Unmanned aerial vehicle, control method, and recording medium

Abstract

This unmanned flight vehicle (100) is provided with: a microphone (103) having a plurality of elements (131); and a processor (101) which processes signals outputted from the plurality of elements (131), wherein the processor (101) executes detection processing for detecting a target sound signal of a target sound from among the outputted signals, and, according to the result of the detection processing, changes, among the plurality of elements (131), elements that are subjects of signal processing.

Description

[Technical field]

[0001] The present disclosure relates to unmanned air vehicles. [Background technology]

[0002] Patent Document 1 discloses an unmanned aerial vehicle that performs a process to remove background noise from audio data collected by a background microphone. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Special Publication No. 2017-502568 Summary of the Invention [Problem to be solved by the invention]

[0004] Since it is difficult to equip such unmanned aerial vehicles with large-capacity batteries, it is desirable to reduce the amount of power required for processing in the unmanned aerial vehicles.

[0005] Therefore, the present disclosure provides an unmanned aerial vehicle that can achieve both reducing power consumption in the unmanned aerial vehicle and detecting a target sound. [Means for solving the problem]

[0006] The unmanned aerial vehicle of the present disclosure comprises a microphone having a plurality of elements and a processor that processes signals output from the plurality of elements, and the processor performs a detection process to detect a target sound signal of a target sound from the output signal, and changes the element among the plurality of elements that is to process the signal depending on the result of the detection process.

[0007] An unmanned aerial vehicle according to another aspect of the present disclosure is an unmanned aerial vehicle comprising a microphone having a plurality of elements and a processor that processes signals output from the plurality of elements, wherein the processor acquires a flight state of the unmanned aerial vehicle and changes the element among the plurality of elements that processes the signal in accordance with the flight state.

[0008] Furthermore, these general or specific aspects may be realized by a system, a method, an integrated circuit, a computer program, or a recording medium such as a computer-readable CD-ROM, or may be realized by any combination of a system, a method, an integrated circuit, a computer program, and a recording medium. Effect of the Invention

[0009] The unmanned aerial vehicle of the present disclosure can achieve both reducing power consumption in the unmanned aerial vehicle and detecting target sounds. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram showing the external appearance of an unmanned aerial vehicle and a controller according to the first embodiment. [Diagram 2] FIG. 2 is a top view of the unmanned aerial vehicle according to embodiment 1. FIG. [Diagram 3] FIG. 3 is a block diagram showing the configuration of the unmanned aerial vehicle according to the first embodiment. [Figure 4] FIG. 4 is a diagram for explaining an example of a process for changing an element that processes a plurality of signals. [Diagram 5] FIG. 5 is a diagram showing the positional relationship between the unmanned aerial vehicle and the sound source in the first scene when viewed from the horizontal direction. [Figure 6] FIG. 6 is a diagram showing an example of an element selected as a target element in the first scene. [Figure 7] FIG. 7 is a diagram showing the positional relationship between the unmanned aerial vehicle and the sound source in the second scene when viewed from the horizontal direction. [Figure 8]FIG. 8 is a diagram showing an example of an element selected as a target element in the second scene. [Figure 9] FIG. 9 is a diagram showing another example of an element selected as a target element in the second scene. [Figure 10] FIG. 10 is a diagram showing an example of an element selected as a target element in the third scene. [Figure 11] FIG. 11 is a diagram showing an example of an element that is selected as a target element when detecting a target sound in the low power mode. [Figure 12] FIG. 12 is a flowchart showing an example of the sound collection operation of the unmanned aerial vehicle. [Figure 13] FIG. 13 is a diagram for explaining a first example of a process for changing a target element depending on a remaining battery charge. [Figure 14] FIG. 14 is a diagram for explaining a second example of the process of changing the target element depending on the remaining battery charge. [Figure 15] FIG. 15 is a diagram for explaining a third example of the process of changing the target element depending on the remaining battery charge. [Figure 16] FIG. 16 is a flowchart showing a first example of the sound collection operation of the unmanned aerial vehicle according to the second embodiment. [Figure 17] FIG. 17 is a flowchart showing a second example of the sound collection operation of the unmanned aerial vehicle according to the second embodiment. [Figure 18] FIG. 18 is a flowchart showing a third example of the sound collection operation of the unmanned aerial vehicle according to the second embodiment. [Figure 19] FIG. 19 is a graph showing the relationship between the noise level of an unmanned aerial vehicle and the rotor speed command. [Figure 20] FIG. 20 is a diagram showing an example of the relationship between the rotation speed command for the rotor of an unmanned aerial vehicle and the number of target elements. [Figure 21] FIG. 21 is a flowchart showing an example of the sound collection operation of the unmanned aerial vehicle according to embodiment 3. [Figure 22]FIG. 22 is a flowchart showing an example of a change process according to the modified example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] (Findings on which this disclosure is based) As described above, the unmanned aerial vehicle described in Patent Document 1 performs signal processing to remove background noise generated by a propulsion unit such as a rotor of the unmanned aerial vehicle from collected voice data. However, no consideration is given to selecting an element to be subjected to signal processing among the multiple elements of each of the multiple microphones equipped in the unmanned aerial vehicle. For this reason, the unmanned aerial vehicle of Patent Document 1 may not be able to sufficiently reduce the amount of power required for detection processing of signals output from the multiple elements.

[0012] The unmanned aerial vehicle is equipped with a battery, and obtains thrust for flight by driving a number of rotors using the power of the battery. For this reason, the flight time (or flight distance) of the unmanned aerial vehicle is limited to a time (or distance) according to the storage capacity of the battery. In addition, since the unmanned aerial vehicle performs the above-mentioned signal processing using the power of the battery, when power is consumed in the signal processing, the power available for flying the unmanned aerial vehicle is also reduced. Therefore, the flight time of the unmanned aerial vehicle thereafter becomes shorter. Therefore, it is conceivable to reduce power consumption by stopping the signal processing in order to suppress the reduction in flight time. However, during the period when the signal processing is stopped, the target sound cannot be detected by the microphone.

[0013] As such, with conventional unmanned aerial vehicles, it is difficult to simultaneously reduce power consumption in the unmanned aerial vehicle and detect the target sound.

[0014] In order to solve such problems, an unmanned aerial vehicle according to one embodiment of the present disclosure comprises a microphone having multiple elements and a processor that processes signals output from the multiple elements, wherein the processor performs a detection process to detect a target sound signal of a target sound from the output signal, and changes the element among the multiple elements that is to process the signal depending on the result of the detection process.

[0015] According to this, since the elements to be processed are changed according to the detection result of the target sound signal, the detection process is not performed on the signals output from some elements at least either before or after the change. Therefore, the processing load required for the detection process at least either before or after the change can be reduced, and the amount of power required for the detection process can be reduced. Therefore, it is possible to reduce the power consumption of the unmanned aerial vehicle and detect the target sound at the same time.

[0016] Furthermore, the processor may increase the number of target elements for processing the signal when the target sound signal is detected from the signal by the detection process.

[0017] Therefore, the number of target elements before the target sound signal is detected can be reduced compared to after the target sound signal is detected. Therefore, the amount of power required for signal processing of the signal output from the microphone can be reduced while continuing detection of the target sound. In addition, after the target sound signal is detected, the number of target elements is increased, so that the quality of the processing result for the signal output from the microphone can be improved.

[0018] An unmanned aerial vehicle according to another aspect of the present disclosure is an unmanned aerial vehicle comprising a microphone having a plurality of elements and a processor that processes signals output from the plurality of elements, wherein the processor acquires a flight state of the unmanned aerial vehicle and changes the element among the plurality of elements that processes the signal in accordance with the flight state.

[0019] According to this, since the elements to be processed are changed according to the flight state of the unmanned aerial vehicle, detection processing is not performed on signals output from some elements at least either before or after the change. Therefore, the processing load required for detection processing at least either before or after the change can be reduced, and the amount of power required for detection processing can be reduced.

[0020] Furthermore, the unmanned aerial vehicle may further be equipped with a rotor used for flight, and the flight state may be the number of rotations of the rotor per unit time.

[0021] This allows an element suitable for the number of rotations per unit time of the rotor to be selected as the element to be processed, thereby improving the quality of the processing result for the signal output from the microphone.

[0022] The processor may also increase a number of elements of the target in the modification, and the elements of the target that process the signal before the modification may include a first element corresponding to a particular orientation of the microphone.

[0023] According to this, before increasing the number of target elements, that is, when detection processing is not performed on signals output from some elements, detection processing is performed on a signal output from a first element corresponding to a specific direction of the microphone, thereby improving the quality of sound pickup from a specific direction.

