Radio wave environment estimation device, radio wave environment estimation method, and recording medium

Abstract

In order to enable an unmanned flying object to be flown more safely, provided is a radio wave environment estimation device that: receives measured radio wave information, which is information relating to an actual measurement value, obtained by measurement at a measurement point, of a radio wave index, the radio wave index being an index relating to a radio wave environment which is an environment of a radio wave pertaining to a control radio wave for controlling the unmanned flying object; uses an estimation model to estimate a three-dimensional distribution on the basis of the measured radio wave information, the three-dimensional distribution being a distribution of the radio wave environment in a three-dimensional space which includes an area for flying the unmanned flying object and the measurement point; and outputs estimated radio wave information, which is information relating to the three-dimensional distribution.

Description

Radio wave environment estimation device, radio wave environment estimation method, and recording medium

[0001] The present disclosure relates to a radio wave environment estimation device, a radio wave environment estimation method, and a recording medium.

[0002] Many pieces of equipment are in operation at airports. These pieces of equipment deteriorate over time. Therefore, it is important to inspect these pieces of equipment in order to maintain them.

[0003] However, when inspecting facilities manually, securing personnel for inspection becomes a problem. Therefore, it is being considered to solve the problem of securing personnel by using unmanned aerial vehicles to inspect facilities.

[0004] The unmanned aerial vehicle receives control radio waves for controlling the unmanned aerial vehicle, and flies in accordance with the control signals contained in the control radio waves.

[0005] However, within the areas where unmanned aerial vehicles fly for equipment inspections, there may be locations where the unmanned aerial vehicles are unable to properly receive control radio waves. For example, there may be locations where the control radio waves are weak or cannot reach. Furthermore, at airports, various radio waves are flying around in addition to the control radio waves for unmanned aerial vehicles. Therefore, there may be locations where unmanned aerial vehicles are unable to receive control radio waves due to the influence of other radio waves.

[0006] Furthermore, regarding the flight of an unmanned aerial vehicle, Patent Document 1 describes generating a flight route as a candidate route that includes as few locations with poor environments as possible, and lists locations with poor radio wave environments as an example of an environmental parameter.

[0007] Japanese Patent Application Laid-Open No. 2023-040726

[0008] Regarding understanding the radio wave environment, it is possible to understand the radio wave environment on the ground by measuring the radio wave environment at measurement points on the ground. However, the radio wave environment in the air is different from that on the ground. If an unmanned aerial vehicle is flown without sufficient understanding of the radio wave environment in the air, the unmanned aerial vehicle may not be able to receive control radio waves and may not be able to fly safely.

[0009] In view of the above-mentioned problems, the object of the present disclosure is to provide a radio wave environment estimation device, a radio wave environment estimation method, and a recording medium that enable unmanned aerial vehicles to fly more safely.

[0010] In one aspect of the present disclosure, a radio wave environment estimation device comprises a receiving means for receiving measured radio wave information, which is information regarding the actual measured value of a radio wave index, which is an index regarding the radio wave environment, which is the environment of radio waves related to control radio waves for controlling an unmanned aerial vehicle, measured at a measurement point; an estimation means for estimating, using an estimation model, a three-dimensional distribution, which is the distribution of the radio wave environment in a three-dimensional space, which is a space including the area in which the unmanned aerial vehicle is flown and the measurement point; and an output means for outputting estimated radio wave information, which is information regarding the three-dimensional distribution, wherein the estimation model estimates the three-dimensional distribution based on the measured radio wave information.

[0011] In another aspect of the present disclosure, a radio wave environment estimation method receives measured radio wave information, which is information regarding the actual measured value measured at a measurement point of a radio wave index, which is an index regarding the radio wave environment, which is the environment of radio waves related to control radio waves for controlling an unmanned aerial vehicle, estimates a three-dimensional distribution, which is the distribution of the radio wave environment in a three-dimensional space that includes the area in which the unmanned aerial vehicle is flown and the measurement point, using an estimation model that estimates the three-dimensional distribution based on the measured radio wave information, and outputs estimated radio wave information, which is information regarding the three-dimensional distribution.

[0012] In another aspect of the present disclosure, a radio wave environment estimation program recorded on a computer-readable recording medium enables a computer to realize a receiving function that receives measured radio wave information, which is information regarding the actual measured value of a radio wave index, which is an index regarding the radio wave environment, which is the environment of radio waves related to control radio waves for controlling an unmanned aerial vehicle, measured at a measurement point; an estimation function that uses an estimation model to estimate a three-dimensional distribution, which is the distribution of the radio wave environment in a three-dimensional space that includes the area in which the unmanned aerial vehicle is flown and the measurement point; and an output function that outputs estimated radio wave information, which is information regarding the three-dimensional distribution, and the estimation model estimates the three-dimensional distribution based on the measured radio wave information.

[0013] According to the present disclosure, it becomes possible to fly unmanned aerial vehicles more safely.

[0014] 1 is a diagram illustrating an example of a configuration of a radio wave environment estimation device of the present disclosure. FIG. 2 is a diagram illustrating an example of an operation flow of a radio wave environment estimation device of the present disclosure. FIG. 3 is a diagram illustrating an example of a configuration of a system including a radio wave environment estimation device of the present disclosure. FIG. 4 is a diagram illustrating an example of a configuration of a radio wave environment estimation device of the present disclosure. FIG. 5 is a diagram illustrating an example of a display image. FIG. 6 is a diagram illustrating an example of a configuration of a system including a radio wave environment estimation device of the present disclosure. FIG. 7 is a diagram illustrating an example of a configuration of a radio wave environment estimation device of the present disclosure. FIG. 8 is a diagram illustrating an example of an operation flow of a radio wave environment estimation device of the present disclosure. FIG. 9 is a diagram illustrating an example of a hardware configuration of each embodiment of the present disclosure.

[0015] [First embodiment] A first embodiment of the present disclosure will be described. Note that specific examples of the radio wave environment estimation device 10 in the first embodiment are a radio wave environment estimation device 20 in a second embodiment, a radio wave environment estimation device 30 in a third embodiment, and a radio wave environment estimation device 40 in a fourth embodiment, which will be described later.

[0016] First, an example of the configuration of a radio wave environment estimation device 10 will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the configuration of a radio wave environment estimation device 10. The radio wave environment estimation device 10 includes a receiving unit 11, an estimation unit 12, and an output unit 13.

[0017] The receiving unit 11 receives measured radio wave information. The measured radio wave information is information relating to the measured value of a radio wave index. The radio wave index is an index relating to the radio wave environment. The measured value of the radio wave index is measured at a measurement point. The measurement point is a point where the measured value of the radio wave index is measured. The radio wave environment is a radio wave environment relating to control radio waves for controlling the unmanned aerial vehicle.

[0018] The estimation unit 12 estimates the three-dimensional distribution using an estimation model. The three-dimensional distribution is the distribution of the radio wave environment in three-dimensional space. The three-dimensional space includes the area in which the unmanned aerial vehicle is flown and the measurement points. The estimation model estimates the three-dimensional distribution based on actually measured radio wave information.

[0019] The output unit 13 outputs the estimated radio wave information. The estimated radio wave information is information relating to a three-dimensional distribution.

[0020] Next, a description will be given of an example of the operation flow of the radio wave environment estimation device 10. An example of the operation flow of the radio wave environment estimation device 10 is shown in FIG.

[0021] The receiving unit 11 receives the measured radio wave information (step S101).

[0022] The estimation unit 12 estimates the three-dimensional distribution using an estimation model (step S102). The estimation model estimates the three-dimensional distribution based on the actually measured radio wave information.

[0023] The output unit 13 outputs the estimated radio wave information (step S103). The estimated radio wave information is information relating to a three-dimensional distribution.

