Recording system, recording method, and recording program

Abstract

The purpose of the present disclosure is to provide a recording system, a recording method, and a recording program that make it possible to confirm an imaging target more affirmatively. A recording system according to the present disclosure is provided with an image data acquisition unit, a condition setting unit, a target specifying unit, a position / attitude determination unit, and a recording control unit. An image data acquisition unit acquires first image data captured by a camera provided in a moving body that has moved to a target space, based on position data recorded in advance. The condition setting unit sets a recognition condition for recognizing the imaging target based on at least one of a date and a time at which the first image data is captured and a position of the target space. The target specifying unit identifies an imaging target from the first image data. A position and attitude determination unit determines a position and attitude of the moving body with respect to the imaging target based on the recognition condition so as to capture second image data including the imaging target. The recording control unit causes the second image data to be recorded.

Description

Technical Field

[0001] This disclosure relates to a recording system, recording method, and recording procedure. Background Technology

[0002] The use of mobile entities, such as drones that move through the air, is increasing. Furthermore, along with this, the scenarios for using drones are expected to diversify. For example, the use of drones to inspect infrastructure facilities such as power transmission towers has been proposed.

[0003] PTL 1 describes an information processing device that uses images captured by multiple cameras to appropriately control the camera's exposure. In the information processing device disclosed in PTL 1, the future position of a first camera is predicted, and the brightness of an image captured by the first camera at the predicted position is predicted based on images captured by a second camera in the present or past. As a result, in the information processing device disclosed in PTL 1, the image captured by the first camera at the predicted position is controlled to have appropriate brightness.

[0004] Reference List

[0005] Patent documents

[0006] PTL 1: WO 2022 / 065039 A1 Summary of the Invention

[0007] Technical issues

[0008] In the information processing device disclosed in PTL 1, the user must operate a moving object to take pictures using both a first camera and a second camera. If the user is unfamiliar with the operation of the moving object, there is a possibility that the target cannot be photographed or that the target cannot be adequately identified.

[0009] In view of the above problems, the purpose of this disclosure is to provide a recording system, recording method and recording procedure that can more reliably identify the shooting target.

[0010] Problem Solving

[0011] According to one aspect of this disclosure, the recording system includes

[0012] The image data acquisition unit is used to acquire first image data from a camera located on a moving body that has moved into the target space, based on pre-recorded position data.

[0013] The condition setting unit is used to set identification conditions for identifying the captured target based on at least one of the date and time when the first image data was captured and the location of the target space.

[0014] The target designation unit is used to designate the target to be captured from the first image data.

[0015] A position / attitude determination unit is used to determine the position / attitude of the moving object relative to the target based on identification conditions in order to capture second image data including the target.

[0016] The recording control unit is used to record the second image data.

[0017] The recording method according to one aspect of this disclosure is executed by a computer and includes:

[0018] Based on pre-registered location data, first image data is collected from a camera provided by a moving body that has moved to the target space;

[0019] Identification conditions for identifying the captured target are set based on at least one of the date and time the first image data was captured and the location of the target space.

[0020] The target is specified from the first image data, and the position / orientation of the moving object relative to the target is determined based on the recognition conditions for capturing a second image including the target.

[0021] Record the second image data of the target being photographed.

[0022] Recording program according to one aspect of this disclosure for causing a computer to perform the following processes

[0023] Based on pre-registered location data, first image data is collected from a camera provided by a moving body that has moved to the target space;

[0024] Identification conditions for identifying the captured target are set based on at least one of the date and time when the first image data was captured and the location of the target space.

[0025] The target is specified from the first image data, and the position / orientation of the moving body relative to the target is determined according to the identification conditions to capture a second image including the target;

[0026] Record the second image data of the target being photographed.

[0027] Advantages of this disclosure

[0028] According to this disclosure, a recording system, recording method, and recording procedure that can more reliably identify the subject being filmed can be provided. Attached Figure Description

[0029] Figure 1 This is a block diagram illustrating the configuration of the recording system according to this disclosure.