[0024] The specific direction may be a direction in which a sound source of a target sound is predicted to be located.

[0025] This improves the quality of the sound picked up from the sound source.

[0026] Additionally, the target elements that process the signal before the change may further include a second element that is closer to a source of noise generated by the unmanned aerial vehicle than the first element.

[0027] According to this, since the first element and the second element are respectively arranged at positions with different distances from the sound source of the noise generated by the unmanned aerial vehicle, the time for each element to pick up the noise is likely to differ. Therefore, in the detection process, the noise generated by the unmanned aerial vehicle can be effectively suppressed, and the deterioration of the sound collection quality of the target sound due to the noise generated by the unmanned aerial vehicle can be suppressed. Therefore, the sound collection quality of the target sound can be improved.

[0028] Moreover, the target elements for processing the signal before the modification may further include a third element located between the first element and the second element.

[0029] For this reason, since the first element, the second element, and the third element are each disposed at a different distance from the sound source of the noise generated by the unmanned aerial vehicle, there is a tendency for the time that each element picks up the noise to differ. For this reason, the noise generated by the unmanned aerial vehicle can be more effectively suppressed in the detection process, and the deterioration of the sound collection quality of the target sound due to the noise generated by the unmanned aerial vehicle can be suppressed. Therefore, the sound collection quality of the target sound can be improved.

[0030] In addition, in making the change, the processor may further change the element among the plurality of elements that is to process the signal depending on the remaining battery charge of a battery equipped in the unmanned aerial vehicle.

[0031] According to this, for example, when the remaining battery charge falls below a predetermined threshold due to flight, signal detection processing, etc., the number of target elements is reduced, so that the amount of power required for signal processing can be reduced. Therefore, the rate at which the remaining battery charge decreases can be slowed down, and the flight time of the unmanned aerial vehicle can be increased.

[0032] Also, for example, when the remaining battery charge increases above a predetermined threshold due to charging or the like, the number of target elements is increased, thereby improving the sound pickup quality.

[0033] The processor may further obtain a flight route of the unmanned aerial vehicle and estimate the remaining battery charge at a position along the flight route that the unmanned aerial vehicle is expected to reach.

[0034] Therefore, the target element can be changed according to the remaining battery power estimated from the flight route. Therefore, for example, when the remaining battery power is less than the planned power consumption to be consumed until the flight route is completed, the number of target elements can be reduced to slow down the decrease rate of the remaining battery power, and the flight time of the unmanned aerial vehicle can be increased. Also, for example, when the remaining battery power is more than the planned power consumption, the number of target elements can be increased compared to when the remaining battery power is less than a predetermined remaining power, and the sound collection quality can be improved.

[0035] The processor may also estimate the quality of the detected target sound signal using the signal output from the target element after the change, and change the flight route if the quality is below a threshold.

[0036] According to this, when the quality of the estimated target sound signal is less than the threshold, for example, the power required for flight, which is reduced by changing the flight route to shorten the flight distance, can be allocated to signal processing. Therefore, the number of target elements can be increased, and the quality of the target sound signal can be improved.

[0037] The processor may also estimate the quality of the detected target sound signal using the signal output from the target element after the modification, and if the quality is below a threshold, increase the number of the target elements so that the quality is equal to or greater than the threshold.

[0038] According to this, when the quality of the estimated target sound signal is less than the threshold value, the number of target elements can be increased, thereby improving the quality of the target sound signal.

[0039] Furthermore, these general or specific aspects may be realized as a system, a method, an integrated circuit, a computer program, or a recording medium such as a computer-readable CD-ROM, or may be realized as any combination of the system, method, integrated circuit, computer program, or recording medium.

[0040] Below, an unmanned aerial vehicle according to one embodiment of the present invention is described in detail with reference to the drawings.

[0041] Note that the embodiments described below each show a specific example of the present invention. The numerical values, shapes, materials, components, the arrangement and connection of the components, steps, and the order of steps shown in the following embodiments are merely examples and are not intended to limit the present invention. Furthermore, among the components in the following embodiments, components that are not described in an independent claim showing a superordinate concept are described as optional components.

[0042] (Embodiment 1) Hereinafter, the first embodiment will be described with reference to FIGS.

[0043] [composition] Fig. 1 is a diagram showing the appearance of an unmanned aerial vehicle and a controller according to embodiment 1. Fig. 2 is a top view of the unmanned aerial vehicle according to embodiment 1.

[0044] 1 and 2, the unmanned aerial vehicle 100 receives an operation signal from the controller 200 in response to an operation input by a user (hereinafter also referred to as "operation") to the controller 200, and flies in response to the received operation signal. In addition, while flying, the unmanned aerial vehicle 100 may capture an image using a camera 114 provided in the unmanned aerial vehicle 100 in response to the received operation signal. The captured image captured by the camera 114 may be transmitted to the controller 200, or may be transmitted to a mobile terminal such as a smartphone.

[0045] The controller 200 receives an operation from a user and transmits an operation signal corresponding to the received operation to the unmanned aerial vehicle 100. The controller 200 includes a display 300. The display 300 displays, for example, a captured image received from the unmanned aerial vehicle 100. Note that the controller 200 may be connected to a mobile terminal such as a smartphone to use the display of the mobile terminal as the display 300.

[0046] This allows the user to change the flight state, which is at least one of the position and attitude of the unmanned aerial vehicle 100 during flight, by operating the controller 200 while checking in real time the images captured by the camera 114 of the unmanned aerial vehicle 100 on the display 300 of the controller 200. This allows the user to freely change the imaging range captured by the camera 114 of the unmanned aerial vehicle 100.

[0047] The unmanned aerial vehicle 100 comprises four generators 110, an airframe 120, and four arms 121.

[0048] Each of the four generators 110 generates a force for flying the unmanned aerial vehicle 100. Specifically, each of the four generators 110 generates a force for flying the unmanned aerial vehicle 100 by generating an airflow. Each of the four generators 110 has a rotor 111 that rotates to generate an airflow, and an actuator 112 that rotates the rotor 111. The rotor 111 and the actuator 112 have a rotation axis that is approximately parallel to the vertical direction, and generate an airflow that flows from above the rotor 111 to below by rotating on the rotation axis. As a result, the four generators 110 generate a thrust that causes the unmanned aerial vehicle 100 to float upward, and generate a force for flying the unmanned aerial vehicle 100. The actuator 112 is, for example, a motor that rotates on the rotation axis of the rotor 111.

[0049] When the unmanned aerial vehicle 100 is viewed from above, the four generators 110 are arranged at 90 degree intervals around the periphery of the airframe 120, with the center of gravity of the airframe 120 at the center. In other words, the four generators 110 are arranged in a ring shape surrounding the airframe 120.

[0050] Although the rotor 111 of each of the four generators 110 is illustrated as being composed of one propeller, the present invention is not limited to this and may be composed of two contra-rotating propellers that rotate in opposite directions on the same rotation axis. The number of generators 110 may be less than four or may be five or more, as long as the propeller is capable of providing the thrust required for the unmanned aerial vehicle 100 to fly.

[0051] The body 120 is, for example, a substantially cylindrical box-shaped member, that is, a housing, and has electrical devices such as a processor, memory, battery, various sensors, etc. The shape of the body 120 is not limited to a cylindrical shape, and may be another shape such as a rectangular prism.

[0052] In addition, a camera 114 and a microphone 103 are arranged outside the airframe 120. For example, the microphone 103 is a directional microphone having a plurality of elements 131 for collecting sound. When the unmanned aerial vehicle 100 is viewed from above, the microphone 103 is fixed to the tip of an arm unit 122 that extends in a direction between two adjacent generators 110 among the four generators 110 arranged in a ring shape so as to surround the airframe 120. In other words, the microphone 103 is arranged, for example, with the airframe 120 as the center, facing in a direction shifted by 45° from the direction toward one of the four generators 110. The arm unit 122 extends, for example, toward the front of the unmanned aerial vehicle 100. For this reason, the microphone 103 is fixed to the airframe 120 while facing toward the front of the unmanned aerial vehicle 100.

[0053] Further, the four arms 121 are members that extend from the airframe 120 toward the four generators 110, and have the four generators 110 fixed to their tips. That is, one end of each of the four arms 121 is fixed to the airframe 120, and the four generators 110 are fixed to the other ends of each of the four arms 121.

[0054] Fig. 3 is a block diagram showing the configuration of the unmanned aerial vehicle according to embodiment 1. Specifically, Fig. 3 is a block diagram for explaining the hardware configuration of the unmanned aerial vehicle 100 and the functions of the processor 101.