[0024] As described above, in the first embodiment of the present disclosure, the radio wave environment estimation device 10 includes a receiving unit 11, an estimating unit 12, and an output unit 13. The receiving unit 11 receives measured radio wave information. The measured radio wave information is information related to the measured value of the radio wave index. The radio wave index is an index related to the radio wave environment. The measured value of the radio wave index is measured at a measurement point. The measurement point is a point where the measured value of the radio wave index is measured. The radio wave environment is a radio wave environment related to control radio waves for controlling the unmanned aerial vehicle. The estimating unit 12 estimates the three-dimensional distribution using an estimation model. The three-dimensional distribution is the distribution of the radio wave environment in three-dimensional space. The three-dimensional space is a space including the area in which the unmanned aerial vehicle is flown and the measurement point. The estimation model estimates the three-dimensional distribution based on the measured radio wave information. The output unit 13 outputs estimated radio wave information. The estimated radio wave information is information related to the three-dimensional distribution.

[0025] This allows the radio wave environment estimation device 10 to estimate the distribution of the radio wave environment in a space including the area in which the unmanned aerial vehicle will be flown before the unmanned aerial vehicle is flown, thereby enabling the unmanned aerial vehicle to be flown more safely.

[0026] Second Embodiment Next, a radio wave environment estimation device 20 according to a second embodiment of the present disclosure will be described. Note that the radio wave environment estimation device 20 according to the second embodiment is a specific example of the radio wave environment estimation device 10 according to the first embodiment.

[0027] First, FIG. 3 shows an example of the configuration of a system including a radio wave environment estimation device 20.

[0028] The radio wave environment estimation device 20 is connected to the display means 50. The radio wave environment estimation device 20 can output estimated radio wave information to the display means 50. The estimated radio wave information will be described later. Note that the output destination of the estimated radio wave information does not have to be the display means 50.

[0029] 4 shows an example of the configuration of the radio wave environment estimation device 20. The radio wave environment estimation device 20 includes a receiving unit 21, an estimating unit 22, and an output unit 23.

[0030] The receiver 21 receives measured radio wave information. The measured radio wave information is information related to the measured value of a radio wave index. The radio wave index is an index related to the radio wave environment. The measured value of the radio wave index is measured at a measurement point. The measurement point is the location where the measured value of the radio wave index is measured. The radio wave environment is the environment of radio waves related to control radio waves for controlling the unmanned aerial vehicle. The control radio waves may be, for example, radio waves provided by a mobile communication service or radio waves usable in a narrow area such as an airport, but the radio waves used for the control radio waves are not limited to these. The control radio waves may be, for example, radio waves for controlling the movement of the unmanned aerial vehicle. The control radio waves may also be radio waves related to position information used to control the unmanned aerial vehicle, for example, radio waves related to a GNSS (Global Navigation Satellite System) function.

[0031] For example, if the unmanned aerial vehicle flies within an airport, the measurement point may be a point within the airport. The measurement point may also include, for example, a point on the ground. The measurement point may also include a point other than the ground, such as a rooftop of a building. The measurement point may also include a location where radio waves that affect the radio wave environment in the area where the unmanned aerial vehicle flies can be received.

[0032] The measured radio wave information may include, for example, information on radio wave indicators measured by a person who visited the measurement point, or information on radio wave indicators measured by a radio wave sensor or measuring device installed at the measurement point.

[0033] The measured radio wave information may include, for example, information on received signal strength (RSSI (Received Signal Strength Indicator)). The measured radio wave information may also include information on communication quality such as a signal-to-noise ratio (SNR). The measured radio wave information may also include information on the direction of arrival of the radio waves. Note that the direction of arrival of the radio waves can be measured by methods such as physically changing the orientation of a directional antenna, using an array antenna, or using multiple antennas with different directivities.

[0034] The measured radio wave information also includes measured values ​​of radio wave indices for control radio waves for controlling the unmanned aerial vehicle. The measured radio wave information may also include measured values ​​of radio wave indices for radio waves emitted by noise sources. Radio waves emitted by noise sources are radio waves (noise) that may deteriorate the radio wave environment for control radio waves. For example, radio waves from a wireless local area network (LAN) may become noise for control radio waves.

[0035] The measured radio wave information may also include information about environmental noise. The environmental noise is also called a noise floor. The environmental noise may be measured for each of two or more frequencies that may be used as control radio waves. Note that the environmental noise may also include noise emitted by the measuring instrument that measures the environmental noise, and therefore the information about the environmental noise may include information about the noise emitted by the measuring instrument itself, as well as the measured value of the environmental noise. The information about the environmental noise may be used to determine whether the unmanned aerial vehicle is capable of receiving control radio waves (reception feasibility).

[0036] The estimation unit 22 estimates a three-dimensional distribution based on the measured radio wave information. The three-dimensional distribution is the distribution of the radio wave environment in a three-dimensional space. The three-dimensional space is a space that includes the measurement point and the area in which the unmanned aerial vehicle is flown. For example, the three-dimensional space is a space that includes the ground and the sky above an airport. The three-dimensional space is not limited to a space related to an airport.

[0037] The three-dimensional distribution may include, for example, a distribution of estimated values ​​of radio wave indicators for control radio waves. The three-dimensional distribution may include, for example, a distribution of signal-to-noise ratios for control radio waves. The three-dimensional distribution may also include a distribution of whether or not control radio waves can be received. The three-dimensional distribution may also include, for example, a distribution of noise in the control radio waves of an unmanned aerial vehicle.

[0038] The estimation unit 22 uses an estimation model to estimate the three-dimensional distribution. The estimation model estimates the three-dimensional distribution based on actually measured radio wave information.

[0039] The estimation model is generated, for example, by a learning device (not shown). The estimation unit 22 may generate the estimation model. Input information to the estimation model includes measured radio wave information. The input information may include information on the date and time when the measured value of the radio wave index included in the measured radio wave information was measured. The input information may also include specified date and time information, which is information on when the three-dimensional distribution is desired to be estimated.

[0040] Furthermore, the output information from the estimation model includes information about the three-dimensional distribution, which may be information according to the specified date and time information.

[0041] The estimation model learns using propagation estimation results as training data. The propagation estimation results are information about the results of radio wave propagation estimation (simulation) performed based on actually measured radio wave information for learning. In radio wave propagation estimation, the distribution of the radio wave environment in three-dimensional space is estimated. The radio wave propagation estimation is performed based on actually measured radio wave information for learning.

[0042] The measured radio wave information for learning is also learned as training data. The data to be learned may include information on the date and time when the measured values ​​of the radio wave indices included in the measured radio wave information were measured.

[0043] The estimation model may also learn information about the shape of the three-dimensional space, such as information about the terrain and buildings, and information about areas where unmanned aerial vehicles cannot fly. Information about the terrain and buildings may affect the distribution of the radio wave environment.

[0044] For example, the learning device estimates the location of a radio wave source based on measured radio wave information for learning.The learning device then estimates the distribution of the radio wave environment in three-dimensional space by radio wave propagation estimation based on the location of the radio wave source and the measured radio wave information for learning.The learning device then generates an estimation model using the propagation estimation results as training data.

[0045] The learning device may estimate the location of the source of the control radio waves as the location of the source of the radio waves. Also, the learning device may estimate the location of the noise source as the location of the source of the radio waves. Also, the learning device may estimate the location of the source of the control radio waves and the location of the noise source as the location of the source of the radio waves. Note that information on the location of the source of the control radio waves may be provided to the learning device in advance. For example, when radio waves provided by a mobile communication service are used as control radio waves, the location of the source of the control radio waves may be the location of a base station of the mobile communication service.

[0046] The learning device estimates the distribution of the radio wave environment in three-dimensional space by radio wave propagation estimation based on the position of the control radio wave source and the measured radio wave information for learning. Alternatively, the learning device may estimate the distribution of the radio wave environment in three-dimensional space by radio wave propagation estimation based on the position of the control radio wave source, the position of the noise source, and the measured radio wave information for learning. In this case, the distribution of the radio wave environment may be the distribution of the radio wave environment for the control radio waves.

