of the closest of the future time, the new flight prediction time for the plurality of drones.

According to an embodiment of the present disclosure, the step of determining whether to allow the flight of the plurality of drones may include the flight of the plurality of drones when all of the respective flight risks calculated for each drone are less than a predetermined threshold. And determining to allow.

According to an embodiment of the present disclosure, the step of calculating the flight risk for each of the plurality of drones uses at least one of current weather information, information about the specification of each drone, and flight route information of each drone. Thus, it may include the step of calculating the flight risk for each drone.

According to another feature of the present disclosure, a computer-readable recording medium containing one or more instructions, wherein the one or more instructions, when executed by a computer, cause the computer to perform any one of the methods described above. A computer readable recording medium is provided.

According to another feature of the present disclosure, a computer device comprising: a memory; And a processor, the processor performing a method of any one of the methods described above.

According to the present disclosure, in a structure safety check using a plurality of drones, if it is determined that the drones are not allowed to fly at a certain time, adjustment of the flight scheduling of the drones, that is, attempting to fly the drones at a certain time again (Ie retrying the decision to allow the flight) can be done automatically without the intervention of the administrator. According to the present disclosure, as an administrator, it is not necessary to make additional efforts to determine the timing of deciding whether or not to allow drones to fly, thereby reducing the burden of management. According to the present disclosure, since the flight scheduling of the drones is automatically adjusted, the flight attempts of the drones can be continuously made in a timely manner, and the efficiency and safety of the structure safety check can be improved. According to the present disclosure, it is possible to automatically fly drones, periodically acquire data related to safety inspection, and accordingly, it is possible to expect an effect of constructing an infrastructure capable of quickly discovering, managing, and processing an aging part of the structure.

1 is a diagram schematically showing the overall configuration of a structure safety management system 100 according to an embodiment of the present disclosure.
FIG. 2 is a block diagram schematically showing the functionality of the drone management system 108 shown in FIG. 1.
3 is a functional block diagram for explaining the function of the flight control unit 208 of FIG. 2.
FIG. 4 is a functional block diagram for explaining the function of the flight schedule adjustment unit 210 of FIG. 2.

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Hereinafter, when it is determined that there is a risk of unnecessarily obscuring the subject matter of the present disclosure, a detailed description of already known functions and configurations will be omitted. In addition, it should be understood that the contents described below are only for one embodiment of the present disclosure, and the present disclosure is not limited thereto.

The terms used in this specification are only used to describe specific embodiments and are not intended to limit the present disclosure. For example, a component expressed as a singular should be understood as a concept including a plurality of components unless the context clearly refers to the singular. In addition, in the specification of the present disclosure, terms such as'include' or'have' are only intended to designate the existence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, such as The use of the term is not intended to exclude the possibility of the presence or addition of one or more other features or numbers, steps, actions, components, parts or combinations thereof.

In the embodiments described herein,'block' or'unit' refers to a functional part that performs at least one function or operation, and may be implemented in hardware or software, or a combination of hardware and software. In addition, a plurality of'blocks' or'parts' may be implemented as at least one processor by being integrated with at least one software module, except for'blocks' or'parts' that need to be implemented with specific hardware. .

In addition, unless defined otherwise, all terms used in this specification, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art to which this disclosure belongs. It should be understood that commonly used dictionary-defined terms are to be interpreted as having meanings consistent with contextual meanings of related technologies, and are not to be construed as being excessively limited or extended unless explicitly defined otherwise in the specification of the present disclosure. You should know.

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

1 is a diagram schematically showing a configuration of a structure safety management system 100 according to an embodiment of the present disclosure. As shown, the structure safety management system 100 includes a structure 102, a plurality of drones 104, a communication network 106, and a drone management system 108.

According to one embodiment of the present disclosure, the structure 102 may be various structures, including a predetermined building, plant, facility, and the like. The structure 102 may have various defects affecting safety, such as cracks or breakages, due to aging and other various reasons over time. In this figure, although the structure 102 is shown as a large bridge, it should be understood that the present disclosure is not limited to this, and may be various types of structures that require periodic safety checks.