[0030] Figure 2 This is a flowchart illustrating the recording method according to the present disclosure.

[0031] Figure 3 This is a block diagram illustrating an example of the use of the recording system according to this disclosure.

[0032] Figure 4 This is a schematic diagram illustrating an example of the use of the recording system according to this disclosure.

[0033] Figure 5 It is a schematic diagram illustrating the first image data and the second image data in the recording system according to the present disclosure.

[0034] Figure 6 This is a schematic diagram illustrating an example of the use of the recording system according to this disclosure.

[0035] Figure 7 This is a schematic diagram illustrating an example of the use of the recording system according to this disclosure.

[0036] Figure 8 This is a diagram illustrating a learning example of the position / attitude determination unit in the recording system according to this disclosure.

[0037] Figure 9 This is a block diagram illustrating an example of the use of the recording system according to this disclosure.

[0038] Figure 10 It is a block diagram of the recording system according to this disclosure.

[0039] Figure 11 This is a schematic diagram illustrating an example of the use of the recording system according to this disclosure.

[0040] Figure 12 It is a block diagram of the recording system according to this disclosure.

[0041] Figure 13 This is a flowchart of the recording method according to this disclosure.

[0042] Figure 14 This is a flowchart of the recording method according to this disclosure.

[0043] Figure 15 This is a flowchart of the recording method according to this disclosure.

[0044] Figure 16 This is a block diagram illustrating a configuration example of a management device 201, etc., according to this disclosure. Detailed Implementation

[0045] In the following description, this disclosure will be based on exemplary embodiments, but the disclosure described in the claims is not limited to the following exemplary embodiments. Not all configurations described in the exemplary embodiments are necessary as a means of solving the problem. For clarity, the following description and drawings have been appropriately omitted and simplified. In the drawings, the same elements are represented by the same reference numerals, and repeated descriptions are omitted where necessary.

[0046] <First Example Implementation>

[0047] <Recording System>

[0048] In the following description, the recording system according to this disclosure will be described with reference to the accompanying drawings. Figure 1 This is a block diagram illustrating the configuration of a recording system according to the present disclosure. The recording system 10 according to the present disclosure includes an image data acquisition unit 11, a condition setting unit 12, a target designation unit 13, a position / attitude determination unit 14, and a recording control unit 15.

[0049] The image data acquisition unit 11 acquires first image data from a camera provided by a moving body that has moved to the target space, based on pre-registered location data. The target space is the space that includes the target being photographed. For example, in the inspection of a power transmission tower, multiple inspection points of the power transmission tower are inspected collectively, but the target being photographed is each inspection point of the power transmission tower, and the target space is the space surrounding each inspection point of the power transmission tower. The target space can be a single space corresponding to multiple targets being photographed, or multiple spaces corresponding one-to-one to each target being photographed.

[0050] For example, in the case of three shooting targets, the target space can be a space that includes all three shooting targets, or it can be two spaces where one space includes two shooting targets and another space includes the remaining shooting target. Since the first image data is captured by a camera provided in the moving body that has moved into the target space, the first image data includes the shooting targets.

[0051] A mobile body is a moving object that moves through the air, and examples include drones (autonomous flying objects) or flying cars. Mobile bodies use methods such as Simultaneous Localization and Mapping (SLAM) to estimate their own position. In SLAM, the machine's position is calculated based on an environmental map, which is point cloud data of the surrounding environment obtained by distance measurement sensors such as LiDAR. The mobile body estimates its own position and moves towards the target space based on the received, pre-registered position data.

[0052] The condition setting unit 12 sets identification conditions for identifying the captured target based on at least one of the date and time when the first image data was captured and the location of the target space. The identification conditions include geographical conditions, seasonal conditions, weather conditions such as weather, temperature, and wind speed, and date and time conditions. Geographical conditions include topographic information associated with the location indicated by latitude, longitude, etc., and information about the surrounding environment indicating its nature or artificial structures. Additionally, the identification conditions include color, brightness, and contrast caused by the weather conditions based on each of the geographical conditions, seasonal conditions, weather conditions such as weather, temperature, and wind speed, and date and time conditions.