[0047] Alternatively, the learning device may estimate the distribution of the radio wave environment in three-dimensional space by radio wave propagation estimation based on the position of the noise source and the measured radio wave information for learning. In this case, the distribution of the radio wave environment may be the distribution of the radio wave environment for noise.

[0048] The learning data used by the estimation model may include information about environmental noise. In this case, the information about environmental noise may be reflected in the estimation of the three-dimensional distribution including the distribution of whether or not control radio waves can be received.

[0049] For example, the training data may include information on environmental noise measured at various dates and times. The estimation model may then estimate environmental noise at a date and time specified by the specified date and time information and use the estimated environmental noise to estimate whether or not a control radio wave can be received. For example, the estimation model may reflect information on the environmental noise in an estimate of the S / N ratio of the control radio wave and estimate whether or not a control radio wave can be received based on the estimated S / N ratio.

[0050] Furthermore, for example, the learning data may include environmental information, which is information about the environment, and information about environmental noise corresponding to the environmental information. The environmental information includes information about objects or events that may generate environmental noise. Furthermore, the input information to the estimation model may include the environmental information. Then, the estimation model may estimate environmental noise according to the input environmental information, and use the estimated environmental noise to estimate whether or not control radio waves can be received.

[0051] The environmental information may include, for example, information regarding the degree of vehicle congestion within the three-dimensional space. The environmental information may also include, for example, information regarding the degree of vehicle congestion around the three-dimensional space. The information regarding the degree of vehicle congestion may include image information of roads captured within or around the three-dimensional space. The environmental information may also include, for example, information regarding the running of electric vehicles (EVs) within or around the three-dimensional space. Noise emitted by EVs may act as environmental noise and affect whether or not control radio waves can be received.

[0052] Furthermore, for example, the environmental information may include information about the density of other unmanned aerial vehicles flying in or around the three-dimensional space. When other unmanned aerial vehicles are densely packed, noise emitted by the densely packed unmanned aerial vehicles may act as environmental noise and affect whether or not the control radio waves can be received.

[0053] In this way, the estimation unit 22 can estimate the three-dimensional distribution in three-dimensional space based on the actual measured values ​​of the radio wave index at the measurement point. Therefore, the three-dimensional distribution can be estimated before flying the unmanned aerial vehicle. For example, the estimation unit 22 can estimate the distribution of the radio wave environment in the sky based on the actual measured values ​​of the radio wave index at the observation point on the ground.

[0054] The learning device may update the estimation model by adding, as training data, information about the actual measured values ​​of the radio wave indices measured by the unmanned aerial vehicle when the unmanned aerial vehicle is flown. The information about the actual measured values ​​of the radio wave indices measured by flying the unmanned aerial vehicle includes information about the location where the actual measured values ​​were measured. In this case, for example, the receiving unit 21 may receive information about the actual measured values ​​of the radio wave indices measured by flying the unmanned aerial vehicle. Then, the estimation unit 22 may input information about the actual measured values ​​of the radio wave indices measured by flying the unmanned aerial vehicle to the learning device. This can improve the accuracy of the three-dimensional distribution estimated by the estimation model.

[0055] The output unit 23 outputs the estimated radio wave information. The estimated radio wave information is information relating to three-dimensional distribution. The output unit 23 outputs the estimated radio wave information to, for example, the display means 50. An image displayed on the display means 50 by the output unit 23 outputting the estimated radio wave information to the display means 50 may hereinafter be referred to as a display image.

[0056] The display image may, for example, show information about three-dimensional distribution on a three-dimensional display showing three-dimensional space. Alternatively, the display image may show information about three-dimensional distribution on a two-dimensional display showing a plane formed by two of the three axes of the three-dimensional space. For example, the display image may show the distribution of the radio wave environment at a specified altitude on a two-dimensional display.

[0057] The estimated radio wave information may include information indicating an area in which the unmanned aerial vehicle can receive control radio waves. The display image may include, for example, an image indicating an area in which the unmanned aerial vehicle can receive control radio waves. Note that the area in which the unmanned aerial vehicle can receive control radio waves may hereinafter be referred to as the receivable area.

[0058] An example of a display image is shown in Figure 5. For example, the display image may show a receivable area at an altitude selected by a user. The display image may show a receivable area on a two-dimensional map. The display showing the receivable area may show whether reception is possible in each of rectangular areas divided into a mesh pattern. The receivable area may also be shown in any shape other than a rectangle. For example, the receivable area may be shown by a curved line. The display image may also include a display showing areas where unmanned aerial vehicles cannot pass, such as the location of buildings.

[0059] The display image may also include a check box that allows the user to select the display altitude. The display altitude may be selected by a method other than the check box. The display altitude selected by the user may be one, or two or more. The display altitude that the user can select may be a discrete value or a continuous value. For example, the display altitude may be dynamically changed by a user operation on a bar display indicating the altitude.

[0060] The display image may show receivable areas at two or more altitudes. In this case, the receivable areas at each altitude may be displayed in a different display format, for example, in a different color. Furthermore, if the unmanned aerial vehicle uses a backup frequency that is different from the normal frequency when it is unable to receive control radio waves, the display image may include an image showing the receivable area for control radio waves of the backup frequency in addition to the receivable area for control radio waves of the normal frequency.

[0061] The estimated radio wave information may also include information indicating an area where it is possible that the control radio wave cannot be received. The display image may include, for example, an image indicating an area where it is possible that the control radio wave cannot be received.

[0062] The display image may also include an image showing the current position of the unmanned aerial vehicle. In this case, the receiving unit 21 may receive information about the current position of the unmanned aerial vehicle, and the output unit 23 may cause the display means 50 to display a display image including information about the current position of the unmanned aerial vehicle. In this case, information about the current position of the unmanned aerial vehicle may be input to the radio wave environment estimation device 20 from a control device (not shown) external to the radio wave environment estimation device 20. Note that the measurement of the current position of the unmanned aerial vehicle may be performed using a GNSS (Global Navigation Satellite System) function installed in the unmanned aerial vehicle, or may be performed by monitoring the unmanned aerial vehicle with a monitoring device (not shown). The monitoring device may measure the current position of the unmanned aerial vehicle using, for example, images captured by a camera.

[0063] The coverage area may be estimated by an estimation model as a three-dimensional distribution. Alternatively, the coverage area may be estimated by the estimation unit 22 based on the distribution of radio wave indices estimated by the estimation model as a three-dimensional distribution.

[0064] By checking the display image as described above, the operator of the unmanned aerial vehicle can control the unmanned aerial vehicle so that it passes through an area where it can receive control radio waves. Alternatively, while looking at the display image as described above, the operator of the unmanned aerial vehicle can control the unmanned aerial vehicle so that it avoids areas where it cannot receive control radio waves.

[0065] Furthermore, the radio wave environment estimation device 20 can estimate the three-dimensional distribution before flying the unmanned aerial vehicle, allowing the unmanned aerial vehicle to fly more safely.

[0066] Next, an example of the operation flow of the radio wave environment estimation device 20 of this embodiment will be described with reference to FIG.

[0067] The receiving unit 21 receives the measured radio wave information (step S101).

[0068] The estimation unit 22 estimates the three-dimensional distribution using an estimation model (step S102). The estimation model estimates the three-dimensional distribution based on the actually measured radio wave information.

[0069] The output unit 23 outputs the estimated radio wave information (step S103). The estimated radio wave information is information relating to a three-dimensional distribution.

[0070] As described above, in the second embodiment of the present disclosure, the radio wave environment estimation device 20 includes a receiving unit 21, an estimating unit 22, and an output unit 23. The receiving unit 21 receives measured radio wave information. The measured radio wave information is information related to the measured value of the radio wave index. The radio wave index is an index related to the radio wave environment. The measured value of the radio wave index is measured at a measurement point. The measurement point is a point where the measured value of the radio wave index is measured. The radio wave environment is a radio wave environment related to control radio waves for controlling the unmanned aerial vehicle. The estimating unit 22 estimates the three-dimensional distribution using an estimation model. The three-dimensional distribution is the distribution of the radio wave environment in three-dimensional space. The three-dimensional space is a space including the area in which the unmanned aerial vehicle is flown and the measurement point. The estimation model estimates the three-dimensional distribution based on the measured radio wave information. The output unit 23 outputs estimated radio wave information. The estimated radio wave information is information related to the three-dimensional distribution.