[0055] The unmanned aerial vehicle 100 includes a processor 101, a memory 102, a microphone 103, a geomagnetic sensor 104, an acceleration sensor 105, a gyro sensor 106, a GPS (Global Positioning System) receiver 107, a battery 108, a battery monitoring unit 109, a generator 110, a communication IF (Interface) 113, a camera 114, and a gimbal 115.

[0056] The processor 101 acquires detection results detected by various sensors including the microphone 103, the geomagnetic sensor 104, the acceleration sensor 105, the gyro sensor 106, the GPS receiver 107, and the image sensor of the camera 114, reception results by the communication IF 113, and executes various processes on the acquired detection results or reception results by executing a predetermined program stored in the memory 102 or a storage (not shown). The processor 101 executes a detection process for detecting a target sound signal of a target sound from signals output from a plurality of elements 131 of the microphone 103, for example. In this way, the processor 101 controls at least one of the four generators 110, the microphone 103, the camera 114, and the communication IF 113.

[0057] The memory 102 stores coefficients used to execute a suppression process for suppressing noise from signals output by the multiple elements 131 of the microphone 103, the coefficients corresponding to a combination of elements to be processed for executing the suppression process, etc. The memory 102 may store all signals output by the multiple elements 131 of the microphone 103. The memory 102 may store a program executed by the processor 101. The memory 102 is realized by, for example, a non-volatile memory.

[0058] The microphone 103 is configured with a microphone array having a plurality of elements 131 each for collecting sound. The shape of the microphone 103 is, for example, spherical, and the plurality of elements 131 are arranged substantially uniformly at a predetermined interval on the surface of the spherical microphone 103. This allows the microphone 103 to collect sounds from a plurality of radial directions with respect to the center of the microphone 103. In other words, the microphone 103 can collect sounds from a plurality of different directions around the microphone 103. Note that the shape of the microphone 103 is not limited to a spherical shape, and may be a disc shape, and the plurality of elements 131 may be arranged at a predetermined interval on the surface of the disc-shaped microphone 103. The number of the plurality of elements 131 may be, for example, four, eight, sixteen, or any other number.

[0059] The geomagnetic sensor 104 is a sensor that detects the direction in which the reference direction of the unmanned aerial vehicle 100 is facing. The reference direction may be, for example, the front of the unmanned aerial vehicle 100. The geomagnetic sensor 104 is an example of an attitude sensor that detects the attitude of the unmanned aerial vehicle 100.

[0060] The acceleration sensor 105 is a sensor that detects acceleration in each of three different directions of the unmanned aerial vehicle 100. The acceleration sensor 105 is an example of a position sensor that detects the position of the unmanned aerial vehicle 100. Note that the three different directions may be perpendicular to each other.

[0061] The gyro sensor 106 is a sensor that detects the angular velocity of rotation around three axes that correspond to three different directions of the unmanned aerial vehicle 100. The gyro sensor 106 is an example of an attitude sensor that detects the attitude of the unmanned aerial vehicle 100.

[0062] The GPS receiver 107 receives information indicating the position of the GPS receiver from artificial satellites including GPS satellites. That is, the GPS receiver 107 detects the current position of the unmanned aerial vehicle 100. Note that the artificial satellites that transmit the information received by the GPS receiver 107 may be satellites that support the GNSS (Global Navigation Satellite System) and are not limited to GPS satellites. The GPS receiver 107 is an example of a position sensor that detects the position of the unmanned aerial vehicle 100.

[0063] The battery 108 supplies power necessary for the operation of electrical devices provided in the unmanned aerial vehicle 100, such as the processor 101, memory 102, microphone 103, geomagnetic sensor 104, acceleration sensor 105, gyro sensor 106, GPS receiver 107, battery monitoring unit 109, generator 110, communication IF 113, camera 114, and gimbal 115. The battery 108 is, for example, a secondary battery that can be charged and discharged. The battery 108 may be detachable from the airframe 120. The battery 108 is not limited to a secondary battery, and may be a replaceable (detachable) primary battery.

[0064] The battery monitoring unit 109 is a control circuit that monitors the operating state of the battery 108. The battery monitoring unit 109 is a control circuit that performs, for example, output control to control output of power stored in the battery 108 to electrical devices equipped in the unmanned aerial vehicle 100, and charging control to the battery 108 by receiving power from an external power source.

[0065] The four generators 110 have been described above and will not be described in detail.

[0066] The communication IF 113 is a communication interface for communicating with the controller 200 or a communication terminal. The communication IF 113 includes, for example, a communication interface for receiving a transmission signal emitted by the controller 200. The communication IF 113 may be, for example, a wireless LAN (Local Area Network) interface conforming to the IEEE802.11a, b, g, n, ac, and ax standards, or an interface conforming to the Bluetooth (registered trademark) standard. The communication IF 113 may be a communication interface for communicating with the camera 114. In this case, the communication IF 113 may be, for example, a wired communication interface using a USB (Universal Serial Bus) or the like.

[0067] The camera 114 is a device having an optical system such as a lens and an image sensor. The camera 114 is supported by a gimbal 115 for keeping the attitude of the camera 114 constant around the three axial directions. The gimbal 115 is a device for maintaining the attitude of the camera 114 at a desired attitude, for example, with respect to the Earth coordinate system, even if the attitude of the unmanned aerial vehicle 100 changes. Here, the desired attitude may be an attitude determined by the imaging direction of the camera 114 included in the operation signal received from the controller 200. Note that the camera 114 does not need to be supported by the gimbal 115, and the relative orientation with respect to the airframe 120 may be fixed.

[0068] The processor 101 has a flight control unit 101a, a prediction unit 101b, and a microphone control unit 101c as functional components. In other words, the functions of the flight control unit 101a, the prediction unit 101b, and the microphone control unit 101c are realized by the processor 101 executing a program stored in the memory 102.

[0069] The flight control unit 101a controls the number of rotations per unit time (i.e., the rotational speed) of the actuator 112 of the generator 110 in response to the current position, flight speed, and flight attitude of the unmanned aerial vehicle 100 detected by the geomagnetic sensor 104, the acceleration sensor 105, the gyro sensor 106, the GPS receiver 107, etc., and an operation signal from the controller 200 received by the communication IF 113. In this way, the flight control unit 101a controls the flight state of the unmanned aerial vehicle 100. In other words, the flight control unit 101a controls the flight state of the unmanned aerial vehicle 100 in response to an operation signal output from the controller 200 in response to an operation on the controller 200 by a user.

[0070] The prediction unit 101b acquires power storage information indicating the remaining battery charge of the battery 108 from the battery monitoring unit 109, and predicts the remaining possible flight time of the unmanned aerial vehicle 100 from the remaining battery charge indicated by the power storage information. The prediction unit 101b predicts the flight time based on, for example, the remaining battery charge, the amount of power consumed by the generator 110 of the unmanned aerial vehicle 100, and the amount of power consumed by the processor 101. The prediction unit 101b may measure the amount of power consumed by the generator 110 and the amount of power consumed by the processor 101 in advance, and predict the flight time using the measurement results.

[0071] The microphone control unit 101c acquires, from each of the multiple elements 131 of the microphone 103, a signal output by each of the multiple elements 131 detecting a sound. The microphone control unit 101c acquires, from the multiple elements 131, a multiple number of signals each corresponding to the multiple elements 131. The microphone control unit 101c also executes a detection process for detecting a target sound signal of a target sound from the acquired multiple signals. The microphone control unit 101c changes an element among the multiple elements 131 that is to process the multiple signals according to a result of the detection process. In the detection process, the microphone control unit 101c may perform, for example, signal conversion for converting digital signals as the multiple signals into analog signals.

[0072] FIG. 4 is a diagram for explaining an example of a process for changing an element that processes a plurality of signals.

[0073] As shown in the figure, the microphone control unit 101c switches between a low power mode and a full processing mode to perform the detection process. In the low power mode, the microphone control unit 101c performs the detection process by targeting some of the elements 131 of the microphone 103 as the detection process targets and other elements as the detection process targets. In this way, in the low power mode, signals output by some of the elements 131 of the microphone 103 are used in the detection process, and signals output by the other elements are not used in the detection process. In the full processing mode, the microphone control unit 101c uses multiple signals output by all of the elements 131 of the microphone 103 in the detection process.

[0074] That is, in the low power mode, the signals output by some other elements are not used in the detection process, so the processing load required for the detection process is reduced compared to the full processing mode. Therefore, in the low power mode, the amount of power consumption can be reduced compared to the full processing mode. On the other hand, in the full processing mode, the signals output by all of the multiple elements 131 are used in the detection process, so the quality of the detected target sound can be improved compared to the low power mode.