[0053] The target designation unit 13 designates the shooting target from the first image data. For example, since checkpoints are determined during routine inspections of infrastructure maintenance, the type of infrastructure facility is determined from the first image data, and the checkpoint is designated as the shooting target.

[0054] In order to capture second image data including the target, the position / attitude determination unit 14 determines the position / attitude of the moving body relative to the target based on identification conditions. The position / attitude of the moving body relative to the target includes, for example, the direction in which the moving body is relative to the target and the altitude at which it is flying. For example, the position / attitude of the moving body relative to the target might be flying eastward relative to the target while maintaining an altitude of 100 meters. Alternatively, the position / attitude of the moving body relative to the target could be flying at a certain angle relative to the horizontal—including the degree of tilt of the fuselage. Furthermore, the position / attitude determination unit 14 can determine not only the direction and altitude of the moving body relative to the target, but also its distance from the target.

[0055] When determining the position / attitude of the moving body, the position / attitude determination unit 14 transmits a signal to the moving body instructing it to control its position / attitude. Upon receiving the signal, the moving body moves based on the determined position / attitude and captures second image data including the target. For example, the moving body can capture the second image by approaching the target, or it can capture the second image by zooming in on a camera provided in the moving body.

[0056] Here, the first image data is captured by a camera provided in a moving body that has moved into the target space, and includes the target being photographed. However, the first image data is an image used to specify the target being photographed, and for example, due to reasons such as the small size of the target being photographed in the first image data, the user cannot use the first image data to confirm the target being photographed.

[0057] On the other hand, similar to the first image data, the second image data is captured by a camera provided in the moving body and includes the target being photographed. Furthermore, the second image data is an image captured with recognition conditions in mind, and for example, because the target in the second image data is large and clear, the user can use the second image data to confirm the target. In this way, the second image data is a confirmation image used by the user to confirm the target.

[0058] The recording control unit 15 records second image data containing the target being photographed. The recording destination of the recording control unit 15 is, for example, a memory such as random access memory (RAM) or read-only memory (ROM).

[0059] <Recording Method>

[0060] The recording method according to this disclosure will be described next. Figure 2 This is a flowchart illustrating the recording method according to the present disclosure.

[0061] First, the image data acquisition unit 11 acquires first image data from a camera provided by a moving body that has moved to the target space, based on pre-registered location data (step ST1).

[0062] Next, the condition setting unit 12 sets identification conditions for identifying the captured target based on at least one of the date and time when the first image data was captured and the location of the target space (step ST2).

[0063] Next, the target designation unit 13 designates the target from the first image data (step ST3), and the position / attitude determination unit 14 determines the position / attitude of the moving body relative to the target based on the identification conditions, so as to capture second image data including the target (step ST4).

[0064] Then, the recording control unit 15 records the second image data, including the target, in a memory such as RAM or ROM (step ST5).

[0065] As described above, in the recording system 10 according to this disclosure, the position / attitude of the moving body relative to the target is determined based on identification conditions for identifying the target, and second image data captured by the moving body based on the determined position / attitude is recorded. With this configuration, even if the user is unfamiliar with the operation of the moving body, it is easy to capture images of the target, and the target can be more reliably confirmed using the second image data.

[0066] Here, the inspection of a power transmission tower is used as an example to illustrate the use of the recording system 10 to confirm the target being photographed, but this is not the only case, and the recording system 10 according to this disclosure can also be used for infrastructure maintenance, such as the inspection of substations, and disasters such as fires and tsunamis.

