KR102176132B1 - Method and apparatus for determining an expected flight time for a plurality of drones, computer readable recording medium - Google Patents

Abstract

A method is provided for automatically determining a new flight estimate for multiple drones. The method includes: calculating a flight risk for each of the plurality of drones in association with a preset flight prediction time; Determining whether or not to allow the plurality of drones to fly based on the flight risk, calculated for each of the plurality of drones; When it is determined that the flight of the plurality of drones is not allowed, calculating an expected flight risk for each of the plurality of drones at each of the future times at each of a plurality of future times separated by a predetermined time interval; And determining a new expected flight time for the plurality of drones at each future time, based on each of the estimated flight risk calculated for each of the plurality of drones.

Description

TECHNICAL FIELD: 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 specifically, to adjustment of flight scheduling of multiple drones used for structural safety inspection.

All structures such as plants, buildings, and various facilities are apt to undergo deterioration over time, and the occurrence of abnormalities due to such deterioration can directly affect the safety of many people. Therefore, for all structures, safety checks and maintenance treatments accordingly must be carried out continuously. However, many of the structures are located in locations that are difficult or dangerous to access by humans, so if a person directly climbs the structure and goes to safety checks, there is a possibility that it will take a lot of cost and time and cause a safety accident. However, these problems are hindering the ongoing and timely structure safety inspection and maintenance process.

In response to this problem, in recent years, more than one drone (multicopter) is used to take pictures/videos of each part of a structure, and the case of performing a safety check on a corresponding structure by analyzing the shooting result is increasing. The use of such a drone is advantageous in that it is possible to increase safety and efficiency related to safety inspection and maintenance of a structure, and to enable a quick response when an abnormality occurs.

In order to perform safety checks on structures using drones, multiple drones of various standards are simultaneously flying (and photographed or video taken) and data obtained therefrom (e.g., photo/video shooting results for each part of the structure, etc.) ) Collection and monitoring must be repeated periodically. However, drones are not always allowed to fly, and the specifications of each drone (e.g., weight, number of propellers, flight capability, wind resistance value, etc.), weather factors (e.g., wind speed, wind direction, rain, etc.), flight path and Depending on the characteristics of the structure and other factors, the flight may or may not be permitted. Therefore, in order to initiate simultaneous flight of multiple drones for structural safety inspection, considering these various factors, it must first be determined whether all drones will be allowed to fly at that time. Until now, the manager has usually directly intervened. These decisions have been made manually.

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

Therefore, when a structure safety inspection is performed using a plurality of drones, there is a need for a method of automatically determining the flight scheduling of the plurality of drones, that is, at what point the next flight attempt will be made, without the intervention of the manager. .

According to an aspect of the present disclosure, a method for automatically determining a new flight prediction time for a plurality of drones is provided. 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 or not to allow the plurality of drones to fly based on the flight risk, calculated for each of the plurality of drones; When it is determined that the flight of the plurality of drones is not allowed, calculating an expected flight risk for each of the plurality of drones at each of the future times at each of a plurality of future times separated by a predetermined time interval; And determining a new expected flight time for the plurality of drones at each future time, based on each of the estimated flight risk calculated for each of the plurality of drones.

According to an embodiment of the present disclosure, the calculating of the estimated flight risk for each of the plurality of drones at each of the future times includes weather prediction information for each future time, and the standard of each drone. Using at least one of information and flight path information of each of the drones, calculating the expected flight risk for each of the drones.

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

According to an embodiment of the present disclosure, the calculating of the estimated flight risk for each of the plurality of drones at each of the future times includes the wind speed prediction information for each future time and the maximum Calculating a wind speed flight risk of each of the drones 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 of the drones; And determining a final flight predicted risk of each drone according to the weighted sum for each of the drones.

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

According to an embodiment of the present disclosure, the determining of a new flight estimated time for the plurality of drones includes, among the future times, the final flight estimated risk calculated for each of the plurality of drones are all less than a predetermined threshold. And determining the nearest future time among the future times as the new flight prediction times 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 includes the flight of the plurality of drones when the flight risks calculated for each of the drones are all less than a predetermined threshold. It may include determining to allow.

According to an embodiment of the present disclosure, the calculating of the flight risk for each of the plurality of drones includes at least one of current weather information, information on the standard of each drone, and flight path information of each drone. Thus, it may include calculating the flight risk for each of the drones.

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

According to another aspect of the present disclosure, a computer device comprising: a memory; And a processor, wherein the processor performs any one of the above-described methods.