[0075] For example, when a target sound signal is detected by the detection process, the microphone control unit 101c may increase the number of target elements for signal processing by switching from the low power mode to the full processing mode. When a sound in a predetermined frequency band is detected by the detection process, the microphone control unit 101c may determine that the target sound signal is detected. The sound in the predetermined frequency band is, for example, a human voice, that is, a frequency band of a voice, and is a sound in the range of 300 to 11000 Hz. As a result, the microphone control unit 101c executes the detection process in the low power mode during a period when the target sound signal is not detected, so that the amount of power consumption during the period when the target sound signal is not detected can be reduced. In addition, when a target sound signal is detected, the microphone control unit 101c switches from the low power mode to the full processing mode, so that the quality of the target sound obtained by the detection process can be improved.

[0076] Conversely, when a target sound signal is detected by the detection process, the microphone control unit 101c may reduce the number of target elements for signal processing by switching from the full processing mode to the low power mode. This allows the microphone control unit 101c to detect the target sound with high sensitivity, thereby reducing the time required for detecting the target sound. Therefore, the amount of power consumption required for the detection process of the target sound can be reduced. In addition, since the detection process is performed using the signals of all the elements, the position of the sound source of the target sound can be estimated with high accuracy. Therefore, an element suitable for the position of the estimated sound source of the target sound can be selected as the target element. Therefore, even in the low power mode, the quality of the obtained target sound can be effectively improved.

[0077] 5 and 6 are diagrams showing an example of an element selected as a target element in a low power mode in a first scene. Fig. 5 is a diagram showing the positional relationship between the unmanned aerial vehicle and a sound source in the first scene when viewed from the horizontal direction. Fig. 6 is a diagram showing an example of an element selected as a target element in the first scene.

[0078] The microphone control unit 101c selects a first element corresponding to a specific direction from the microphone 103 as a target element for detection processing. Specifically, the microphone control unit 101c may process a plurality of signals output by a plurality of elements 131 using a direction estimation algorithm to estimate a direction in which the sound pressure of the target sound is estimated to be large as the specific direction.

[0079] Also, instead of estimating a specific direction using the detection result by the microphone 103, the microphone control unit 101c may estimate the specific direction using an image captured by the image sensor of the camera 114. In this case, the microphone control unit 101c identifies the position of the sound source in the image by recognizing the color, shape, type, etc. of the sound source that is predetermined by image processing of the captured image. Then, the microphone control unit 101c estimates the direction of the sound source relative to the unmanned aerial vehicle 100 as a specific direction using the position and attitude of the camera 114 relative to the unmanned aerial vehicle 100 when the image was captured and the position of the sound source in the image.

[0080] Furthermore, the microphone control unit 101c may specify the specific direction based on an operation signal received from the controller 200 via the communication IF 113. In this case, the operation signal includes information indicating the specific direction.

[0081] The sound source may be, for example, a person, an animal, a speaker, or a vehicle.

[0082] 5, the first scene is a scene in which the unmanned aerial vehicle 100 is located above the head of a person who is the sound source 10. In the first scene, the microphone control unit 101c selects, as the first element, element 131a located in a direction D1 diagonally downward outward from the unmanned aerial vehicle 100 and on the side of the surface of the microphone 103 in the direction D1 where the sound source 10 is predicted to be located.

[0083] Furthermore, the microphone control unit 101c selects a second element that is closer to the source of the noise generated by the unmanned aerial vehicle 100 than element 131a as the target element for detection processing. For example, the microphone control unit 101c selects element 131b that is closer to generator 110, which is the source of the noise generated by the unmanned aerial vehicle 100, as the second element. The microphone control unit 101c may also select elements 131c and 131d located between elements 131a and 131b as the third element.

[0084] In the first scene, the microphone control unit 101c performs detection processing on a signal output from the element 131a corresponding to the specific direction D1 of the microphone 103. Therefore, the quality of the sound pickup from the specific direction D1 can be improved. Also, in the first scene, among the multiple elements 131 of the microphone 103, the elements 131a, 131b, 131c, and 131d are arranged at positions with different distances from the generator 110, which is the sound source of the noise generated by the unmanned aerial vehicle 100. Therefore, there is a tendency for differences to occur in the time that each of the elements 131a, 131b, 131c, and 131d picks up the noise from the generator 110. Therefore, in the detection processing, the noise generated by the unmanned aerial vehicle 100 can be effectively suppressed, and the deterioration of the quality of the sound pickup of the target sound due to the noise generated by the unmanned aerial vehicle 100 can be suppressed. Therefore, the quality of the sound pickup of the target sound can be improved.

[0085] 7 and 8 are diagrams showing an example of an element selected as a target element in a low power mode in a second scene. Fig. 7 is a diagram showing the positional relationship between the unmanned aerial vehicle and a sound source in the second scene when viewed from the horizontal direction. Fig. 8 is a diagram showing an example of an element selected as a target element in the second scene.

[0086] 7, the second scene is a scene in which the unmanned aerial vehicle 100 is located at the same height as the sound source 10. In the second scene, the microphone control unit 101c selects, as the first element, element 131e, which is located in a direction D2 horizontally outward from the unmanned aerial vehicle 100 and on the side of the direction D2 where the sound source 10 is predicted to be located among the positions on the surface of the microphone 103.

[0087] Furthermore, the microphone control unit 101c selects a second element that is closer to the source of the noise generated by the unmanned aerial vehicle 100 than element 131e as the target element for detection processing. For example, the microphone control unit 101c selects element 131b that is closer to generator 110, which is the source of the noise generated by the unmanned aerial vehicle 100, as the second element. The microphone control unit 101c may also select elements 131f and 131g located between elements 131e and 131b as the third element.

[0088] In the second scene, the microphone control unit 101c performs detection processing on a signal output from the element 131e corresponding to the specific direction D2 of the microphone 103. Therefore, the quality of the sound pickup from the specific direction D2 can be improved. Also, in the second scene, among the multiple elements 131 of the microphone 103, the elements 131b, 131e, 131f, and 131g are arranged at positions with different distances from the generator 110, which is the sound source of the noise generated by the unmanned aerial vehicle 100. Therefore, there is a tendency for differences to occur in the time that each of the elements 131b, 131e, 131f, and 131g picks up the noise from the generator 110. Therefore, in the detection processing, the noise generated by the unmanned aerial vehicle 100 can be effectively suppressed, and the deterioration of the quality of the sound pickup of the target sound due to the noise generated by the unmanned aerial vehicle 100 can be suppressed. Therefore, the quality of the sound pickup of the target sound can be improved.

[0089] The low power mode is not limited to the examples described with reference to FIGS. 5 to 8, and elements as shown in FIGS. 9 to 11 may be selected.

[0090] Fig. 9 is a diagram showing another example of an element selected as a target element in the second scene. In this case, unlike the case of Fig. 8, the microphone control unit 101c may select elements 131c and 131h arranged in positions close to a straight line extending in the direction D2 passing through the element 131e, from among the elements other than the element 131e as the first element and the element 131b as the second element.

[0091] 10 is a diagram showing an example of an element selected as a target element in the third scene. The third scene is a scene in which the microphone 103 of the unmanned aerial vehicle 100 is located directly above the sound source 10. In this case, the microphone control unit 101c selects, as the first element, the element 131g located on the surface of the microphone 103 on the side of the direction D3 where the sound source 10 is predicted to be located.

[0092] Furthermore, the microphone control unit 101c selects, as the second element, element 131b, which is closer to the source of the noise generated by the unmanned aerial vehicle 100 than element 131g. Furthermore, the microphone control unit 101c may select elements 131c and 131d, which are positioned closer to a straight line that passes through element 131g and extends in direction D3, from among the elements other than element 131g as the first element and element 131b as the second element.

[0093] FIG. 11 is a diagram showing an example of an element selected as a target element when detecting a target sound in a low power mode. In a low power mode in which the low power mode is switched to a full processing mode when a target sound signal is detected by a detection process, the microphone control unit 101c may select elements located in different directions as target elements as shown in FIG. 11. Specifically, the microphone control unit 101c may select target elements located in dispersed positions so that non-target elements are included between target elements, that is, so that target elements are not adjacent to each other. This allows the target sound to be effectively detected even when a small number of elements are selected as target elements.

[0094] [Operation] Next, the operation of the unmanned aerial vehicle 100 will be described.

[0095] FIG. 12 is a flowchart showing an example of the sound collection operation of the unmanned aerial vehicle 100.

[0096] In the unmanned aerial vehicle 100, sound is collected using the microphone 103 (S11).

[0097] Next, the processor 101 determines whether or not the current processing mode of the sound collection is the low power mode (S12). Specifically, the processor 101 determines whether or not the processing mode of the sound collection stored in the memory 102 is the low power mode by referring to mode information indicating the current processing mode of the sound collection stored in the memory 102.