[0067] <Second Example Implementation>

[0068] <Recording System>

[0069] In the following description, the recording system according to this disclosure will be described with reference to the accompanying drawings. Figure 3 This is a block diagram illustrating an example of the use of the recording system according to this disclosure. Figure 3 The illustration shows a mobile device 101 and a management device 201. The mobile device 101 and the management device 201 are connected to enable wireless communication.

[0070] The mobile body 101 includes a drive unit 111, a communication unit 112, an imaging unit 113, a mobile body control unit 114, a position data storage unit 115, and its own position estimation unit 116. The management device 201 includes a communication unit 211, a second image data storage unit 212, an image data acquisition unit 11, a condition setting unit 12, a target designation unit 13, a position / attitude determination unit 14, and a recording control unit 15. (For example...) Figure 3 As shown in the diagram, the management device 201 includes, according to Figure 1 The illustrated recording system 10 of this disclosure.

[0071] First, the configuration of the mobile body 101 will be described. The drive unit 111 includes a motor for rotating a propeller, which is the movement device of the mobile body 101. The imaging unit 113 is, for example, a camera for capturing first and second image data. The mobile body control unit 114 includes a computing device such as a CPU or MCU and controls each configuration of the mobile body 101. That is, the mobile body control unit 114 exchanges information with the management device 201 via the communication unit 112 and issues instructions accordingly for each configuration of the mobile body 101. The location data storage unit 115 includes non-volatile memory, such as flash memory or SSD, and stores location data of the target space. The self-position estimation unit 116 estimates its own position using SLAM or the like.

[0072] Next, the configuration of the management device 201 will be described. This is because the image data acquisition unit 11, condition setting unit 12, target designation unit 13, position / attitude determination unit 14, and recording control unit 15 are connected to... Figure 1Similar to that in the previous section, its description will be omitted. The management device 201 exchanges information with the mobile body 101 via the communication unit 211. The second image data storage unit 212 includes non-volatile memory such as flash memory or SSD, and stores the second image data obtained by the imaging unit 113 of the mobile body 101.

[0073] Here, we will refer to Figures 4 to 6 The recording system according to this disclosure will be described in more detail. Figure 4 and Figure 6 This is a schematic diagram illustrating an example of the use of the recording system according to this disclosure. Figure 5 This is a schematic diagram illustrating first image data and second image data in a recording system according to the present disclosure. Figures 4 to 6 The example shown uses the inspection of power transmission tower T1 as an example.

[0074] like Figure 4 As shown in the diagram, assume that the checkpoint of the power transmission tower T1 is a checkpoint CP1 with a defect CR1. Figures 4 to 6 The target of the filming was checkpoint CP1. Furthermore, in Figures 4 to 6 In this context, assume the left direction of the graph is west, and the depth direction is north. Figure 4 and Figure 6 In the example shown, the target space is TS1.

[0075] First, since the location data storage unit 115 stores the location data of the target space TS1, the moving body 101 can move toward the target space TS1, such as... Figure 4 As illustrated. Then, the moving body 101 takes pictures through the imaging unit 113. Figure 5 The first image data 300 is shown in the figure. Figure 5 The first image data 300 shown includes the entire power transmission tower T1. In the first image data 300, the presence of defect CR1 at inspection point CP1 cannot be confirmed.

[0076] Next, the management device 201 acquires first image data 300 captured by the moving body 101 via the image data acquisition unit 11. The condition setting unit 12 sets identification conditions based on the location of the target space TS1 and the date and time when the first image data was captured. For example, the power transmission tower T1 is located at 45 degrees north latitude and 140 degrees east longitude, and the date and time when the first image data 300 was captured are as follows: Figure 5 In the case of late afternoon in February as illustrated, setting the condition setting unit 12 at 45 degrees north latitude and 140 degrees east longitude is the identification condition for winter dusk.

[0077] Next, the target designation unit 13 designates checkpoint CP1 from the first image data 300. Then, the position / attitude determination unit 14 determines the position / attitude of the moving body relative to the target being photographed, so as to capture second image data based on the identification conditions.