According to the present disclosure, when it is determined that the flight of drones is not allowed at any one point in the structure safety inspection using a plurality of drones, the flight scheduling of these drones is adjusted, that is, attempts to fly these drones again at some point. Whether to (i.e., retry the decision on whether to allow the flight) can be made automatically without the intervention of the manager. According to the present disclosure, there is no need for a manager to make additional efforts to determine the timing of determining 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 well and in a timely manner, and the efficiency and safety of structural safety inspection can be improved. According to the present disclosure, it is possible to automatically fly drones and obtain data on safety checks periodically, and accordingly, an effect of building an infrastructure capable of quickly discovering, managing, and handling deteriorated parts of structures can be expected.

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 illustrating the functions 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, exemplary 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 possibility that the subject matter of the present disclosure may be unnecessarily obscured, detailed descriptions of functions and configurations already known are omitted. In addition, it should be understood that the contents described below are only related to an 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 in the singular should be understood as a concept including a plurality of components unless the context clearly means only 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, actions, components, parts, or a combination thereof described in the specification. The use of the term is not intended to exclude the possibility of the presence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

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

In addition, unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. Terms defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and are not interpreted as excessively limited or expanded unless explicitly defined otherwise in the specification of the present disclosure. You should know.

Hereinafter, exemplary 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 an embodiment of the present disclosure, the structure 102 may be various structures including a predetermined building, plant, or facility. The structure 102 may have various defects that affect safety, such as cracking or breaking due to aging over time and various other reasons. In this drawing, the structure 102 is shown as a large bridge, but it should be understood that the present disclosure is not limited thereto, and may be various types of structures requiring periodic safety checks.

According to an 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 later. 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 can take pictures/videos about the structure 102 using a camera, etc., while flying along a predetermined path around the structure 102. have. According to the exemplary embodiment of the present disclosure, each of the plurality of drones 104 may collect data on 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/videos captured/collected by each of the plurality of drones 104 may be analyzed for safety diagnosis of the structure 102. In this drawing, the structure safety management system 100 is shown to include 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 less drones may be included. In this drawing, each drone 104 is shown to have 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 in a shape having more or less propellers.

According to an 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 an 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, and the like, and the present disclosure is not limited thereto. According to an embodiment of the present disclosure, the communication network 106 is, for example, Ethernet, GSM, EDGE (Enhanced Data GSM Environment), CDMA, TDMA, OFDM, Bluetooth, Wi-MAX, Wibro and any of various wired or wireless communication protocols. It can be implemented using

According to an embodiment of the present disclosure, the drone management system 108 generates a control command for a plurality of drones 104, such as a flight start command, a path control command, and the like, and through the communication network 106, the generation You can send the command. According to an embodiment of the present disclosure, the drone management system 108 may receive data from each of the plurality of drones 104 through the communication network 106 according to a wired or wireless communication method, but the present disclosure It is not so limited. According to an embodiment of the present disclosure, the drone management system 108 may store a predetermined predicted drone flight time, and when the predetermined predicted time is reached, the state of each drone, along with the weather condition at the time, and the flight path In consideration of various factors that affect safety flight, such as, it is possible to finally determine whether the drones 104 start flying. According to an embodiment of the present disclosure, the drone management system 108 may determine that the drones 104 cannot start flying at a predetermined drone flight expected 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 in consideration of the weather prediction situation and the like after that time.

2 is a block diagram schematically illustrating a function of the drone management system 108 according to an 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 state 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 transmit a control command from the drone management system 108 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, from various weather information providing systems (not shown) including domestic and foreign meteorological agencies, etc. Current weather information and predicted weather information about wind speed, wind direction, temperature, humidity, tsunami, fine dust information, UV index, etc. may be included, but are not limited thereto. According to an embodiment of the present disclosure, the meteorological information collecting unit 204, through the communication unit 202, is a variety of meteorological data collecting devices disposed at a location where the structure to be inspected is located, such as a wind direction/anemometer, a thermometer, The measured current local weather information may be received from a hygrometer or the like.