[0098] When the processor 101 determines that the current sound collection processing mode is the low power mode (Yes in S12), it executes a predetermined process on signals output from some of the elements selected in the low power mode among all the elements 131 of the microphone 103 (S13). As the predetermined process, the processor 101 executes a process to suppress noise generated from the generator 110 of the unmanned aerial vehicle 100, for example, using a plurality of signals output from a plurality of elements selected as elements to be subjected to the detection process. Note that the number of elements selected as elements to be subjected to the detection process in the low power mode is not limited to a plurality, and may be one.

[0099] Next, the processor 101 detects a target sound using a result of the predetermined process in step S13 (S14). The processor 101 detects a target sound signal indicating a target sound in a predetermined frequency band from a processed signal obtained by a process to suppress noise, for example.

[0100] Next, the processor 101 determines whether or not a sound collection event is detected (S15). The processor 101 may determine that a sound collection event is detected, for example, when the sound pressure level of the target sound signal detected in step S14 is equal to or higher than a predetermined sound pressure level. The processor 101 may also determine that a sound collection event is detected, for example, when the sound pressure level of a specific frequency region of the target sound signal detected in step S14 is equal to or higher than a predetermined sound pressure level. The processor 101 may also determine that a sound collection event is detected, for example, when a predetermined command is included in the voice recognition result by performing voice recognition on the target sound signal.

[0101] When it is determined that the sound collection event has not been detected (No in S15), the processor 101 determines whether or not the target event has been detected (S16). For example, the processor 101 may determine that the target event has been detected when the GPS receiver 107 of the unmanned aerial vehicle 100 detects that the unmanned aerial vehicle 100 is located at a position within a predetermined area. The processor 101 may also determine that the target event has been detected when, for example, an operation signal received by the communication IF 113 from the controller 200 includes information indicating the start of the target event. The processor 101 may also determine that the target event has been detected when, for example, a person is detected in an image captured by the camera 114 by performing image processing on the image.

[0102] When it is determined that a sound collection event is detected (Yes in S15) or when it is determined that a target event is detected (Yes in S16), the processor 101 switches the sound collection processing mode to the full processing mode (S17). For example, when switching to the full processing mode, the processor 101 updates the mode information stored in the memory 102 to information indicating that the current sound collection processing mode is the full processing mode.

[0103] In the above description, the determination in step S15 and the determination in step S16 are performed separately, but they may be performed in the same determination. For example, when performing the same determination, the processor 101 determines whether or not an event is detected. The detection of an event here includes the detection of a sound pickup event and the detection of a target event.

[0104] Next, the processor 101 executes a predetermined process on the signals output from all the elements 131 of the microphone 103 (S18). As the predetermined process, the processor 101 executes a process to suppress noise generated from the generator 110 of the unmanned aerial vehicle 100, for example, by using a plurality of signals output from all the elements 131. Note that step S18 is also performed when the processor 101 determines in step S12 that the current processing mode for the collected sound is the full processing mode (No in S12).

[0105] Next, the processor 101 detects a target sound using a result of the predetermined process in step S18 (S19). The processor 101 detects a target sound signal indicating a target sound in a predetermined frequency band from a processed signal obtained by a process to suppress noise, for example.

[0106] Next, the processor 101 determines whether the all-processing mode has been completed (S20). The processor 101 may determine that the all-processing mode has been completed, for example, when an operation signal received by the communication IF 113 from the controller 200 indicates the completion of the all-processing mode. The processor 101 may also determine that the all-processing mode has been completed, for example, when a predetermined time has elapsed since the target sound was no longer detected. The processor 101 may also determine that the all-processing mode has been completed, for example, when the GPS receiver 107 detects that the unmanned aerial vehicle 100 has been positioned outside a predetermined area.

[0107] When the processor 101 determines that all processing modes have been completed (Yes in S20), it switches the processing mode of the sound collection to the low power mode (S21). For example, when switching to the low power mode, the processor 101 updates the mode information stored in the memory 102 to information indicating that the current processing mode of the sound collection is the low power mode.

[0108] If the processor 101 determines in step S16 that the target event has not been detected (No in S16), if it determines in step S20 that the full processing mode has not been completed (No in S20), or if the switch to the low power mode has been completed in step S21, the processor 101 returns to step S11 and executes step S11.

[0109] In addition, the processor 101 may stop the sound collection operation of the unmanned aerial vehicle 100 when the operation signal received by the communication IF 113 from the controller 200 indicates stopping the operation.

[0110] [Effects, etc.] According to the unmanned aerial vehicle 100 of this embodiment, the processor 101 executes a detection process for detecting a target sound signal of a target sound from the signals output from the multiple elements 131 of the microphone 103, and changes the element among the multiple elements 131 that processes the signal according to the result of the detection process. In other words, since the processor 101 changes the element to be processed according to the detection result of the target sound signal, the detection process is not performed on the signal output from some elements at least either before or after the change. Therefore, the processing load required for the detection process at least either before or after the change can be reduced, and the amount of power required for the detection process can be reduced.

[0111] (Embodiment 2) A second embodiment will now be described.

[0112] In the unmanned aerial vehicle 100 according to the first embodiment, the processor 101 changes the element of the microphone 103 for which the signal is to be processed, among the multiple elements 131, depending on the result of the detection process, but this is not limited to the above. In the unmanned aerial vehicle 100 according to the second embodiment, the processor 101 acquires the remaining battery charge of the battery 108 provided in the unmanned aerial vehicle 100, and changes the element of the microphone 103 for which the signal is to be processed, among the multiple elements 131, depending on the remaining battery charge.

[0113] In this case, the communication IF 113 of the unmanned aerial vehicle 100 acquires the flight route of the unmanned aerial vehicle 100, for example, from the controller 200 or another device. The flight control unit 101a estimates the remaining battery charge at a position where the unmanned aerial vehicle 100 is scheduled to arrive on the flight route based on the flight route acquired by the communication IF 113 and the remaining battery charge acquired by the prediction unit 101b.

[0114] Hereinafter, a process of changing an element, among a plurality of elements 131 of microphone 103, which is a target for signal processing according to the remaining battery power will be described with reference to Figs.

[0115] Fig. 13 is a diagram for explaining a first example of a process for changing a target element according to a remaining battery level. Fig. 14 is a diagram for explaining a second example of a process for changing a target element according to a remaining battery level. Fig. 15 is a diagram for explaining a third example of a process for changing a target element according to a remaining battery level.

[0116] As shown in FIGS. 13 to 15, the flight route of the unmanned aerial vehicle 100 is, for example, a flight route that starts from the position of the home H1, passes through waypoints P1, P2, P3, and P4 in order, and returns to the home H1.

[0117] 13, the first example is an example in which the unmanned aerial vehicle 100 processes sound collection in full processing mode over the entire flight route. In the unmanned aerial vehicle 100, the flight control unit 101a predicts the battery consumption, remaining battery charge, predicted remaining battery charge upon arrival at home H1, sound collection processing mode, and remaining battery charge up to home H1 at each waypoint P1 to P4 on the flight route.

[0118] Battery consumption indicates the amount of power consumed from home H1 to each of waypoints P1 to P4. For example, battery consumption is the ratio of the amount of power consumed from home H1 to each of waypoints P1 to P4 to the battery capacity. The amount of power consumed can be calculated, for example, by integrating the time series change in output current over the operation period of the unmanned aerial vehicle 100 and multiplying the value obtained by the time integration by the rated voltage of the battery 108. The time series change in output current can be obtained by successively measuring the output current from the battery 108.

[0119] The remaining battery capacity indicates the remaining capacity of the battery 108 remaining from the home H1 to each of the waypoints P1 to P4. For example, the remaining battery capacity is a value obtained by subtracting the battery consumption capacity from 100%.

[0120] The predicted remaining battery charge when the unmanned aerial vehicle 100 arrives at the home H1 is the remaining battery charge predicted to remain when the unmanned aerial vehicle 100 flies from each of the waypoints P1 to P4 to the home H1 while collecting sound. The predicted remaining battery charge is a value obtained by subtracting the ratio of the amount of power predicted to be consumed until the unmanned aerial vehicle 100 arrives at the home H1 to the battery capacity from the remaining battery charge at each of the waypoints P1 to P4. The amount of power predicted to be consumed can be obtained, for example, by acquiring past flight data including the change in flight state from each of the waypoints P1 to P4 to the home H1, the flight distance, and the amount of power consumption corresponding to the change in flight state and the flight distance, and calculating the average amount of power consumption from the acquired past flight data. The change in flight state is, for example, a change in flight speed, straight flight, turning flight, or the like, or a change in the rotation speed of the rotor 111 in each generator 110.