[0078] Reference Figure 6 The position / attitude of the moving body 101 is described. The position / attitude determination unit 14 determines that the sun is located to the west based on the identification condition that it is dusk at the location of 45 degrees north latitude and 140 degrees east longitude. In this case, if an attempt is made to capture second image data from the east side (right side in the figure) towards the west side (left side in the figure) of checkpoint CP1, the light becomes backlight, and a clear image of checkpoint CP1 cannot be captured. On the other hand, if the second image data is captured from the west side (left side in the figure) towards the east side (right side in the figure), the light does not become backlight, and a clear image of checkpoint CP1 can be captured.

[0079] Therefore, the position / attitude determination unit 14 determines that the aircraft is flying at a height of 20 meters to the west relative to the checkpoint CP1, so that the moving body 101 can take pictures from the west relative to the checkpoint CP1.

[0080] Next, as Figure 6 As illustrated, once the moving body 101 flies at an altitude of 20m relative to the checkpoint CP1 to the west, it is captured by the imaging unit 113. Figure 5 The illustrated second image data 400. Next, the management device 201 causes the recording control unit 15 to store the second image data 400 captured by the imaging unit 113 in the second image data storage unit 212.

[0081] like Figure 5 As illustrated, in the second image data 400, the checkpoint CP1 is magnified compared to the first image data 300. As a result, the user cannot confirm that the checkpoint CP1 has a defect CR1 in the first image data 300, but can confirm that the checkpoint CP1 has a defect CR1 in the second image data 400.

[0082] <Movement Planning Path>

[0083] exist Figure 5 In the illustrated example, the first image data 300 includes only one checkpoint CP1, but is not limited to this, and the first image data may include multiple shooting targets. In this case, the target designation unit 13 creates a movement planning path for the shooting targets from the first image data based on identification conditions. (Refer to...) Figure 7 Provide a more specific description. Figure 7 This is a schematic diagram illustrating an example of the use of the recording system according to this disclosure.

[0084] exist Figure 7 In the example shown, the checkpoints for power transmission tower T11 are three points from checkpoint CP1 to CP3. Figure 7 The shooting targets were three points among checkpoints CP1 to CP3. Additionally, in Figure 7 In this diagram, assume the right direction is west and the front direction is north. Figure 7 In the illustrated example, the target space is not shown, but it is assumed to be a space including three checkpoints CP1 to CP3.

[0085] In addition, Figure 7 In the illustrated example, it is assumed that the power transmission tower T11 is located at 25 degrees North latitude and 130 degrees East longitude, and the date and time of the first image data acquisition are summer noon. That is, the condition setting unit 12 is set to identify the summer noon time zone as 25 degrees North latitude and 130 degrees East longitude.

[0086] like Figure 7 As shown, target designation unit 13 determines at 12:00 that the sun is directly above power transmission tower T11 based on the identification condition that the location is in the summer noon time zone at 25 degrees north latitude and 130 degrees east longitude. Furthermore, as... Figure 7 As shown in the diagram, at 13:00, target designation unit 13 determines that the sun is slightly west of power transmission tower T11. Figure 7 (The right side of the middle).

[0087] In this scenario, checkpoints CP11 and CP13 are brightly illuminated by the sun at 12:00, but the sun shifts to the west at 13:00, making them slightly darker. On the other hand, checkpoint CP12 is more brightly illuminated by the sun at 13:00 than it was at 12:00.

[0088] Therefore, the target designation unit 13 creates a movement planning path L1 such that checkpoints CP11 and CP13 are captured first, and checkpoint CP12 is captured later. As a result, even if the user is unfamiliar with the operation of the moving body, it is possible to prevent the failure to capture the second image data and to effectively acquire the second image data.

[0089] Here, as Figure 7 The illustration shows an example of a motion planning path created by the target designation unit 13 based on brightness according to seasonal conditions. However, this is not the only case, and the target designation unit 13 can create a motion plan based on at least one of the following identification conditions: geographical conditions, seasonal conditions, weather conditions such as weather, temperature and wind speed, date and time conditions, and flight time identification conditions.