According to an embodiment of the present disclosure, the drone state management unit 206 may store state 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, number of propellers, propeller size, camera resolution, battery, Standard information such as flight capability information such as maximum wind resistance, dynamic status information of each drone 104, flight path information of each drone 104, and various status information of drones that may be related to data collection for other safety inspections 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 path control command, and the like, and through the communication unit 202, the generation The command can be transmitted to each drone 104. According to an embodiment of the present disclosure, the flight control unit 208 may store a predetermined predicted drone flight time. According to an embodiment of the present disclosure, the flight control unit 208, from the meteorological information collection unit 204, when the stored flight prediction time is reached, one or more currents that may affect the flight of the drones 104 Weather information may be received, and one or more state information (such as standard and dynamic state) for each drone 106 may be received from the drone state 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 point using the received current weather information and the drone status information, and finally It is possible to determine whether the drones 104 will be allowed to start flying. According to an embodiment of the present disclosure, the flight control unit 208, based on the calculated flight risk, when it is determined that the flight start of the drones 104 can be finally allowed at the predetermined flight expected 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, when it is determined that the flight start of the drones 104 is finally not allowed at the predetermined flight expected time, the You can cancel the estimated flight time.

According to an embodiment of the present disclosure, if the flight schedule adjustment unit 210 determines that the flight start of the drones 104 cannot be finally allowed at a predetermined drone flight expected time, the flight schedule adjustment unit 210 You can determine the expected time of flight of the drone. According to an embodiment of the present disclosure, the flight schedule adjustment unit 210 may be performed at a predetermined time interval (eg, every 3 hours) from the predetermined drone flight estimated time t to a predetermined time (eg, 48 hours thereafter). Time), weather forecasting situation at each corresponding time (e.g., t+3, t+6, t+9, t+12, ..., t+48, etc.), expected state of each drone, flight path Considering various factors such as, it is possible to calculate the estimated flight risk of each of the plurality of drones 104 at each corresponding time (each candidate time). According to an embodiment of the present disclosure, the flight schedule adjustment unit 210 is configured for each candidate time (eg, t+3, t+6, t+9, t+12, ..., t+48, etc.). By comprehensively considering the flight predicted risk calculation result of each of the plurality of drones 104, a new flight predicted time after the predetermined (but finally determined to be impossible to fly) drone flight predicted time may be determined. According to an embodiment of the present disclosure, when the flight schedule adjustment unit 210 determines a new flight expected time, the determined time may be notified to the flight control unit 208.

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 allowance determination unit 304, and a control command generation unit 306.

According to an embodiment of the present disclosure, the flight predicted time storage unit 302 stores a predetermined flight predicted time, which is determined so that the plurality of drones 104 start a new flight for safety inspection of the structure 102, and There may be. According to an embodiment of the present disclosure, the flight predicted time stored in the flight predicted time storage unit 302 may be a flight predicted time predetermined by the flight schedule adjusting unit 210 as described above.

According to an embodiment of the present disclosure, the flight allowance determination unit 304 is, as described above, at the flight estimated time stored in the flight estimated time storage unit 302, from the meteorological information collection unit 204, drones One or more current weather information that may affect the flight of 104 can be received, and one or more (such as standard and dynamic conditions) status information (such as standard and dynamic status) about each drone 106 from the drone status management unit 206 , Each standard information such as drone size (W×H×D), weight, number of propellers, propeller size, camera resolution, battery, maximum wind resistance, etc., stored in the drone status management unit 206, and each drone ( 104), the flight path information of each drone 104, and one or more of various state information of the drone that may be related to data collection for other safety checks) may be received. According to an embodiment of the present disclosure, the flight allowance determination unit 304 calculates the flight risk of the drones 104 at this point by using the received current weather information and the drone state information, and based on it Thus, it is finally possible to determine whether the drones 104 are allowed to start flying. According to an embodiment of the present disclosure, the flight allowance determination unit 304 compares the flight risk calculated for each drone 104 with a threshold value, and the calculated flight risk for all drones 104 If it is less than the threshold value, it may be finally determined that the drones 104 are allowed to start flying. For detailed flight risk calculation, reference may be made to the description of the estimated flight risk calculation unit 402 of FIG. 4.

According to an embodiment of the present disclosure, the control command generation unit 306 generates a control command for each of the plurality of drones 104, for example, a flight start command, a path control command, and the like, and through the communication unit 202, The generated command can be transmitted to each drone 104. According to an embodiment of the present disclosure, by the flight permission determination unit 304, the flight start of the drones 104 may be finally allowed at a predetermined flight estimated time stored in the flight estimated time storage unit 302. If it is determined that there is, 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 shown, the flight schedule adjustment unit 210 may include a flight estimated risk calculation unit 402, a flight estimated time determination unit 404, and a flight scheduling adjustment notification unit 406.