[0121] The sound collection processing mode is the same as the processing mode described in the first embodiment.

[0122] The remaining battery charge up to the home H1 is information indicating a prediction of whether or not there is a remaining battery charge when the vehicle arrives at the home H1. The remaining battery charge up to the home H1 is "yes" if the predicted remaining battery charge is a positive number, and "no" if the predicted remaining battery charge is a negative number.

[0123] In the first example, the battery has remaining charge at all waypoints P1 to P4, so the unmanned aerial vehicle 100 can fly the entire flight route while collecting sound without switching to low power mode and remaining in full processing mode.

[0124] As shown in Fig. 14, the second example is an example in which the unmanned aerial vehicle 100 flies along a flight route similar to that of the first example while collecting sound, but consumes more power from the battery 108 than in the first example due to the influence of unplanned wind during the flight or a flight to confirm the source of a detected suspicious sound. Also, the second example is an example in which, like the first example, sound collection processing is performed in full processing mode over the entire flight route.

[0125] In the second example, the battery 108 consumes more power than in the first example before passing through the waypoint P2, so the predicted remaining battery charge when the unmanned aerial vehicle 100 arrives at the home H1 at the waypoint P2 is a negative number. In other words, if the full processing mode is maintained, the battery consumption before arriving at the home H1 will be greater than the remaining battery charge, so it is predicted that the unmanned aerial vehicle 100 will not be able to arrive at the home H1.

[0126] For this reason, it is possible to increase the flight time of the unmanned aerial vehicle 100 by switching the sound collection processing mode from full processing mode to low power mode.

[0127] 15, the third example, like the second example, is an example in which the power of the battery 108 is consumed more than in the first example due to the influence of unplanned wind during the flight or a flight to confirm the source of a detected suspicious sound. Also, unlike the first and second examples, the third example is an example in which sound collection processing is performed by switching from the full processing mode to the low power mode.

[0128] In the third example, as in the second example, the battery 108 consumes more power than in the first example before passing waypoint P2, so the predicted remaining battery charge when arriving at home H1 at waypoint P2 is a negative number, and it is predicted that the unmanned aerial vehicle 100 will not be able to arrive at home H1 if it remains in full processing mode. Therefore, the unmanned aerial vehicle 100 switches the sound collection processing mode from full processing mode to low power mode. As a result, from waypoint P3 onwards, the predicted remaining battery charge when arriving at home H1 is a positive number, and it is predicted that the unmanned aerial vehicle 100 will be able to fly to home H1 while collecting sound.

[0129] FIG. 16 is a flowchart showing a first example of the sound collection operation of the unmanned aerial vehicle 100 according to the second embodiment.

[0130] In the unmanned aerial vehicle 100, sound is collected using the microphone 103 (S31).

[0131] Next, the processor 101 predicts the power consumption required to fly the flight route (S32). The processor 101 calculates the power consumption required to collect sound while returning to the home H1, for example, by multiplying the flight time required to fly from the current position through each of the waypoints P1 to P4 on the flight route and return to the home H1 by the average power consumption per unit time in the current sound collection processing mode. The processor 101 also calculates the power consumption required to fly from the current position through each of the waypoints P1 to P4 on the flight route and return to the home H1, for example. The processor 101 calculates the predicted power consumption amount that is predicted to be consumed until the flight route is completed, by adding the power consumption amount required to collect sound while returning to the home H1 and the power consumption amount required for the flight back to the home H1. The processor 101 calculates the battery consumption amount to the home H1 using the calculated power consumption amount.

[0132] Next, the processor 101 determines whether or not the battery 108 has power remaining to be consumed in the current processing mode (S33). The processor 101 determines, for example, whether or not the battery consumption for flying the flight route calculated in step S32 is smaller than the remaining battery charge of the battery 108. If the battery consumption is smaller than the remaining battery charge, the processor 101 determines that the battery 108 has power remaining to be consumed in the current processing mode, and if not, determines that the battery 108 does not have power remaining to be consumed in the current processing mode.

[0133] When it is determined that there is no power remaining in battery 108 to be consumed in the current processing mode (No in S33), processor 101 performs sound collection processing by reducing the number of elements targeted for sound collection processing among multiple elements 131 of microphone 103 (S34). Processor 101 reduces the number of targeted elements by, for example, switching from the full processing mode to the low power mode.

[0134] Then, after reducing the number of elements targeted for sound collection processing, the processor 101 again determines whether or not the battery 108 has enough power to be consumed in the current processing mode (S35).

[0135] If the processor 101 determines that there is no power remaining in the battery 108 to be consumed in the current processing mode (No in S35), the processor 101 returns to step S34 to further reduce the number of elements among the multiple elements 131 of the microphone 103 that are subject to sound collection processing.

[0136] If it is determined in step S33 or S35 that the battery 108 has enough power remaining to be consumed in the current processing mode (Yes in S33 or S35), the processor 101 returns to step S31.

[0137] Furthermore, the unmanned aerial vehicle 100 according to the second embodiment may perform a sound collection operation as shown in FIG.

[0138] FIG. 17 is a flowchart showing a second example of the sound collection operation of the unmanned aerial vehicle 100 according to the second embodiment.

[0139] In the unmanned aerial vehicle 100, sound is collected using the microphone 103 (S41).

[0140] Next, the processor 101 predicts the amount of power consumption required to fly the flight route (S42). Specifically, the processor 101 performs the same process as in step S32.

[0141] Next, the processor 101 determines whether or not the battery 108 has enough power to be consumed in the current processing mode (S43). Specifically, the processor 101 performs the same process as in step S33.

[0142] When it is determined that there is no power remaining in battery 108 to be consumed in the current processing mode (No in S43), processor 101 performs sound collection processing by reducing the number of elements targeted for sound collection processing among multiple elements 131 of microphone 103 (S44). Processor 101 reduces the number of targeted elements by, for example, switching from the full processing mode to the low power mode.

[0143] Next, the processor 101 estimates the SNR (Signal-Noise Ratio) of the target sound obtained as a result of the sound collection process, and determines whether the estimated SNR is greater than a threshold value (S45). The SNR of the target sound is an example of an index indicating the quality of the target sound. The SNR of the target sound is, for example, the difference between the sound pressure level of a signal obtained by collecting the sound generated by the flight of the unmanned aerial vehicle 100 with the microphone 103 before the noise suppression process, and the sound pressure level of the target sound obtained by collecting the sound with the microphone 103 after the noise suppression process.

[0144] If the processor 101 determines that the SNR of the target sound obtained as a result of the sound collection process is below the threshold value (No in S45), it restores the number of target elements reduced in step S44 and performs the sound collection process (S46).

[0145] Next, the processor 101 adjusts the flight route of the unmanned aerial vehicle 100 (S47). The processor 101, for example, shortens the distance of the flight route.

[0146] When it is determined that the SNR of the target sound obtained as a result of the sound collection process is greater than the threshold value (Yes in S45), the processor 101 determines whether or not the battery 108 has power remaining to be consumed in the current processing mode (S48). Specifically, the processor 101 performs the same process as in step S43.

[0147] When it is determined that there is no power remaining in the battery 108 to be consumed in the current processing mode (No in S48), the processor 101 adjusts the flight route of the unmanned aerial vehicle 100 (S49). For example, the processor 101 shortens the distance of the flight route.

[0148] If it is determined in step S43 or S48 that the power consumed in the current processing mode remains in the battery 108 (Yes in S43 or S48), the processor 101 returns to step S41 after step S47 or after step S49.

[0149] Furthermore, the unmanned aerial vehicle 100 according to the second embodiment may perform a sound collection operation as shown in FIG.

[0150] FIG. 18 is a flowchart showing a third example of the sound collection operation of the unmanned aerial vehicle 100 according to embodiment 2.

[0151] In the unmanned aerial vehicle 100, sound is collected using the microphone 103 (S51).

[0152] Next, the processor 101 predicts the amount of power consumption required to fly the flight route (S52). Specifically, the processor 101 performs the same process as in step S32.

[0153] Next, the processor 101 determines whether or not the battery 108 has enough power to be consumed in the current processing mode (S53). Specifically, the processor 101 performs the same process as in step S33.

[0154] When it is determined that there is no power remaining in battery 108 to be consumed in the current processing mode (No in S53), processor 101 performs sound collection processing by reducing the number of elements targeted for sound collection processing among multiple elements 131 of microphone 103 (S54). Processor 101 reduces the number of targeted elements by, for example, switching from the full processing mode to the low power mode.