[0090] Furthermore, the target designation unit 13 may have the following configuration. First, the target designation unit 13 calculates the success rate of the second image data in each target based on at least one of the identification conditions and the time of flight.

[0091] The shooting success rate calculated by the target designation unit 13 will be described using the following example: a moving body is shooting two separate targets in weather conditions where it is predicted to rain 30 minutes later than the forecast. Here, it is assumed that the flight time relative to one target near the moving body is within 30 minutes, and the flight time relative to another target far from the moving body is more than 30 minutes.

[0092] Since the flight time of the moving object relative to one of the shooting targets located near the moving object is less than 30 minutes, there is a high probability that it will not rain, and therefore a high probability that the second image data will be successfully captured. However, since the movement time of the moving object relative to another shooting target located far from the moving object is more than 30 minutes, there is a possibility that the weather will change during the movement and that it will rain when the moving object reaches the other shooting target. Therefore, the other shooting target located farther from the moving object has a lower probability of success in capturing the second image data compared to the other shooting target located closer to the moving object. In this way, the target designation unit 13 calculates the success rate of capturing the second image data relative to each shooting target.

[0093] The target designation unit 13 can calculate the imaging success rate by allowing the user to select at least one of the identification conditions and flight time. Furthermore, the user can choose whether or not to calculate the imaging success rate of the target designation unit 13. Of course, the target designation unit 13 can use values ​​such as, for example, 50% or 0.5 to calculate the success rate of capturing the second image data.

[0094] Then, the target designation unit 13 creates a motion planning path based on the success rate of the capture, indicating the order in which each target is captured. In the example above, a target located close to the moving body is captured in descending order of the probability of successfully capturing the second image data, and a motion planning path is created for capturing another target located far from the moving body. As a result, even if the user is unfamiliar with the operation of the moving body, it is possible to further suppress the failure to capture the second image data and to effectively acquire the second image data.

[0095] <Using a learning model to determine the position / attitude of a moving object>

[0096] Here, the position / attitude determination unit 14 can use a trained model to determine the position / attitude of the moving object. This trained model has learned to determine the position / attitude of the moving object using identification conditions and first image data including the target being captured as input. (Refer to...) Figure 8 Provide a more specific description. Figure 8 This is a diagram illustrating a learning example of the position / attitude determination unit in the recording system according to this disclosure.

[0097] like Figure 8 As illustrated, the learning model LM1 is generated by learning from sample images associated with geographical conditions, seasonal conditions, weather conditions such as weather, temperature, and wind speed, and date and time conditions. The learning model LM1 is generated, for example, by learning from sample images of power transmission towers including checkpoints, which are photographic targets associated with geographical conditions such as latitude and longitude, and weather conditions such as rain. The learning model LM1 is generated, for example, by utilizing learning methods such as neural networks. The trained model LM2 is either a model that has already completed learning from the learning model LM1 or is currently being trained.

[0098] As a result, such Figure 8 As illustrated, the position / pose determination unit 14 can determine the position / pose of a moving object using a trained model LM2 by using identification conditions and first image data as input. For example, in Figure 6 In the illustrated example, the first image data is of a power transmission tower taken at a location of 45 degrees North latitude and 140 degrees East longitude, and the identification condition is that it is winter dusk at this location. Therefore, the position / attitude determination unit 14 uses the trained model LM2 as input to determine that the moving body is approaching the checkpoint CP1 from the west while maintaining a height of 20m. In this way, the position / attitude determination unit 14 can automatically determine the position / attitude of the moving body using the trained model LM2.