According to one embodiment of the present disclosure, the plurality of drones 104 may fly around the structure 102 under the control of the drone management system 108, as described below. Although not specifically shown, according to an embodiment of the present disclosure, each of the plurality of drones 104 may be equipped with various sensors including a camera. According to an embodiment of the present disclosure, each of the plurality of drones 104 may take pictures/videos and the like of the structure 102 using a camera or the like while flying along a predetermined path around the structure 102. have. According to an embodiment of the present disclosure, each of the plurality of drones 104 may collect data regarding the structure 102 using various sensors while flying along a predetermined path around the structure 102. According to an embodiment of the present disclosure, various data such as photographs/images captured/collected by each of the plurality of drones 104 may be analyzed for safety diagnosis of the structure 102. In this figure, the structure safety management system 100 is illustrated as including three drones, but the present disclosure is not limited thereto. It should be noted that according to other embodiments of the present disclosure, more or fewer drones may be included. In this figure, each drone 104 is shown as having a quadcopter shape, but the present disclosure is not limited thereto. It should be noted that according to another embodiment of the present disclosure, each of the plurality of drones 104 may have a different shape, and each may be configured to have more or fewer propellers.

According to one embodiment of the present disclosure, the communication network 106 may include any wired or wireless communication network, such as a TCP/IP communication network. According to one embodiment of the present disclosure, the communication network 106 may include, for example, a Wi-Fi network, a LAN network, a WAN network, an Internet network, etc., and the present disclosure is not limited thereto. According to one embodiment of the present disclosure, the communication network 106 is, for example, Ethernet, GSM, Enhanced Data GSM Environment (EDGE), CDMA, TDMA, OFDM, Bluetooth, Wi-MAX, Wibro and any other various wired or wireless communication protocols It can be implemented using.

According to one embodiment of the present disclosure, the drone management system 108 generates control commands for a plurality of drones 104, such as a flight start command, a route control command, and the like, through the communication network 106. Command can be sent. According to an embodiment of the present disclosure, the drone management system 108 may receive data from each of a plurality of drones 104 through a communication network 106, depending on a wired or wireless communication method. This is not a limitation. According to an embodiment of the present disclosure, the drone management system 108 may store a pre-determined drone flight forecast time, and when the predetermined forecast time is reached, along with the weather conditions at the time, the status of each drone and flight path Considering various factors affecting safe flight, such as, it is possible to finally determine whether or not the drones 104 start flying. According to one embodiment of the present disclosure, the drone management system 108 may determine that it is impossible to start the flight of the drones 104 at a predetermined drone flight prediction time. In such a case, the drone management system 108 may automatically determine a new drone flight prediction time for the plurality of drones 104, taking into account the weather forecast situation after the time, and the like.

2 is a block diagram schematically illustrating the functionality of a drone management system 108, according to one embodiment of the present disclosure. As shown, the drone management system 108 includes a communication unit 202, a weather information collection unit 204, a drone status management unit 206, a flight control unit 208, and a flight schedule adjustment unit 210. .

According to an embodiment of the present disclosure, the communication unit 202 may support the drone management system 100 to communicate with the outside through the communication network 106 according to a predetermined wired or wireless communication protocol. According to an embodiment of the present disclosure, the communication unit 202 may enable control commands from the drone management system 108 to be transmitted to each of the plurality of drones 104 through the communication network 106. According to an embodiment of the present disclosure, the communication unit 202 may allow the drone management system 108 to receive various necessary information such as weather information from the outside through the communication network 106.

According to an embodiment of the present disclosure, the meteorological information collection unit 204, through the communication unit 202, various weather-related information (for example, whether it is rainy, etc.) from various weather information providing systems (not shown), including domestic and foreign meteorological offices. Wind speed, wind direction, temperature, humidity, tsunami, fine dust information, UV index, etc. may include current weather information and predicted weather information, but are not limited thereto. According to an embodiment of the present disclosure, the meteorological information collection unit 204, through the communication unit 202, various meteorological data collection devices disposed at locations where structures to be inspected are located, such as a wind direction/anemometer, a thermometer, It is possible to receive the measured current local weather information from a hygrometer or the like.