[0155] Next, the processor 101 determines whether the SNR of the target sound obtained as a result of the sound collection process is greater than a threshold value (S55).

[0156] When it is determined that the SNR of the target sound obtained as a result of the sound collection process is equal to or less than the threshold (No in S55), the processor 101 adjusts the flight route of the unmanned aerial vehicle 100 (S56). For example, the processor 101 shortens the distance of the flight route.

[0157] When it is determined that there is power remaining in battery 108 to be consumed in the current processing mode (Yes in S53), processor 101 determines whether there is power remaining in battery 108 to be consumed even if the number of elements targeted for sound collection processing is increased (S57).

[0158] When it is determined that there is still power remaining in battery 108 to be consumed even if the number of elements targeted for sound collection processing is increased (Yes in S57), processor 101 increases the number of elements targeted for sound collection processing among multiple elements 131 of microphone 103, and performs sound collection processing (S58). Processor 101 increases the number of target elements by, for example, switching from low power mode to full processing mode.

[0159] When it is determined that the SNR of the target sound obtained as a result of the sound collection process is greater than the threshold value (Yes in S55), the processor 101 determines whether or not the battery 108 has power remaining to be consumed in the current processing mode (S59). Specifically, the processor 101 performs the same process as in step S53.

[0160] When it is determined that there is no power remaining in the battery 108 to be consumed in the current processing mode (No in S59), the processor 101 adjusts (S60) the flight route of the unmanned aerial vehicle 100. For example, the processor 101 shortens the distance of the flight route.

[0161] Processor 101 returns to step S51 after step S56, after step S58, after step S60, or if it is determined in step S57 that there is no power remaining in battery 108 to be consumed even if the number of elements targeted for sound collection processing is increased (No in S57), or if it is determined in step S59 that there is power remaining in battery 108 to be consumed in the current processing mode (Yes in S59).

[0162] [Effects, etc.] According to the unmanned aerial vehicle 100 of this embodiment, when it is determined that there is no power remaining in the battery 108 to be consumed in the current processing mode, the processor 101 reduces the number of target elements, thereby reducing the amount of power required for signal processing. This makes it possible to slow down the rate at which the battery level decreases, thereby increasing the flight time of the unmanned aerial vehicle. In addition, for example, when the battery level increases above a predetermined threshold due to charging, the number of target elements is increased, thereby improving the sound collection quality.

[0163] Furthermore, according to the unmanned aerial vehicle 100 of this embodiment, the processor 101 further estimates the position that the unmanned aerial vehicle 100 is expected to reach on the acquired flight route, that is, the remaining battery charge at each of the waypoints P1 to P4.

[0164] Therefore, the processor 101 can change the target elements according to the remaining battery power estimated from the flight route. For example, in the current processing mode, when the remaining battery power is greater than the predicted power consumption amount predicted to be consumed until the flight of the flight route is completed, the processor 101 can reduce the number of target elements to slow down the rate at which the remaining battery power decreases, and the flight time of the unmanned aerial vehicle 100 can be increased. Also, for example, when the remaining battery power is greater than the predicted power consumption amount, the number of target elements can be increased compared to when the remaining battery power is less than the predicted power consumption amount, and the sound collection quality can be improved.

[0165] Furthermore, according to the unmanned aerial vehicle 100 of this embodiment, when the SNR of the estimated target sound signal is less than a threshold, the power required for flight, which is reduced by changing the flight route to shorten the flight distance, can be used for signal processing. Therefore, the number of target elements can be increased, thereby improving the quality of the target sound signal.

[0166] Also, according to the unmanned aerial vehicle 100 according to the present embodiment, the processor 101 estimates the SNR of the target sound signal detected using the signal output from the target element after the change of the target element, and if the estimated SNR is less than the threshold, increases the number of target elements so that the SNR is equal to or greater than the threshold. For example, if the determination is No in step S45, the number of target elements is increased by restoring the number of target elements to the original number in step S46, so that the SNR can be improved. Also, for example, if the determination is No in step S55, the flight route is adjusted to be shorter, so that the predicted power consumption calculated the next time step S52 is performed is reduced, and it becomes easier to determine Yes in step S53. Then, if the determination is Yes in step S53, the number of target elements is increased in step S58 and sound collection processing is performed if the determination is Yes in step S57, so that the SNR can be improved. In this way, if the SNR of the estimated target sound signal is less than the threshold, the number of target elements can be increased, so that the quality of the target sound signal can be improved.

[0167] (Embodiment 3) A third embodiment will now be described.

[0168] In the unmanned aerial vehicle 100 according to the third embodiment, the processor 101 acquires the flight state of the unmanned aerial vehicle 100, and changes the element of the microphone 103 that processes the signal according to the flight state. The flight state is, for example, the number of rotations per unit time of the rotor 111 of the generator 110 of the unmanned aerial vehicle 100.

[0169] FIG. 19 is a graph showing the relationship between the noise level of an unmanned aerial vehicle and the rotor speed command.

[0170] As shown in the figure, the larger the rotation speed command for the rotor 111 and the higher the rotation speed per unit time of the rotor 111, the higher the noise level generated by the unmanned aerial vehicle 100. This is because the noise of the unmanned aerial vehicle 100 is mainly generated by the rotation of the rotor 111. For this reason, the processor 101 may improve the quality of the target sound obtained by the sound collection process by increasing the number of elements that are the target of the sound collection process among the multiple elements 131 of the microphone 103 as the noise level generated by the unmanned aerial vehicle 100 increases.

[0171] FIG. 20 is a diagram showing an example of the relationship between the rotation speed command for the rotor of an unmanned aerial vehicle and the number of target elements.

[0172] The processor 101 may change the target elements according to a rotation speed command of the rotor 111 during flight of the unmanned aerial vehicle 100 by referring to the relationship shown in Fig. 20. The processor 101 changes the target elements so that the number of target elements increases as the rotation speed command increases. Note that the rotation speed command is indicated, for example, by the ratio of the rotation speed per unit time of the rotor 111 required to obtain thrust for flight to the maximum rotation speed per unit time of the rotor 111.

[0173] FIG. 21 is a flowchart showing an example of the sound collection operation of the unmanned aerial vehicle 100 according to the third embodiment.

[0174] In the unmanned aerial vehicle 100, sound is collected using the microphone 103 (S71).

[0175] Next, the processor 101 acquires a rotation speed command (S72). Specifically, the processor 101 determines the rotation speed per unit time of the rotor 111 as the rotation speed for generating thrust in the generator 110 for flight according to an operational instruction by the controller 200 or flight along a flight route. The processor 101 outputs a rotation speed command to the generator 110 for driving the rotor 111 at the determined rotation speed per unit time.

[0176] Processor 101 selects a set of target elements that correspond to the output rotation speed command in the relationship shown in Fig. 20 (S73). For example, when the rotation speed command is 55%, processor 101 selects the target elements of Set B.

[0177] The processor 101 executes noise suppression processing using the selected set of target elements (S74).

[0178] [Effects, etc.] According to the unmanned aerial vehicle 100 of this embodiment, the elements to be processed are changed according to the flight state of the unmanned aerial vehicle 100, for example, the number of rotations per unit time of the rotor, so that detection processing is not performed on signals output from some elements at least either before or after the change. Therefore, the processing load required for detection processing at least either before or after the change can be reduced, and the amount of power required for detection processing can be reduced. In addition, depending on the number of rotations per unit time of the rotor, an element suitable for that number of rotations can be selected as the element to be processed. Therefore, the quality of the processing result for the signal output from the microphone can be improved.

[0179] (Modification) The change process for changing the target element in the above embodiment may be executed as shown in the flowchart of Fig. 22. The change process can be applied to the processes shown in steps S21, S34, S44, S46, S54, S58, S73, etc.

[0180] FIG. 22 is a flowchart showing an example of a change process according to the modified example.

[0181] When the change process is started, the processor 101 determines whether or not the processing coefficients of the target element combination are stored in the memory 102 (S81). The processing coefficients are coefficients corresponding to each element of the target element combination used in the noise suppression process. The processing coefficients can be different values ​​depending on the target element combination.

[0182] When it is determined that the processing coefficients for the target element combination are stored in memory 102 (Yes in S81), processor 101 acquires the processing coefficients corresponding to the target element combination from memory 102 (S82).

[0183] Next, the processor 101 performs the sound collection process by applying the processing coefficients corresponding to the acquired combination of target elements to the sound collection process (S83). For example, the processor 101 performs the sound collection process by applying the processing coefficients corresponding to each of the multiple signals output from the target elements.