[0099] Furthermore, if the capture of the second image data fails, the learning model LM1 can be relearned using neural networks or similar methods. In other words, the learning model LM1 can be generated by learning from sample images associated with geographical conditions, seasonal conditions, weather conditions such as weather, temperature, and wind speed, and date and time conditions, even when the capture has failed, rather than only when the capture has been successful. As a result, the position / pose determination unit 14 can use the trained model LM2 to determine the position / pose of the moving object and suppress the failure to capture the second image data.

[0100] <Explicit Description of the Subject Using a Learning Model>

[0101] Here, it has been described that the position / attitude determination unit 14 uses a trained model to determine the position / attitude of a moving body. Similarly, the target designation unit 13 can use a trained model to designate a shooting target from the first image data. More specifically, the learning model is generated by learning sample images associated with the shooting target. For example, in the case of a tall building, the checkpoint used as the shooting target is a lightning rod on the roof or window, and therefore the learning model is generated by learning sample images of tall buildings associated with lightning rods or windows. As a result, the target designation unit 13 is able to designate a shooting target using the first image data as input by using a trained model.

[0102] Furthermore, if the acquisition of the second image data fails, the learning model can be relearned using neural networks or similar methods. In other words, a learning model can be generated not only when the acquisition of the second image data is successful, but also when the acquisition of the second image data fails. As a result, the target designation unit 13 can designate the target using the trained model and suppress the failure to acquire the second image data.

[0103] <Creating Mobility Planning Paths Using Learning Models>

[0104] Furthermore, the target designation unit 13 can create a planned movement path for the target by using a learned model. In this case, the learned model is generated by learning from sample images, wherein at least one of the identification conditions and time of flight is associated with the first image data. The target designation unit 13 is able to create a planned movement path for the target by using the trained model, taking at least one of the identification conditions and time of flight and the first image data as input.

[0105] The learning model is not limited to learning at least one sample image associated with the first image data if the acquisition of the second image data has been successful. If the acquisition of the second image data has failed, the learning model can also learn at least one sample image associated with the first image data if the acquisition of the second image data has failed. With this configuration, even if the moving body moves according to the movement planning path created by the target designation unit 13 and the acquisition of the second image data fails, the failure result can be reflected when creating the next movement planning path. Therefore, it is possible to suppress the failure to acquire the second image data.

[0106] In this way, the target designation unit 13 can use a trained model to designate the shooting target, and further, can use the trained model to create a movement planning path for the shooting target.

[0107] Here, in Figure 3 In the illustrated example of the recording system, the mobile body 101 and the management device 201 are connected wirelessly. However, the example of the recording system is not limited to this and may include... Figure 9 The example shown in the illustration. Figure 9 This is a block diagram illustrating an example of the use of the recording system according to this disclosure. Figure 9 In this context, the moving body 102 includes a driving unit 111, a communication unit 112, an imaging unit 113, a moving body control unit 114, a position data storage unit 115, a second image data storage unit 212, an image data acquisition unit 11, a condition setting unit 12, a target designation unit 13, a position / attitude determination unit 14, and a recording control unit 15. That is, it is related to... Figure 3 Compared to the illustrated example of a recording system, the mobile body 102 is able to perform all processing of each functional block without communicating with the management device.

[0108] <Third Example Implementation>

[0109] <Recording System>

[0110] In the following description, the recording system according to this disclosure will be described with reference to the accompanying drawings. Figure 10 This is a block diagram of the recording system according to this disclosure. For example... Figure 10 As illustrated, the recording system 20 includes a weather information acquisition unit 16, a shooting condition setting unit 17, an image data acquisition unit 11, a condition setting unit 12, a target designation unit 13, a position / attitude determination unit 14, and a recording control unit 15. Because the image data acquisition unit 11, the target designation unit 13, the position / attitude determination unit 14, and the recording control unit 15 are... Figure 1 and Figure 3 Those similar to those in the previous section will be omitted from the description. Here, the weather information acquisition unit 16, the condition setting unit 12, and the shooting condition setting unit 17 will be described.