[0071] This allows the radio wave environment estimation device 20 to estimate the distribution of the radio wave environment in a space including the area in which the unmanned aerial vehicle will be flown before the unmanned aerial vehicle is flown, thereby enabling the unmanned aerial vehicle to be flown more safely.

[0072] Third Embodiment Next, a radio wave environment estimation device 30 according to a third embodiment of the present disclosure will be described. Note that the radio wave environment estimation device 30 according to the third embodiment is a specific example of the radio wave environment estimation device 10 according to the first embodiment.

[0073] 6 shows an example of the configuration of a system including a radio wave environment estimation device 30. The radio wave environment estimation device 30 is connected to a display means 50.

[0074] 7 shows an example configuration of the radio wave environment estimation device 30. The radio wave environment estimation device 30 includes a receiving unit 21, an estimating unit 22, an output unit 23, and a generating unit 34. Note that the function of the generating unit 34 may be included in a device external to the radio wave environment estimation device, for example, a flight path generating device (not shown).

[0075] The receiving unit 21 and the estimating unit 22 are the same as those in the second embodiment, and therefore their explanation will be omitted.

[0076] In this embodiment, the output unit 23 outputs the estimated radio wave information to the generation unit 34. The output unit 23 may also output the estimated radio wave information to the display means 50. Furthermore, the information that the output unit 23 outputs to the generation unit 34 as the estimated radio wave information and the information that the output unit 23 outputs to the display means 50 as the estimated radio wave information may be different information.

[0077] The generation unit 34 generates flight path information regarding the flight path of the unmanned aerial vehicle based on the estimated radio wave information. Then, the generation unit 34 outputs information related to the generated flight path information to the display means 50. Note that the generation unit 34 may output the flight path information to the output unit 23, and the output unit 23 may output information related to the flight path information to the display means 50.

[0078] The generation unit 34 generates flight path information based on, for example, the three-dimensional distribution estimated by the estimation unit 22, the flight-prohibited position information, and the passing point information. The flight-prohibited position information is information about locations where the unmanned aerial vehicle cannot fly. The passing point information is information about locations where the unmanned aerial vehicle will fly.

[0079] The no-fly location information is, for example, information about the location of a building. The no-fly location information may also include information about locations where other unmanned aerial vehicles will pass and information about the date and time when the other unmanned aerial vehicles will pass those locations. The no-fly location information may also include information about locations where aircraft using the airport will pass and information about the date and time when the aircraft will pass those locations. The no-fly location information may be stored in a storage means (not shown) inside or outside the radio wave environment estimation device 30, or may be received by the receiving unit 21.

[0080] The waypoint information is information about a location where the unmanned aerial vehicle is scheduled to pass, for example, for an airport facility inspection. The waypoint information may include, for example, information about the location where the unmanned aerial vehicle will perform the inspection and information about the time when the unmanned aerial vehicle will perform the inspection at that location. The waypoint information is received, for example, by the receiving unit 21.

[0081] In generating the flight route information, the generation unit 34 generates the flight route information based on the waypoint information so that the flight route passes through the positions indicated by the waypoint information. Furthermore, in generating the flight route information, the generation unit 34 generates the flight route information based on the no-fly position information so that the flight route does not pass through the positions indicated by the no-fly position information. Furthermore, in generating the flight route information, the generation unit 34 generates the flight route information based on the three-dimensional distribution so that the flight route passes through positions where control radio waves can be received. The generation unit 34 then outputs the flight route information.

[0082] More specifically, the generation unit 34 may generate flight path information so as to maximize an evaluation score. The evaluation score indicates the degree of appropriateness of the flight path information. The evaluation score is calculated based on an evaluation function. The generation unit 34 generates a flight path for the unmanned aerial vehicle based on the waypoint information so as to pass through the positions indicated by the waypoint information.

[0083] The parameters of the evaluation function include a radio wave environment score. The radio wave environment score is a score related to the radio wave environment. For example, the shorter the length of a flight route that passes through an area where it is estimated that control radio waves cannot be received, the lower the radio wave environment score may be.

[0084] The parameters of the evaluation function may include, for example, a path length score. The path length score is a score related to the length of the flight path. For example, the path length score may be lower as the flight path is longer.

[0085] Furthermore, the parameters of the evaluation function may include, for example, a required time score. The required time score is a score related to the required time. The required time is the time it takes for the unmanned aerial vehicle to fly along the flight path. For example, the required time score may be lower as the required time is longer.

[0086] The parameters of the evaluation function may also include a ground risk score. The ground risk score is a score related to ground risk. The ground risk is the risk that the flight of an unmanned aerial vehicle may pose to the ground. For example, areas above important cultural properties, railways, densely inhabited districts (DIDs), and other areas on the ground would have a significant impact if the unmanned aerial vehicle were to fall for some reason, so it is desirable that these areas not be included in the flight path of the unmanned aerial vehicle. Areas on the ground that are desirable not to be included in the flight path may hereinafter be referred to as areas recommended to be avoided.

[0087] The areas recommended to be avoided may include predetermined areas on the ground, such as locations of important cultural properties, locations on roads with heavy traffic, densely populated areas, and locations where railways pass. The areas recommended to be avoided may also be changed according to ground conditions. For example, a location that is usually vacant but attracts many people on event days may be included in the areas recommended to be avoided on event days. The ground conditions may include, for example, information regarding traffic volume, information regarding the event area and the event date and time, etc. Information regarding the ground conditions is input from an information providing device (not shown) or the like.

[0088] For example, the shorter the length of the flight path that passes through the recommended avoidance area, the lower the ground risk score may be. Also, for example, the greater the distance between the flight path and the recommended avoidance area, the lower the ground risk score may be.

[0089] The parameters of the evaluation function may also include an air risk score. The air risk score is a score related to air risk. The air risk is the risk that the unmanned aerial vehicle will be unable to fly. Information used to calculate the air risk score may include information on the routes of other unmanned aerial vehicles, information on the locations of buildings, information on windy locations, weather information, etc. The information used to calculate the air risk is input from an information providing device (not shown), etc.

[0090] If an unmanned aerial vehicle collides with some object, it may become unable to fly. Therefore, for example, when the distance between the unmanned aerial vehicle and another unmanned aerial vehicle is closer than a predetermined distance, the air risk score may be lower than when the distance between the unmanned aerial vehicle and another unmanned aerial vehicle is equal to or greater than the predetermined distance. Also, when the distance between the unmanned aerial vehicle and a building is closer than a predetermined distance, the air risk score may be lower than when the distance between the unmanned aerial vehicle and the building is equal to or greater than the predetermined distance.

[0091] Furthermore, if an unmanned aerial vehicle flies in a windy location or on a windy day, it may be unable to fly due to the effects of the wind. Therefore, for example, if the flight path includes a location where winds may blow at speeds exceeding the wind speed at which the unmanned aerial vehicle can fly (for example, a canyon between buildings), the air risk score may be lowered. Whether or not information about the wind is reflected in the air risk score may be changed depending on whether or not the unmanned aerial vehicle is wind-resistant. Furthermore, information about whether or not the unmanned aerial vehicle is wind-resistant may be input to the receiving unit 21.

[0092] Furthermore, some unmanned aerial vehicles cannot fly in the rain. Therefore, if the flight path includes an area where rain is predicted to fall on the date and time the unmanned aerial vehicle is scheduled to fly based on weather information, the air risk score may be lowered. Furthermore, whether or not information about rain is reflected in the air risk score may be changed depending on whether or not the unmanned aerial vehicle is waterproof. Furthermore, information about whether or not the unmanned aerial vehicle is waterproof may be input to the receiving unit 21.