[0184] When it is determined that the processing coefficients for the combination of the target elements are not stored in the memory 102 (No in S81), the processor 101 determines whether or not calibration sound data for all elements of the microphone 103 is stored in the memory 102 (S84). The calibration sound data is, for example, data of collected white noise.

[0185] If the processor 101 determines that calibration sound data for all elements of the microphone 103 is stored in the memory 102 (Yes in S84), it uses the sound data to generate processing coefficients corresponding to the combination of elements of interest (S85).

[0186] When the processor 101 determines that calibration sound data for all elements of the microphone 103 is not stored in the memory 102 (No in S84), it selects a combination of elements to be the target elements from a plurality of combinations of elements corresponding to a plurality of processing coefficients stored in the memory 102 (S86).

[0187] In addition, in the above embodiment, the processor 101 changes the element among the multiple elements 131 of the microphone 103 that is the target of the sound collection processing, but this is not limited to the above, and the element that is the target of the sound collection processing may be changed by turning the power of the multiple elements 131 of the microphone 103 on and off.

[0188] Furthermore, in the above embodiment, the processor 101 may perform signal processing on the signals output from the multiple elements 131 of the microphone 103 in real time, or may store the output signals in the memory 102 and later perform signal processing using the multiple signals stored in the memory 102. In this case, information indicating whether the processing mode of the sound collection in which the multiple signals stored in the memory 102 were obtained was the full processing mode or the low power mode may be stored in the memory 102 together with the signals.

[0189] In the above embodiment, the processor 101 changes the element to be processed among the multiple elements 131 of the microphone 103. However, the present invention is not limited to this, and the frequency band to be extracted from the obtained signal may also be adjusted. The frequency band to be extracted may be the frequency band of a human voice, or may be the frequency band of a specific sound such as a whistle. The processor 101 can reduce the processing load and power consumption by extracting a signal with a narrower band than the output signal and then performing sound collection processing.

[0190] In addition, in the above embodiment, when adjusting the number of target elements, for example, the number may be adjusted continuously on an element-by-element basis, or may be adjusted stepwise on a group-by-group basis including multiple elements. For example, the number of target elements may be adjusted in n steps. That is, the number of target elements may be increased or decreased on an element-by-element basis, or may be increased or decreased stepwise on a group-by-group basis including multiple elements.

[0191] In each of the above embodiments, each component may be implemented by dedicated hardware or by executing a software program suitable for each component. Each component may be implemented by a program execution unit such as a CPU or processor reading and executing a software program recorded on a recording medium such as a hard disk or semiconductor memory.

[0192] Although the unmanned aerial vehicle according to one or more aspects of the present invention has been described based on the embodiment, the present invention is not limited to this embodiment. As long as it does not deviate from the spirit of the present invention, various modifications conceived by a person skilled in the art to this embodiment and forms constructed by combining components in different embodiments may also be included within the scope of one or more aspects of the present invention.

[0193] The processing performed by the processor 101, as well as the image recognition processing and the voice recognition processing, may use machine learning. Examples of machine learning include supervised learning, which learns the relationship between input and output using teacher data to which labels (output information) are assigned to input information, unsupervised learning, which builds a data structure only from unlabeled input, semi-supervised learning, which handles both labeled and unlabeled data, and reinforcement learning, which learns a continuous action that can obtain the most reward by obtaining feedback (reward) for an action selected from the observation result of a state. Specific examples of machine learning include neural networks (including deep learning using a multi-layered neural network), genetic programming, decision trees, Bayesian networks, and support vector machines (SVMs). In the present disclosure, any of the specific examples listed above may be used. [Industrial Applicability]

[0194] The present disclosure is useful for unmanned aerial vehicles and the like that can achieve both reduced power consumption and detection of target sounds. [Explanation of symbols]

[0195] 10. Sound Source 100 Unmanned Aerial Vehicles 101 Processor 101a Flight control unit 101b Prediction Department 101c Microphone control unit 102 Memory 103 Microphone 104 Geomagnetic Sensor 105 Acceleration Sensor 106 Gyro sensor 107 GPS receiver 108 Battery 109 Battery monitoring unit 110 Generator 111 Rotor 112 Actuator 113 Communication Interface 114 Camera 115 Gimbal 120 Aircraft 121 Arm 122 Arm section 131 elements 200 Controller 300 Display

Claims

1. a microphone having multiple elements; A processor for processing signals output from the plurality of elements; The processor, Executing a detection process for detecting a target sound signal of a target sound from the output signal; changing an element among the plurality of elements that is a target for processing the signal according to a result of the detection process; Estimating the quality of the detected target sound signal using the signal output from the target element after the modification; If the quality is less than a threshold, increase the number of elements of interest so that the quality is equal to or greater than the threshold. Unmanned aerial vehicle.

2. a microphone having multiple elements; A battery; A processor for processing signals output from the plurality of elements; An unmanned aerial vehicle having a rotor for flight, The processor, Acquire the number of rotations per unit time of the rotor blade; (i) changing the target elements such that the number of elements among the plurality of elements that are targets for processing the signal is increased as the rotation speed increases, and (ii) the number of elements among the plurality of elements that are targets for processing the signal is decreased as the remaining battery charge of the battery equipped in the unmanned aerial vehicle decreases. Unmanned aerial vehicle.

3. The elements of interest that process the signal before the modification include a first element that corresponds to a particular orientation of the microphone. An unmanned aerial vehicle as described in claim 1 or 2.

4. The specific direction is a direction in which a sound source of a target sound is predicted to be located. The unmanned aerial vehicle according to claim 3.

5. The target elements that process the signal before the modification further include a second element that is closer to a source of noise generated by the unmanned air vehicle than the first element. An unmanned aerial vehicle as described in claim 3 or 4.

6. The target elements for processing the signal before the modification further include a third element located between the first element and the second element. The unmanned aerial vehicle according to claim 5.

7. The processor further comprises: Acquire a flight route of the unmanned aerial vehicle; Estimating the remaining battery charge at a position where the unmanned aerial vehicle is scheduled to arrive along the flight route. The unmanned aerial vehicle according to claim 2.

8. The processor, Estimating the quality of the detected target sound signal using the signal output from the target element after the modification; If the quality is below a threshold, alter the flight route. The unmanned aerial vehicle described in claim 7.

9. a microphone having multiple elements; A processor for processing signals output from the plurality of elements. The processor, Acquire a flight status of the unmanned aerial vehicle; changing an element among the plurality of elements that is a target for processing the signal according to the flight state; Estimating the quality of the detected target sound signal using the signal output from the target element after the modification; If the quality is less than a threshold, increase the number of elements of interest so that the quality is equal to or greater than the threshold. Unmanned aerial vehicle.

10. a microphone having multiple elements; A battery; A processor for processing signals output from the plurality of elements; A control method for an unmanned aerial vehicle having a rotor for flight, comprising: The control method includes causing the processor to: A process of acquiring the number of rotations per unit time of the rotor; (i) executing a process of changing the target elements such that the number of elements among the plurality of elements that are targets for processing the signal is increased as the rotation speed increases, and (ii) the number of elements among the plurality of elements that are targets for processing the signal is decreased as the remaining battery charge of the battery equipped in the unmanned aerial vehicle decreases. Control methods.

11. a microphone having multiple elements; A control method for an unmanned aerial vehicle comprising: The control method includes causing the processor to: A process of acquiring a flight status of the unmanned aerial vehicle; A process of changing an element that processes the signal among the plurality of elements according to the flight state; A process of estimating the quality of a target sound signal detected using a signal output from the target element after the change; and If the quality is less than a threshold, a process of increasing the number of the target elements is executed so that the quality is equal to or greater than the threshold. Control methods.

12. a microphone having multiple elements; A battery; A processor for processing signals output from the plurality of elements; A recording medium having a program for controlling an unmanned aerial vehicle having a rotor for flight, The program causes the processor to: A process of acquiring the number of rotations per unit time of the rotor; A process of changing the target elements is executed so that (i) the number of elements among the plurality of elements that are targets for processing the signal is increased as the number of rotations increases, and (ii) the number of elements among the plurality of elements that are targets for processing the signal is decreased as the remaining battery charge of the battery equipped in the unmanned aerial vehicle decreases. Recording medium.

13. a microphone having multiple elements; A recording medium having a program for controlling an unmanned aerial vehicle including a processor for processing signals output from the plurality of elements, The program causes the processor to: A process of acquiring a flight status of the unmanned aerial vehicle; A process of changing an element that processes the signal among the plurality of elements according to the flight state; A process of estimating the quality of a target sound signal detected using a signal output from the target element after the change; and If the quality is less than a threshold, a process of increasing the number of the target elements is executed so that the quality is equal to or greater than the threshold. Recording medium.

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