According to an embodiment of the present disclosure, the drone status management unit 206 may store status information of each drone 104 under the control of the drone management system 108. According to an embodiment of the present disclosure, the drone state management unit 206 includes standard information of each drone 104, such as drone size (W×H×D), weight, propeller number, propeller size, camera resolution, battery, Specification information such as flight capability information such as maximum wind resistance, dynamic status information of each drone 104, flight route information of each drone 104, and various status information of drones that may be related to data collection for safety check Can be saved.

According to an embodiment of the present disclosure, the flight control unit 208 generates a control command for each of the plurality of drones 104, for example, a flight start command, a route control command, and the like, through the communication unit 202. The command can be sent to each drone 104. According to an embodiment of the present disclosure, the flight control unit 208 may store a predetermined drone flight prediction time. According to one embodiment of the present disclosure, the flight control unit 208, when reaching the stored flight prediction time, one or more currents that may affect the flight of the drones 104 from the weather information collection unit 204 Weather information may be received, and one or more status information (such as standard and dynamic status) of each drone 106 may be received from the drone status management unit 206. According to an embodiment of the present disclosure, the flight control unit 208 calculates the flight risk of the drones 104 at this time using the received current weather information and drone status information, and finally based on the flight risk It can be determined whether or not the drones 104 are allowed to start flying. According to an embodiment of the present disclosure, the flight control unit 208, based on the calculated flight risk, determines that the flight start of the drones 104 can be finally permitted at the predetermined flight prediction time, the flight A start command may be generated and transmitted to each drone 104 through the communication unit 202. According to an embodiment of the present disclosure, the flight control unit 208, based on the calculated flight risk, determines that the flight start of the drones 104 cannot be finally permitted at the predetermined flight prediction time. You can cancel the expected flight time.

According to an embodiment of the present disclosure, the flight schedule adjustment unit 210, when the flight control unit 208 determines that the flight start of the drones 104 may not be finally permitted at a predetermined drone flight prediction time, a new You can determine the expected time of flying drones. According to an embodiment of the present disclosure, the flight schedule adjustment unit 210 is set to a predetermined time interval (for example, every 48 hours) after a predetermined drone flight expected time t, for example, every 3 hours. Weather forecast situation for each corresponding time (e.g., t+3, t+6, t+9, t+12, ..., t+48, etc.) for each time, the expected status of each drone, flight path In consideration of various factors such as, it is possible to calculate the expected risk of flight of each of the plurality of drones 104 for each corresponding time (each candidate time). According to an embodiment of the present disclosure, the flight schedule adjustment unit 210 is for each candidate time (eg, t+3, t+6, t+9, t+12, ..., t+48, etc.). In consideration of the results of calculating the expected risk of flight of each of the plurality of drones 104, it is possible to determine a new expected flight time after a predetermined drone flight forecast time (but finally determined to be impossible to fly). According to an embodiment of the present disclosure, when determining a new flight prediction time, the flight schedule adjustment unit 210 may notify the flight control unit 208 of the determined time.

3 is a functional block diagram for explaining the function of the flight control unit 208 of FIG. 2. As illustrated, the flight control unit 208 may include a flight prediction time storage unit 302, a flight permission determination unit 304, and a control command generation unit 306.

According to an embodiment of the present disclosure, the flight prediction time storage unit 302 stores a predetermined flight prediction time, in which a plurality of drones 104 are set to embark on a new flight for safety inspection of the structure 102. It can be. According to an embodiment of the present disclosure, the flight prediction time stored in the flight prediction time storage unit 302 may be a flight prediction time predetermined by the flight schedule adjustment unit 210 as described above.

According to an embodiment of the present disclosure, the flight allowance determination unit 304, at the expected flight time stored in the flight prediction time storage unit 302, as described above, drones from the weather information collection unit 204 One or more current weather information that may affect the flight of 104, and one or more (such as standard and dynamic) status information for each drone 106 from drone status manager 206 (e.g. Drone size (W×H×D), weight, propeller number, propeller size, camera resolution, battery, maximum wind resistance, and other standard information, such as drone flight capability information stored in the drone condition management unit 206, each drone ( 104), dynamic status information of each drone 104, information on one or more of various status information of drones that may be related to data collection for other safety checks). According to an embodiment of the present disclosure, the flight allowance determination unit 304 calculates the flight risk of the drones 104 at this time, based on the received current weather information and drone status information, and based thereon Finally, it can be determined whether or not the drones 104 are allowed to start flying. According to an embodiment of the present disclosure, the flight allowance determination unit 304 compares the calculated flight risk for each drone 104 with a threshold value, and each calculated flight risk for all drones 104 If it is below the threshold, it can be determined that the initiation of flight of the drones 104 is finally permitted. For a specific flight risk calculation, reference may be made to the description of the predicted flight risk calculation unit 402 of FIG. 4.