[0093] When the parameters of the evaluation function include two or more of the above scores, the evaluation score may be, for example, a weighted average of the scores included in the parameters. Furthermore, the weighting coefficient for each parameter may be changeable. For example, when the parameters of the evaluation function include a required time score and a ground risk score, an instruction as to whether to prioritize time or safety may be input to the generation unit 34. The instruction as to whether to prioritize time or safety may be input to the generation unit 34 in response to a user operation. Then, when an instruction to prioritize time is received, the generation unit 34 may increase the weighting coefficient for the required time score, and when an instruction to prioritize safety is received, the generation unit 34 may increase the weighting coefficient for the ground risk score.

[0094] Furthermore, the generation unit 34 outputs information relating to the generated flight path information to, for example, the display means 50. The image displayed on the display means 50 as a result of the generation unit 34 outputting information relating to the flight path information to the display means 50 may hereinafter be referred to as a path image.

[0095] The route image may, for example, display information related to flight path information on a three-dimensional display showing a three-dimensional space. Alternatively, the route image may display information related to flight path information on a two-dimensional display showing a plane formed by two of the three axes in the three-dimensional space. For example, the route image may display the flight path on a two-dimensional map and indicate the flight altitude along the flight path using numbers, colors, or the like. Alternatively, for example, the route image may include an image showing the flight path on a two-dimensional map and an image showing the flight altitude along the flight path.

[0096] The route image may also include information about three-dimensional distribution. For example, the route image may include an indication of areas where control radio waves can be received or areas where control radio waves cannot be received, for altitudes included in the flight altitude of the flight route. For example, when the flight altitude is 10 m to 30 m, the route image may include information about three-dimensional distribution at altitudes 10 m to 30 m.

[0097] The route image may also include a display showing the current location of the unmanned aerial vehicle.

[0098] An example of a route image is shown in Figure 8. In the example shown in Figure 8, a flight route is shown on a two-dimensional map. The route image also includes a display showing the flight altitude along the flight route. In Figure 8, the area surrounded by curved lines indicates an area where control radio waves cannot be received. The route image also includes a display showing the current position of the unmanned aerial vehicle.

[0099] The route image may be output by the output unit 23. In this case, the display related to the three-dimensional distribution and the display related to the flight route information may be superimposed by the output unit 23. The output unit 23 may output the display image including information related to the flight route information.

[0100] Next, an example of the operation flow of the radio wave environment estimation device 30 of this embodiment will be described with reference to FIG.

[0101] The receiving unit 21 receives the measured radio wave information (step S301).

[0102] The estimation unit 22 estimates the three-dimensional distribution using an estimation model (step S302). The estimation model estimates the three-dimensional distribution based on the actually measured radio wave information.

[0103] The generation unit 34 generates flight path information regarding the flight path of the unmanned aerial vehicle based on the estimated radio wave information, which is information regarding three-dimensional distribution (step S303).

[0104] Then, the generation unit 34 outputs information related to the flight path information (step S304).

[0105] As described above, in the third embodiment of the present disclosure, the radio wave environment estimation device 30 includes a receiving unit 21, an estimating unit 22, and an output unit 23. The receiving unit 21 receives measured radio wave information. The measured radio wave information is information related to the measured value of the radio wave index. The radio wave index is an index related to the radio wave environment. The measured value of the radio wave index is measured at a measurement point. The measurement point is a point where the measured value of the radio wave index is measured. The radio wave environment is a radio wave environment related to control radio waves for controlling the unmanned aerial vehicle. The estimating unit 22 estimates the three-dimensional distribution using an estimation model. The three-dimensional distribution is the distribution of the radio wave environment in three-dimensional space. The three-dimensional space is a space including the area in which the unmanned aerial vehicle is flown and the measurement point. The estimation model estimates the three-dimensional distribution based on the measured radio wave information. The output unit 23 outputs estimated radio wave information. The estimated radio wave information is information related to the three-dimensional distribution.

[0106] This allows the radio wave environment estimation device 30 to estimate the distribution of the radio wave environment in a space including the area in which the unmanned aerial vehicle will be flown before the unmanned aerial vehicle is flown, thereby enabling the unmanned aerial vehicle to be flown more safely.

[0107] The radio wave environment estimation device 30 also includes a generation unit 34. The generation unit 34 generates and outputs flight path information regarding the flight path of the unmanned aerial vehicle based on the estimated radio wave information. This allows the operator of the unmanned aerial vehicle to more easily fly the unmanned aerial vehicle so that it passes through an area where it can receive control radio waves by operating the unmanned aerial vehicle in accordance with the flight path information. It also allows a control device (not shown) that controls the unmanned aerial vehicle to control the unmanned aerial vehicle in accordance with the flight path information. Furthermore, by providing the unmanned aerial vehicle with flight path information, it is possible to automatically fly the unmanned aerial vehicle in accordance with the flight path information.

[0108] [Fourth embodiment] Next, a radio wave environment estimation device 40 according to a fourth embodiment of the present disclosure will be described. Note that the radio wave environment estimation device 40 according to the fourth embodiment is a specific example of the radio wave environment estimation device 10 according to the first embodiment.

[0109] 10 shows an example of the configuration of a system including a radio wave environment estimation device 40. The radio wave environment estimation device 40 is connected to a display means 50.

[0110] 11 shows an example of the configuration of the radio wave environment estimation device 40. The radio wave environment estimation device 40 includes a receiving unit 21, an estimating unit 22, an output unit 23, a generating unit 34, and a control unit 45. Note that the function of the control unit 45 may be included in a device external to the radio wave environment estimation device, such as a control device (not shown).

[0111] The receiving unit 21 and the estimating unit 22 are the same as those in the second embodiment, and therefore their explanation will be omitted.

[0112] In this embodiment, the output unit 23 outputs the estimated radio wave information to the generation unit 34. The output unit 23 may also output the estimated radio wave information to the display means 50. Furthermore, the information that the output unit 23 outputs to the generation unit 34 as the estimated radio wave information and the information that the output unit 23 outputs to the display means 50 as the estimated radio wave information may be different information.

[0113] Furthermore, the generation unit 34 outputs information related to the flight path information to the control unit 45. The generation unit 34 may also output information related to the flight path information to the display means 50. The generation unit 34 may also output information related to the flight path information to the output unit 23. Furthermore, the information that the generation unit 34 outputs to the control unit 45 as information related to the flight path information and the information that the generation unit 34 outputs to the display means 50 as information related to the flight path information may be different from each other.

[0114] The control unit 45 controls the flight of the unmanned aerial vehicle.

[0115] For example, the control unit 45 may perform control related to mode switching of the unmanned aerial vehicle.

[0116] The unmanned aerial vehicle operates in two modes, for example, a manual flight mode and an automatic flight mode. The manual flight mode is a mode in which the unmanned aerial vehicle flies in accordance with control radio waves. The control radio waves may be, for example, radio waves for flying the unmanned aerial vehicle in accordance with the operation of the pilot. The control radio waves may also be radio waves for flying the unmanned aerial vehicle in accordance with the flight path generated by the generation unit 34. The control radio waves may be output from an antenna (not shown) that outputs control radio waves in accordance with the control of the control unit 45.

[0117] The automatic flight mode is a mode in which the unmanned aerial vehicle flies automatically. In the automatic flight mode, the unmanned aerial vehicle flies according to predetermined rules. For example, information regarding a flight path generated by the generation unit 34 may be set in advance in the unmanned aerial vehicle, and the unmanned aerial vehicle may fly according to this flight path. In the automatic flight mode, the unmanned aerial vehicle may receive GNSS radio waves to perform automatic flight, or if it is unable to receive GNSS radio waves, it may perform automatic flight using an IMU (Inertial Measurement Unit) sensor or the like.