According to an embodiment of the present disclosure, the flight predicted risk calculation unit 402 is, as described above, by the flight allowance determination unit 304 of the flight control unit 208, a predetermined flight predicted time t In the event that it is finally determined that the flight of the drones 104 is not allowed, it is determined that the flight of the drones 104 is not allowed, over a predetermined period of time (e.g., 48 hours thereafter) after the time (t), and at a predetermined time interval (e.g., every 3 hours). Regarding, weather forecasting conditions (e.g., wind speed forecast data, etc.) at each corresponding time (e.g., t+3, t+6, t+9, t+12, ..., t+48, etc.) Information may be received from the meteorological information collection unit 204. According to an embodiment of the present disclosure, the flight predicted risk calculation unit 402 is also provided with the state information of each drone 104 from the drone state management unit 206 (eg, a standard such as the maximum wind resistance value of each drone 104). Information, dynamic predicted state information of each drone 104, flight path information of each drone 104, and one or more of various other information) may be received. According to an embodiment of the present disclosure, the flight predicted risk calculation unit 402 considers various factors received from the meteorological information collection unit 204 and/or the drone state management unit 206, and includes a plurality of It is possible to calculate the estimated risk of each flight of the drone 104.

According to an embodiment of the present disclosure, the flight predicted risk calculation unit 402 is based on, for example, the wind speed forecast data of each drone 104 (wind speed prediction information received from the weather information collection unit 204) according to the following equation. It is possible to calculate the flight risk according to the flight risk (A) and the flight risk according to the flight path of each drone 104 (the risk of collision of surrounding structures B).

[Equation 1]

A = predicted wind speed/drone maximum wind resistance (when predicted wind speed is less than 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-the shortest distance from the structure in the flight path) / reference distance (when the shortest distance from the structure in the flight route is equal to or less than the reference distance)

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

According to an embodiment of the present disclosure, the flight predicted risk calculation unit 402 is a final flight through the sum of the weights of the predicted flight risk (A) according to the wind speed data calculated previously and the flight predicted 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 expected flight risk (A) according to the wind speed data may be set to 70%, and the weight of the expected flight risk (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 38Km/h and the predicted wind speed is 30Km/h, A=(30/38)=0.789, and the route reference distance 5m (can be set arbitrarily according to the situation), if the shortest distance between the flight path and the structure 102 is 2m, B=(5-2)/5=0.6, and the final risk 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 expected risk (C) can be calculated to be about 73.23%. The flight predicted risk calculation method of the flight predicted risk calculation unit 402 described here, that is, the predicted flight risk according to the wind speed data information for the maximum wind resistance value of the drone, and the flight predicted risk according to the flight path are calculated, and their weighted sum It should be understood that the method of calculating the final flight predicted risk (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 meteorological information collection unit 204 and the drone state management unit 206, and each drone 104 The estimated flight risk at each candidate time of) can be calculated. In addition, the flight risk calculation for the flight allowance determination unit 304 of the flight control unit 208 to determine whether to allow the flight is performed in the same or similar manner as the flight expected risk calculation by the flight expected risk calculation unit 402. However, the present disclosure is not limited thereto.

According to an embodiment of the present disclosure, the flight predicted time determination unit 404 comprehensively considers the flight predicted risk calculation result for each candidate time of each drone 104 by the flight predicted risk calculation unit 402 After that, it is possible to find a time when the estimated flight risk of all the drones 104 is less than the threshold value, and determine a new flight estimated time. For example, the following table is the example previously described with respect to the flight predicted risk calculation unit 402, that is, with respect to the predetermined drone 104, the predicted flight risk based on wind speed data information for the maximum wind resistance value of the drone (A ) And the estimated flight risk (B) according to the flight path of the drone 104 and the final flight estimated risk through weighted summation, assuming that the comparison threshold of the flight risk is 40% , It indicates a time that can become a new flight prediction time among candidate times (e.g., each candidate time of t+3, t+6, 6+9, ..., t+48). It should be understood that the present disclosure is only related to one embodiment, and the present disclosure is not limited thereto). As shown, the possible times for the new flight estimated time for the drone 104 are 6 hours after the current time (t+6), 9 hours after (t+9), and 12 hours later ( t+12) and the like. It should be noted that the following table relates to one of the plurality of drones 104, and for each drone, the following table may be created. In this example, the threshold is set to 40%, but the present disclosure is not limited thereto, and it should be understood that according to another embodiment of the present disclosure, the threshold may be appropriately adjusted according to the judgment of the administrator. According to an embodiment of the present disclosure, the threshold value used for determining a new flight expected time by the flight expected time determination unit 404 is used by the flight permission determination unit 304 of the flight control unit 208 described above. It may be the same as or different from the threshold value. According to an embodiment of the present disclosure, the threshold value used for determining a new flight expected time by the flight expected time determination unit 404 is used by the flight permission determination unit 304 of the flight control unit 208 described above. It may be a value lower than the threshold value.