According to one embodiment of the present disclosure, the control command generation unit 306 generates control commands for each of the plurality of drones 104, such as a flight start command, a route control command, and the like, through the communication unit 202, The generated command can be transmitted to each drone 104. According to an embodiment of the present disclosure, the flight start of the drones 104 may be finally permitted at a predetermined flight prediction time stored in the flight prediction time storage unit 302 by the flight permission determination unit 304. If it is determined, the control command generation unit 306 may generate a flight start command for each drone 104, and transmit the generated command through the communication unit 202. According to an embodiment of the present disclosure, the control command generation unit 306 may generate a flight path control command for each drone 104 and transmit the generated command through the communication unit 202.

FIG. 4 is a functional block diagram for explaining the function of the flight schedule adjustment unit 210 of FIG. 2. As illustrated, the flight schedule adjustment unit 210 may include a flight prediction risk calculation unit 402, a flight prediction time determination unit 404, and a flight scheduling adjustment notification unit 406.

According to an embodiment of the present disclosure, the flight prediction risk calculation unit 402, as described above, is previously determined by the flight control unit 208, whether the flight is allowed or not, the flight prediction time t determined by the determination unit 304. If it is finally determined that the flight of drones 104 is unacceptable, over a period of time (e.g., 48 hours thereafter) after that time t, at regular time intervals (e.g., every 3 hours) Weather forecast situation (e.g. wind speed forecast data, etc.) of each relevant time (e.g., t+3, t+6, t+9, t+12, ..., t+48, etc.) Information may be received from the weather information collection unit 204. According to an embodiment of the present disclosure, the flight predicted risk calculation unit 402 is also a specification of the status information of each drone 104 (eg, the maximum wind resistance value of each drone 104) from the drone status management unit 206 Information, dynamic expected state information of each drone 104, flight path information of each drone 104, one or more of various other information). According to an embodiment of the present disclosure, the flight prediction risk calculation unit 402 takes into account various factors received from the weather information collection unit 204 and/or the drone status management unit 206, and includes a plurality of times for each candidate time. The estimated risk of each drone 104 may be calculated.

According to an embodiment of the present disclosure, the predicted flight risk calculation unit 402 is, for example, according to the following equation, wind speed forecast data of each drone 104 (wind speed prediction information received from the weather information collection unit 204) The flight risk (A) and the flight risk according to the flight path of each drone (104) may be calculated.

[Equation 1]

A = predicted wind speed/drone maximum wind resistance (when the predicted wind speed is less than the drone maximum wind resistance)

A = 1 (when the predicted wind speed is equal to or greater than the maximum wind resistance)

[Equation 2]

B = (reference distance-shortest distance from the structure of the flight path)/reference distance (when the shortest distance from the structure of the flight path is equal to or less than the reference distance)

B = 0 (when the shortest distance from the structure of the flight path is greater than the reference distance)