[0118] For example, based on communication quality information, the control unit 45 may recommend to the pilot of the unmanned aerial vehicle that the communication mode be switched to automatic flight mode if the communication quality is worse than a predetermined quality. Communication quality is the quality of communication performed by the unmanned aerial vehicle. Communication quality information is information relating to communication quality. Communication quality may be the quality of communication via control radio waves transmitted to the unmanned aerial vehicle. Communication quality may also be the quality of communication via radio waves transmitted from the unmanned aerial vehicle. Radio waves transmitted from the unmanned aerial vehicle may hereinafter be referred to as transmitted radio waves. The unmanned aerial vehicle can transmit its own location information and transmission data via transmitted radio waves. The transmitted data may include, for example, data acquired by the unmanned aerial vehicle and information regarding the health status of the unmanned aerial vehicle.

[0119] The quality of communication via control radio waves may be measured in the unmanned aerial vehicle. Then, communication quality information may be transmitted from the unmanned aerial vehicle to the radio wave environment estimation device 40 via transmitted radio waves. The quality of communication via transmitted radio waves may be measured by a base station (not shown) that receives the transmitted radio waves. Then, the communication quality information may be transmitted from the base station to the control unit 45.

[0120] The control unit 45 may, for example, recommend to the operator of the unmanned aerial vehicle that they switch to automatic flight mode by displaying on the display means 50 an image including a display indicating that they recommend switching to automatic flight mode.

[0121] Furthermore, for example, the control unit 45 may transmit a signal to the unmanned aerial vehicle to switch to automatic flight mode when the communication quality is worse than a predetermined quality based on the communication quality information. The signal to switch to automatic flight mode may be included in the control radio wave. Furthermore, for example, if a device (not shown) external to the radio wave environment estimation device 40 controls the mode switching of the unmanned aerial vehicle, the control unit 45 may transmit a signal to the external device indicating that switching to automatic flight mode is recommended. The unmanned aerial vehicle may then receive a signal to switch to automatic flight mode from the external device.

[0122] Furthermore, switching to the automatic flight mode according to the communication quality may be performed autonomously by the unmanned aerial vehicle. The unmanned aerial vehicle may transition to the automatic flight mode when the quality of communication via control radio waves is worse than a predetermined quality. Furthermore, when the quality of communication via control radio waves is worse than a predetermined quality, the unmanned aerial vehicle may be unable to receive the control radio waves. Therefore, when the unmanned aerial vehicle is unable to receive the control radio waves, the unmanned aerial vehicle may attempt to receive the control radio waves using a backup frequency that is different from the normal frequency. Then, when the unmanned aerial vehicle is unable to receive the control radio waves even on the backup frequency, the unmanned aerial vehicle may transition to the automatic flight mode.

[0123] The transition from automatic flight mode to manual flight mode may occur, for example, a predetermined time after switching from manual flight mode to automatic flight mode. For example, the unmanned aerial vehicle may check whether control radio waves can be received at predetermined intervals after switching to automatic flight mode, and if reception is possible, transition to manual flight mode. Also, for example, the control unit 45 may check communication quality at predetermined intervals after switching to automatic flight mode, and transition the unmanned aerial vehicle to manual flight mode if the communication quality improves beyond a predetermined quality.

[0124] Furthermore, for example, the control unit 45 may switch the mode of the unmanned aerial vehicle based on flight path information. For example, if a point where control radio waves are expected to be unable to be received is included in the flight path, the generation unit 34 may plan to operate the unmanned aerial vehicle in automatic flight mode at the point where control radio waves are expected to be unable to be received. The generation unit 34 may then generate flight path information including information about the point where the unmanned aerial vehicle will operate in automatic flight mode. The control unit 45 may then transmit a signal to the unmanned aerial vehicle to switch to automatic flight mode when the unmanned aerial vehicle reaches a point where it is planned to operate in automatic flight mode based on the flight path information. The control unit 45 may also transmit a signal to the unmanned aerial vehicle to switch to manual flight mode when the unmanned aerial vehicle reaches a point where it is planned to switch to manual flight mode based on the flight path information.

[0125] For example, the unmanned aerial vehicle may switch modes of the unmanned aerial vehicle based on flight path information. The unmanned aerial vehicle may transition to automatic flight mode when it reaches a point where it is planned to operate in automatic flight mode based on flight path information. The unmanned aerial vehicle may transition to manual flight mode when it reaches a point where it is planned to switch to manual flight mode based on flight path information.

[0126] The control unit 45 may also control the display of the current position of the unmanned aerial vehicle. For example, the control unit 45 may receive information about the current position of the unmanned aerial vehicle from an information providing device (not shown) and cause the display means 50 to display an image including a display showing the current position of the unmanned aerial vehicle.

[0127] The control unit 45 may also cause the display means 50 to display an image that allows a comparison of the flight path of the unmanned aerial vehicle and the current position of the unmanned aerial vehicle based on the flight path information generated by the generation unit 34. Furthermore, for example, the control unit 45 may calculate the distance between the flight path and the current position of the unmanned aerial vehicle, and, if the calculated distance is equal to or greater than a predetermined value, cause the display means 50 to display an image that includes a display indicating that the position of the unmanned aerial vehicle is deviating from the planned flight path.

[0128] The control unit 45 may also receive information regarding the current position of the aircraft and cause the display means 50 to display an image including an indication of the current position of the aircraft. In this case, the image displayed by the control unit 45 on the display means 50 may include information regarding three-dimensional distribution and information regarding flight path information. The current position of the aircraft can be measured, for example, by monitoring using a radar (not shown). The control unit 45 can receive information regarding the current position of the aircraft from a monitoring device or the like.

[0129] In addition, the control unit 45 may transmit control radio waves in response to operations by the pilot to the unmanned aerial vehicle via a base station.

[0130] The control unit 45 may also receive transmission data from the unmanned aerial vehicle via transmission radio waves and store the data in a storage means (not shown) inside or outside the radio wave environment estimation device 40. The control unit 45 may then cause the display means 50 to display an image related to the transmission data. For example, when the unmanned aerial vehicle inspects a structure, the transmission data may be data related to the results of the inspection. For example, the transmission data may be an image captured by a camera mounted on the unmanned aerial vehicle. When communication via transmission radio waves is not possible, the unmanned aerial vehicle may retain the transmission data, and transmit the transmission data when communication via transmission radio waves becomes possible.

[0131] The image that the control unit 45 causes the display means 50 to display may be output from the output unit 23 to the display means 50. In this case, the display relating to the three-dimensional distribution and the display relating to the information output from the control unit 45 may be superimposed by the output unit 23.

[0132] Next, an example of an operational flow related to mode switching by the radio wave environment estimation device 40 will be described with reference to Fig. 12. Note that, among the operational flows of the radio wave environment estimation device 40, an example of an operational flow related to generating flight path information is the same as that in Fig. 9, and therefore description thereof will be omitted.

[0133] For example, when the communication quality deteriorates below a predetermined quality based on the communication quality information (step S401), the control unit 45 recommends to the operator of the unmanned aerial vehicle that the mode be switched to the automatic flight mode (step S402). For example, the control unit 45 causes the display means 50 to display an image including a display indicating that the mode be switched to the automatic flight mode is recommended.

[0134] Furthermore, for example, the control unit 45 may check the communication quality at predetermined time intervals after switching the unmanned aerial vehicle to the automatic flight mode, and when the communication quality becomes better than a predetermined quality (step S403), switch the unmanned aerial vehicle to the manual flight mode (step S404). For example, the control unit 45 may cause the display means 50 to display an image including a display indicating that switching to the manual flight mode is recommended.