Candidate time Wind speed (Km/h) Flight risk (%) Possible new flight forecast times 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 predicted time determination unit 404 comprehensively considers the predicted flight risk for each of the plurality of drones 104, and the possibility of a new flight predicted time accordingly. , The time at which all the drones 104 are expected to be able to fly (that is, the time it is determined that there is a possibility of a new flight forecast for all drones 104) is predetermined (but finally, it is decided that flight is impossible). ) It may be determined as a new flight expected time after the flight expected time. According to an embodiment of the present disclosure, the flight scheduling adjustment notification unit 406 may determine the new flight expected time determined by the flight expected time determination unit 404 It can be notified to the flight control unit 208. According to an exemplary embodiment of the present disclosure, the flight scheduling adjustment notification unit 406 may notify the manager of the new flight expected time determined by the flight expected time determination unit 404 and receive confirmation thereof from the manager. According to an embodiment of the present disclosure, the flight scheduling adjustment notification unit 406 notifies the manager of the new flight expected time determined by the flight expected time determination unit 404, and after receiving confirmation from the manager, the newly determined The flight predicted 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, and various modifications, reconfigurations, and substitutions may be made without departing from the scope of the present disclosure. For example, the various techniques described herein may be implemented by hardware or software, or a combination of hardware and software. Accordingly, a specific aspect or part of an analysis machine for software safety analysis according to the present disclosure 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, such as EPROM, EEPROM, a nonvolatile memory such as a flash memory device, a magnetic disk such as an internal hard disk and a removable disk, a magneto-optical disk, and It can be implemented in a form stored in various types of storage media, including a CDROM disk. In addition, the program code(s) may be implemented in assembly language or machine language, and may be implemented in a form transmitted through electrical wiring, cabling, optical fiber, or any other type of transmission medium.

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

Claims (10)

As a method for automatically determining a new flight forecast for multiple drones,
Calculating a flight risk for each of the plurality of drones in association with a preset flight prediction time;
Determining whether or not to allow the plurality of drones to fly based on the flight risk, calculated for each of the plurality of drones;
When it is determined that the flight of the plurality of drones is not allowed, calculating an expected flight risk for each of the plurality of drones at each of the future times at each of a plurality of future times separated by a predetermined time interval; And
For each of the future times, based on each of the estimated flight risk calculated for each of the plurality of drones, determining a new flight expected time for the plurality of drones,
The step of calculating the predicted flight risk for each of the plurality of drones at each of the future times includes weather prediction information for each future time, information on the standard of each drone, and a flight path of each drone Using at least one of the information, including the step of calculating the estimated flight risk for each of the drones,
The weather prediction information includes wind speed prediction information,
The information on the standard of each drone includes the maximum wind resistance of each drone,
The step of calculating the expected 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 of the drones according to the flight paths of each of the drones;
Obtaining a weighted sum of the wind speed flight risk and the path flight risk for each of the drones; And
In accordance with the weighted sum for each of the drones, comprising the step of determining a final flight expected risk of each of the drones, flight prediction time determination method. delete delete delete The method of claim 1,
The plurality of drones are for performing safety checks on the structure while flying around a predetermined structure,
The wind speed flight risk of each of the drones 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 of the drones is determined as a ratio to the predetermined reference distance of a value obtained by subtracting the distance from the point closest to the structure to the structure on the flight route of each drone from a predetermined reference distance. Losing, how to determine the expected flight time. The method of claim 1,
Determining a new expected flight time for the plurality of drones may include, among the future times, if all of the final flight predicted risks calculated for each of the plurality of drones are less than a predetermined threshold, the closest arrival among the future times And determining a future time to be the new flight expected time for the plurality of drones. The method of claim 1,
Determining whether to allow the flight of the plurality of drones comprises determining to allow the flight of the plurality of drones when the flight risks calculated for each of the drones are all less than a predetermined threshold. , How to determine the expected flight time. The method of claim 1,
The step of calculating the flight risk for each of the plurality of drones may include using at least one of current weather information, information on the standard of each drone, and flight path information of each drone, and the flight for each drone A method of determining an estimated flight time, comprising the step of 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 any one of claims 1 and 5 to 8. A computer-readable recording medium. As a computer device,
Memory; And
Including a processor,
The computer device, wherein the processor performs the method according to any one of claims 1 and 5 to 8.

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