According to an embodiment of the present disclosure, the flight predicted risk calculation unit 402, the final flight through the weighted sum of the estimated flight risk (A) according to the calculated wind speed data and the expected flight risk (B) according to the flight path The expected risk (C) can be determined. According to an embodiment of the present disclosure, for example, the weight of the estimated risk of flight (A) according to the wind speed data may be set to 70%, and the weight of the estimated risk of flight (B) according to the flight path may be set to 30%. . According to an embodiment of the present disclosure, for example, when the maximum wind resistance of the drone 104 is 38 Km/h and the predicted wind speed is 30 Km/h, A=(30/38)=0.789, and the path reference distance 5m (can be set arbitrarily depending on the situation), if the shortest distance from the structure 102 in the flight path is 2m, B=(5-2)/5=0.6, and the final risk is C=0.7* It can be calculated as A+0.3*B=0.7*(0.789)+0.3*(0.6)=0.5523+0.18=0.7323. In this case, the final estimated risk (C) can be calculated to be about 73.23%. The method for calculating the expected risk of flight of the flight predicted risk calculation unit 402 described herein, that is, the predicted risk of flight according to the wind speed data information for the maximum wind resistance value of the drone, and the predicted risk of flight according to the flight path, are weighted. It should be understood that the method of calculating the final flight expected risk through (and each reference value used) is only an embodiment of the present disclosure. According to another embodiment of the present disclosure, the flight predicted risk calculation unit 402 is based on one or more information received from the weather information collection unit 204 and the drone status management unit 206, each drone 104 in various ways. ), the estimated risk of flight at each candidate time can be calculated. In addition, the flight risk calculation for determining whether to allow the flight of the flight control unit 208 to allow or not the flight control unit 208 may be performed according to the same or a similar method to calculating the expected flight risk by the flight prediction risk calculation unit 402. However, the present disclosure is not so limited.

According to an embodiment of the present disclosure, the flight prediction time determination unit 404 comprehensively considers the flight prediction risk calculation result for each candidate time of each drone 104 by the flight prediction risk calculation unit 402 After that, it is possible to find a time when the expected risk of flying of all the drones 104 is less than a threshold, and determine a new expected flight time. For example, the following table is a flight prediction risk based on wind speed data information for the maximum wind resistance value of the drone, for the example described above with respect to the flight prediction risk calculation unit 402, that is, for a given drone 104. ) And in the example of calculating the predicted risk of flight (B) according to the flight path of the drone 104 and calculating the final predicted risk through weighting of them, assuming that the comparison threshold of flight risk is 40% , Indicates a time that can be a new expected flight time among the candidate times (for example, each of the candidate times of t+3, t+6, 6+9, ..., t+48) (of the present disclosure). It should be understood that the disclosure is not limited to this, but is only limited to one embodiment). As shown, the possible time of the new flight prediction time for the drone 104 is the time 6 hours after the current time (t+6), the time 9 hours later (t+9), and the time 12 hours later ( t+12). It should be noted that the following table relates to one drone among the plurality of drones 104, and for each drone, the following table may be prepared. In this example, the threshold value is set to 40%, but it should be understood that the present disclosure is not limited to this, and according to another embodiment of the present disclosure, the threshold value may be appropriately adjusted according to the administrator's judgment. According to an embodiment of the present disclosure, the threshold value used for determining a new flight prediction time by the flight prediction time determination unit 404 is used by the flight control unit 208 of the flight control unit 208 described above. Can be equal to or different from the threshold. According to an embodiment of the present disclosure, the threshold value used for determining a new flight prediction time by the flight prediction time determination unit 404 is used by the flight control unit 208 of the flight control unit 208 described above. It may be a value lower than the threshold.

Candidate time Wind speed (Km/h) Flight risk (%) New flight forecast visual possibilities Remark Current time (t) 30 73.26 X t + 3 20 54.84 X t + 6 10 36.42 O t + 9 5 27.21 O t + 12 3 23.53 O t + 15 15 45.63 X t + 18 25 64.05 X ... ... ... ...

According to an embodiment of the present disclosure, the flight prediction time determination unit 404 comprehensively considers the risk of flight prediction for each candidate time and the possibility of new flight prediction time according to each of the plurality of drones 104 The time at which all drones 104 are expected to be able to fly (i.e., the time at which all drones 104 are expected to have a new expected time of flight) has been previously determined (but finally determined to be impossible to fly). ) It can be determined as a new flight prediction time after the flight prediction time. According to an embodiment of the present disclosure, the flight scheduling adjustment notification unit 406 determines the new flight prediction time determined by the flight prediction time determination unit 404. The flight control unit 208 can be notified. According to an embodiment of the present disclosure, the flight scheduling adjustment notification unit 406 may notify the administrator of the new flight prediction time determined by the flight prediction time determination unit 404 and receive confirmation from the manager. According to one embodiment of the present disclosure, the flight scheduling adjustment notification unit 406 notifies the manager of the new flight prediction time determined by the flight prediction time determination unit 404, and after receiving confirmation from the manager, the newly determined The expected flight time may be notified to the flight control unit 208.