[0135] As described above, in the fourth embodiment of the present disclosure, the radio wave environment estimation device 40 includes a receiving unit 21, an estimating unit 22, and an output unit 23. The receiving unit 21 receives measured radio wave information. The measured radio wave information is information related to the measured value of the radio wave index. The radio wave index is an index related to the radio wave environment. The measured value of the radio wave index is measured at a measurement point. The measurement point is a point where the measured value of the radio wave index is measured. The radio wave environment is a radio wave environment related to control radio waves for controlling the unmanned aerial vehicle. The estimating unit 22 estimates the three-dimensional distribution using an estimation model. The three-dimensional distribution is the distribution of the radio wave environment in three-dimensional space. The three-dimensional space is a space including the area in which the unmanned aerial vehicle is flown and the measurement point. The estimation model estimates the three-dimensional distribution based on the measured radio wave information. The output unit 23 outputs estimated radio wave information. The estimated radio wave information is information related to the three-dimensional distribution.

[0136] This allows the radio wave environment estimation device 40 to estimate the distribution of the radio wave environment in a space including the area in which the unmanned aerial vehicle will be flown before the unmanned aerial vehicle is flown, thereby enabling the unmanned aerial vehicle to be flown more safely.

[0137] Furthermore, the control unit 45 may recommend to the pilot of the unmanned aerial vehicle that the flight mode be switched to automatic flight mode if the communication quality is lower than a predetermined quality based on the communication quality information. This reduces the possibility that the flight of the unmanned aerial vehicle will become unstable due to a deterioration in the radio wave environment for control radio waves, enabling the unmanned aerial vehicle to fly more safely.

[0138] [Hardware Configuration Example] An example configuration of hardware resources for realizing the radio wave environment estimation device (10, 20, 30, 40) in each of the above-described embodiments of the present disclosure using one information processing device (computer) will be described. Note that the radio wave environment estimation device may be physically or functionally realized using at least two information processing devices. Also, the radio wave environment estimation device may be realized as a dedicated device. Also, only some of the functions of the radio wave environment estimation device may be realized using an information processing device.

[0139] 13 is a diagram illustrating an example of the hardware configuration of an information processing device that can realize the radio wave environment estimation device according to each embodiment of the present disclosure. The information processing device 90 includes a communication interface 91, an input / output interface 92, a computing device 93, a storage device 94, a nonvolatile storage device 95, and a drive device 96.

[0140] 1 can be realized by a communication interface 91 and a computing device 93. Also, the estimation unit 12 can be realized by the computing device 93.

[0141] The communication interface 91 is a communication means for the radio wave environment estimation device of each embodiment to communicate with an external device via a wired or / and wireless connection. When the radio wave environment estimation device is realized using at least two information processing devices, the devices may be connected to each other via the communication interface 91 so as to be able to communicate with each other.

[0142] The input / output interface 92 is a man-machine interface including a keyboard as an example of an input device and a display as an output device.

[0143] The arithmetic unit 93 is realized by a general-purpose central processing unit (CPU), a microprocessor, or other arithmetic processing device, and a plurality of electric circuits. The arithmetic unit 93 is capable of, for example, reading various programs stored in a nonvolatile storage device 95 into the storage device 94 and executing processing in accordance with the read programs.

[0144] The storage device 94 is a memory device such as a RAM (Random Access Memory) that can be accessed by the arithmetic device 93, and stores programs, various data, etc. The storage device 94 may be a volatile memory device.

[0145] The nonvolatile storage device 95 is a nonvolatile storage device such as a ROM (Read Only Memory) or a flash memory, and is capable of storing various programs, data, and the like.

[0146] The drive device 96 is, for example, a device that processes reading and writing of data from and to a recording medium 97, which will be described later.

[0147] The recording medium 97 is any recording medium capable of recording data, such as an optical disk, a magneto-optical disk, or a semiconductor flash memory.

[0148] Each embodiment of the present disclosure may be realized, for example, by configuring a radio wave environment estimation device using an information processing device 90 illustrated in FIG. 13 and supplying a program capable of realizing the functions described in each of the above embodiments to this radio wave environment estimation device.

[0149] In this case, the embodiment can be realized by having the arithmetic unit 93 execute a program supplied to the radio wave environment estimation device. Also, it is possible to configure some, but not all, of the functions of the radio wave environment estimation device in the information processing unit 90.

[0150] Furthermore, the radio wave environment estimation device may be configured so that the program is recorded on a recording medium 97 and is stored in the non-volatile storage device 95 as appropriate when the radio wave environment estimation device is shipped or when it is in operation. In this case, the program may be supplied by installing it in the radio wave environment estimation device using an appropriate tool during the manufacturing stage before shipping or during the operation stage. The program may also be supplied by a general procedure such as downloading it from an external source via a communication line such as the Internet.

[0151] Some or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes.

[0152] (Supplementary Note 1) A radio wave environment estimation device comprising: a receiving means for receiving measured radio wave information, which is information relating to the actual measured value of a radio wave index, which is an index relating to the radio wave environment, which is the environment of radio waves related to control radio waves for controlling an unmanned aerial vehicle, measured at a measurement point; an estimation means for estimating, using an estimation model, a three-dimensional distribution, which is the distribution of the radio wave environment in a three-dimensional space, which is a space including the area in which the unmanned aerial vehicle is flown and the measurement point; and an output means for outputting estimated radio wave information, which is information relating to the three-dimensional distribution, wherein the estimation model estimates the three-dimensional distribution based on the measured radio wave information.

[0153] (Supplementary Note 2) The radio wave environment estimation device according to Supplementary Note 1, wherein the output means outputs the estimated radio wave information to a display means, thereby causing the display means to display an image relating to the three-dimensional distribution.

[0154] (Supplementary Note 3) The radio wave environment estimation device according to Supplementary Note 1 or Supplementary Note 2, wherein the estimation model is updated by adding information relating to actual measured values ​​of radio wave indices measured by the unmanned aerial vehicle as training data.

[0155] (Supplementary Note 4) The radio wave environment estimation device according to any one of Supplementary Note 1 to Supplementary Note 3, wherein the estimation model is generated using propagation estimation results, which are information regarding results of radio wave propagation estimation performed based on measured radio wave information for learning, as training data.

[0156] (Supplementary Note 5) The radio wave environment estimation device described in any one of Supplementary Note 1 to Supplementary Note 4, further comprising a generation means for generating flight path information regarding the flight path of the unmanned aerial vehicle based on the estimated radio wave information.

[0157] (Supplementary Note 6) The radio wave environment estimation device according to Supplementary Note 5, wherein the generating means generates the flight path information so that the flight path passes through a position where the control radio wave can be received.

[0158] (Supplementary Note 7) The radio wave environment estimation device according to Supplementary Note 5 or Supplementary Note 6, wherein the generating means generates the flight path information so as to maximize an evaluation score indicating a degree of appropriateness of the flight path information.

[0159] (Supplementary Note 8) The radio wave environment estimation device according to Supplementary Note 7, wherein parameters of an evaluation function used to calculate the evaluation score include a radio wave environment score, and the radio wave environment score becomes lower as the length of a path passing through an area where it is estimated that the control radio wave cannot be received becomes shorter.

[0160] (Appendix 9) The modes in which the unmanned aerial vehicle operates include a manual flight mode in which it flies in accordance with the control radio waves and an automatic flight mode in which it flies automatically, and when the quality of communication via the control radio waves is worse than a predetermined quality, the unmanned aerial vehicle transitions to the automatic flight mode, a radio wave environment estimation device described in any one of Appendices 1 to 8.

[0161] (Appendix 10) The modes in which the unmanned aerial vehicle operates include a manual flight mode in which it flies in accordance with the control radio waves and an automatic flight mode in which it flies automatically, and the generation means generates flight path information including information about a point at which the unmanned aerial vehicle will operate in automatic flight mode when the flight path includes a point at which it is predicted based on the three-dimensional distribution that the unmanned aerial vehicle will not be able to receive the control radio waves, a radio wave environment estimation device described in any one of Appendices 5 to 8.

[0162] (Supplementary Note 11) A radio wave environment estimation method comprising: receiving measured radio wave information, which is information relating to the actual measured value measured at a measurement point of a radio wave index, which is an index relating to the radio wave environment, which is the environment of radio waves related to control radio waves for controlling an unmanned aerial vehicle; estimating a three-dimensional distribution, which is the distribution of the radio wave environment in a three-dimensional space that includes the area in which the unmanned aerial vehicle is flown and the measurement point, using an estimation model that estimates the three-dimensional distribution based on the measured radio wave information; and outputting estimated radio wave information, which is information relating to the three-dimensional distribution.

[0163] (Appendix 12) A computer-readable recording medium having recorded thereon a radio wave environment estimation program that implements the following in a computer: a receiving function that receives measured radio wave information, which is information relating to the actual measured value of a radio wave index, which is an index relating to the radio wave environment, which is the environment of radio waves related to control radio waves for controlling an unmanned aerial vehicle, measured at a measurement point; an estimation function that uses an estimation model to estimate a three-dimensional distribution, which is the distribution of the radio wave environment in a three-dimensional space that is a space including the area in which the unmanned aerial vehicle is flown and the measurement point; and an output function that outputs estimated radio wave information, which is information relating to the three-dimensional distribution, wherein the estimation model estimates the three-dimensional distribution based on the measured radio wave information.

[0164] Furthermore, some or all of the configurations described in Supplementary Notes 2 to 10, which are dependent on Supplementary Note 1, may also be dependent on Supplementary Notes 11 and 12 in the same dependent relationship as Supplementary Notes 2 to 10. Furthermore, not limited to Supplementary Notes 1, 11, and 12, some or all of the configurations described as Supplements may be made dependent on various hardware, software, various recording means for recording software, or systems, within the scope of each of the above-mentioned embodiments.

[0165] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0166] This application claims priority based on Japanese Patent Application No. 2024-112439, filed on July 12, 2024, the disclosure of which is incorporated herein in its entirety by reference.

[0167] 10, 20, 30, 40 Radio wave environment estimation device 11, 21 Receiving unit 12, 22 Estimation unit 13, 23 Output unit 34 Generating unit 45 Control unit 50 Display means 90 Information processing device 91 Communication interface 92 Input / output interface 93 Arithmetic unit 94 Storage device 95 Non-volatile storage device 96 Drive device 97 Recording medium

Claims

1. A radio wave environment estimation device comprising: a receiving means for receiving measured radio wave information, which is information relating to the actual measured value of a radio wave index, which is an index relating to the radio wave environment, which is the environment of radio waves related to control radio waves for controlling an unmanned aerial vehicle, measured at a measurement point; an estimation means for estimating, using an estimation model, a three-dimensional distribution, which is the distribution of the radio wave environment in a three-dimensional space that is a space including the area in which the unmanned aerial vehicle is flown and the measurement point; and an output means for outputting estimated radio wave information, which is information relating to the three-dimensional distribution, wherein the estimation model estimates the three-dimensional distribution based on the measured radio wave information.

2. The radio wave environment estimation device according to claim 1, wherein the output means outputs the estimated radio wave information to a display means, thereby causing the display means to display an image relating to the three-dimensional distribution.

3. A radio wave environment estimation device as described in claim 1 or claim 2, wherein the estimation model is updated by adding information on the actual measured values ​​of radio wave indices measured by the unmanned aerial vehicle as training data.

4. A radio wave environment estimation device according to any one of claims 1 to 3, wherein the estimation model is generated using propagation estimation results, which are information relating to the results of radio wave propagation estimation performed based on measured radio wave information for learning, as training data.

5. A radio wave environment estimation device as described in any one of claims 1 to 4, further comprising a generation means for generating flight path information regarding the flight path of the unmanned aerial vehicle based on the estimated radio wave information.

6. The radio wave environment estimation device according to claim 5, wherein the generating means generates the flight path information so that the flight path passes through a position where the control radio wave can be received.

7. The radio wave environment estimation device according to claim 5 or 6, wherein the generation means generates the flight route information so as to maximize an evaluation score indicating the degree of appropriateness of the flight route information.

8. The radio wave environment estimation device according to claim 7, wherein the parameters of the evaluation function used to calculate the evaluation score include a radio wave environment score, and the radio wave environment score becomes lower as the length of the path passing through an area where it is estimated that the control radio waves cannot be received becomes shorter.

9. A radio wave environment estimation device as described in any one of claims 1 to 8, wherein the modes in which the unmanned aerial vehicle operates include a manual flight mode in which it flies in accordance with the control radio waves and an automatic flight mode in which it flies automatically, and when the quality of communication via the control radio waves is worse than a predetermined quality, the unmanned aerial vehicle transitions to the automatic flight mode.

10. A radio wave environment estimation device as described in any one of claims 5 to 8, wherein the modes in which the unmanned aerial vehicle operates include a manual flight mode in which it flies in accordance with the control radio waves and an automatic flight mode in which it flies automatically, and the generation means generates flight path information including information about a point at which the unmanned aerial vehicle will operate in automatic flight mode when the flight path includes a point at which it is predicted based on the three-dimensional distribution that the unmanned aerial vehicle will not be able to receive the control radio waves.

11. A radio wave environment estimation method, which receives measured radio wave information, which is information relating to the actual measured value measured at a measurement point of a radio wave index, which is an index relating to the radio wave environment, which is the environment of radio waves related to control radio waves for controlling an unmanned aerial vehicle; estimates a three-dimensional distribution, which is the distribution of the radio wave environment in a three-dimensional space that includes the area in which the unmanned aerial vehicle is flown and the measurement point, using an estimation model that estimates the three-dimensional distribution based on the measured radio wave information; and outputs estimated radio wave information, which is information relating to the three-dimensional distribution.

12. The radio wave environment estimation method according to claim 11, wherein, in outputting the estimated radio wave information, the estimated radio wave information is output to a display means, thereby causing an image relating to the three-dimensional distribution to be displayed on the display means.

13. A radio wave environment estimation method as described in claim 11 or claim 12, wherein the estimation model is updated by adding information regarding the actual measured values ​​of radio wave indices measured by the unmanned aerial vehicle as training data.

14. A radio wave environment estimation method according to any one of claims 11 to 13, wherein the estimation model is generated using propagation estimation results, which are information relating to the results of radio wave propagation estimation performed based on measured radio wave information for learning, as training data.

15. A radio wave environment estimation method described in any one of claims 11 to 14, wherein flight path information regarding the flight path of the unmanned aerial vehicle is generated based on the estimated radio wave information.

16. The radio wave environment estimation method according to claim 15, wherein, in generating the flight path information, the flight path information is generated so that the flight path passes through a position where the control radio wave can be received.

17. A radio wave environment estimation method according to claim 15 or claim 16, wherein, in generating the flight route information, the flight route information is generated so as to maximize an evaluation score indicating the degree of appropriateness of the flight route information.

18. A radio wave environment estimation method as described in claim 17, wherein the parameters of the evaluation function used to calculate the evaluation score include a radio wave environment score, and the radio wave environment score becomes lower as the length of the path passing through an area where it is estimated that the control radio waves cannot be received becomes shorter.

19. A radio wave environment estimation method described in any one of claims 11 to 18, wherein the modes in which the unmanned aerial vehicle operates include a manual flight mode in which it flies in accordance with the control radio waves and an automatic flight mode in which it flies automatically, and when the quality of communication via the control radio waves is worse than a predetermined quality, the unmanned aerial vehicle transitions to the automatic flight mode.

20. A computer-readable recording medium having recorded thereon a radio wave environment estimation program that implements the following in a computer: a receiving function that receives measured radio wave information, which is information relating to the actual measured values ​​measured at a measurement point of a radio wave index, which is an index relating to the radio wave environment, which is the environment of radio waves related to control radio waves for controlling an unmanned aerial vehicle; an estimation function that uses an estimation model to estimate a three-dimensional distribution, which is the distribution of the radio wave environment in a three-dimensional space that includes the area in which the unmanned aerial vehicle is flown and the measurement point; and an output function that outputs estimated radio wave information, which is information relating to the three-dimensional distribution, wherein the estimation model estimates the three-dimensional distribution based on the measured radio wave information.

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