As will be appreciated by those skilled in the art, the present disclosure is not limited to the examples described herein, but may be variously modified, reconstructed, and replaced without departing from the scope of the present disclosure. For example, various techniques described herein can be implemented by hardware or software, or a combination of hardware and software. Thus, a particular aspect or portion of an analysis machine for software safety analysis according to the present application may be implemented as one or more computer programs executable by a general purpose or dedicated microprocessor, micro-controller, or the like. A computer program according to an embodiment of the present disclosure includes a storage medium readable by a computer processor or the like, such as EPROM, EEPROM, non-volatile memory such as a flash memory device, magnetic disks such as internal hard disks and removable disks, magneto-optical disks, and It can be implemented in a form stored in various types of storage media, including CDROM disks. Further, the program code(s) may be implemented in assembly language or machine language, and may also be implemented in a form transmitted through electrical wiring or cabling, optical fiber, or any other form of transmission medium.

In this specification, exemplary embodiments have been mainly described with reference to various drawings, but other similar embodiments may be used. All modifications and changes belonging to the true spirit and scope of the present disclosure are intended to be covered by the following claims.

Claims (10)

As a method for automatically determining a new flight prediction time for multiple drones,
Calculating a flight risk for each of the plurality of drones in relation to a preset flight prediction time;
Determining whether to allow the plurality of drones to fly, based on each of the flight risks calculated for each of the plurality of drones;
If it is determined that the plurality of drones are not allowed to fly, calculating a predicted risk of each flight for each of the plurality of drones at each of the plurality of future times separated by a predetermined time interval; And
For each of the future times, determining a new expected flight time for the plurality of drones based on the estimated risk of each flight calculated for each of the plurality of drones
A method of determining a predicted flight time, which includes. According to claim 1,
The step of calculating the predicted risk of each flight for each of the plurality of drones at each of the future times includes weather prediction information for each future time, information about the specifications of each drone, and the flight route of each drone And calculating, by using at least one of the information, the predicted risk of flight for each of the drones. According to claim 2,
The weather prediction information includes wind speed prediction information,
The information regarding the standard of each drone includes a maximum wind resistance of each drone, and a method for determining a predicted flight time. According to claim 3,
Computing the estimated risk of each flight for each of the plurality of drones at each of the future time,
Calculating a wind speed flight risk of each drone based on the wind speed prediction information for each future time and the maximum wind resistance of each drone;
Calculating a path flight risk of each drone according to the flight path of each drone;
Obtaining a weighted sum of the wind speed flight risk and the path flight risk for each drone; And
And determining, according to each weighted sum for each drone, a predicted risk of final flight of each drone. The method of claim 4,
The plurality of drones is for performing a safety check on the structure while flying around a predetermined structure,
The wind speed flight risk of each drone is determined as a ratio of the wind speed prediction information for each future time to the maximum wind resistance of each drone,
The route flight risk of each drone is determined as a ratio of the distance from the closest point to the structure on the flight path of each drone to the structure as a ratio to the predetermined reference distance minus a predetermined reference distance. Losing, how to determine the expected flight time. The method of claim 4,
Determining a new flight prediction time for the plurality of drones, among the future times, all of the estimated final flight risks calculated for each of the plurality of drones are less than a predetermined threshold, and the closest of the future times And determining a future time as the new expected flight time for the plurality of drones. According to claim 1,
Determining whether or not to allow the flight of the plurality of drones includes determining that the flight of the plurality of drones is permitted when all of the respective flight risks calculated for each drone are less than a predetermined threshold. , How to determine the expected flight time. According to claim 1,
The step of calculating the flight risk for each of the plurality of drones may include using the current weather information, information about the standard of each drone, and flight path information of each drone, to perform the flight for each drone. A method of determining an expected flight time, comprising calculating a risk. A computer-readable recording medium containing one or more instructions, wherein the one or more instructions, when executed by a computer, cause the computer to perform the method according to claim 1. Recordable media. As a computer device,
Memory; And
Including a processor,
The processor performs a method according to any one of claims 1 to 8, a computer device.

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