[0111] <Setting identification criteria based on weather information>

[0112] The weather information acquisition unit 16 acquires weather information in the target space. The weather information includes information related to weather, temperature, and wind speed. It includes past weather data and weather forecast data. For example, the weather information acquisition unit 16 acquires weather data for locations corresponding to the target space from meteorological bureau weather data. The condition setting unit 12 further sets identification conditions based on weather information from the date and time the first image data was captured.

[0113] The weather information acquisition unit 16, the condition setting unit 12, and the position / attitude determination unit 14 will be described in more detail. Here, the first image data will be described by way of example, which was obtained by taking a picture of a power transmission tower located at 35 degrees North latitude and 140 degrees East longitude at 11:00 AM on February 20. In addition, it is assumed that the weather forecast for the location at 35 degrees North latitude and 140 degrees East longitude on February 20 is rain in the morning and sunny in the afternoon.

[0114] In this scenario, firstly, the weather information acquisition unit 16 acquires weather data at a location of 35 degrees North latitude and 140 degrees East longitude, indicating rain in the morning and clear skies in the afternoon. Next, the condition setting unit 12 determines that the first image data was taken at 11:00 AM on February 20th at a location of 35 degrees North latitude and 140 degrees East longitude, and based on the acquired weather data, 11:00 AM at that location is a rain forecast. Then, the condition setting unit 12 sets the identification condition that the location at 35 degrees North latitude and 140 degrees East longitude is in a time zone before noon and that it is raining. Based on this identification condition, the position / attitude determination unit 14 determines the position / attitude of the moving object used to capture the second image data. (Refer to...) Figure 11 An example describing the position / attitude of the moving body determined by the position / attitude determination unit 14.

[0115] Figure 11 This is a schematic diagram illustrating an example of the use of the recording system according to this disclosure. Figure 11 The illustration shows the status of checkpoint CP51, located at 35 degrees North latitude and 140 degrees East longitude, photographed at 11:00 AM using moving object 311. Furthermore, in Figure 11 In the diagram, we assume that the left direction of the graph is west and the depth direction of the graph is north.

[0116] like Figure 11 As illustrated, since it is raining around radio tower T51, if a photo of checkpoint CP51 is taken from the west, the second image data will include the rain. On the other hand, if a photo of checkpoint CP51 is taken from the east while it is below radio tower T51, the rain is blocked by radio tower T51, and the second image data will not include the rain and will become a clear image. Therefore, for example, the position / attitude determination unit 14 determines that it is flying at a height of 20 m relative to the east of checkpoint CP1, so that the moving body 311 can take a photo from the east relative to checkpoint CP51.

[0117] As described above, by including the weather information acquisition unit 16, the recording system 20 can set identification conditions by taking into account weather information in the target space, and can determine the position / attitude of the moving object based on the identification conditions. Therefore, more accurate second image data can be acquired, and the user can more reliably confirm the shooting target.

[0118] <Setting up shooting conditions>

[0119] The shooting condition setting unit 17 sets shooting conditions for capturing second image data based on the identified conditions. Shooting conditions are settings of the imaging unit for the moving object, and include, for example, zoom, brightness, contrast, color settings, flash presence / absence, shooting time, shutter speed, etc. More specifically, under identified conditions where the location is at 35 degrees North latitude and 140 degrees East longitude, in a time zone before noon, and it is raining, the shooting condition setting unit 17 adjusts the brightness and contrast to capture second image data.

[0120] As described above, by providing the shooting condition setting unit 17, the second image data can be captured according to the identification conditions, enabling the acquisition of more accurate second image data, and allowing the user to confirm the shooting target.

[0121] <Fourth Example Implementation>

[0122] <Recording System>

[0123] In the following description, the recording system according to this disclosure will be described with reference to the accompanying drawings. Figure 12 This is a block diagram of the recording system according to this disclosure. For example... Figure 12 As illustrated, the recording system 40 includes a shooting feasibility determination unit 30, a control unit 31, an image data acquisition unit 11, a condition setting unit 12, a target designation unit 13, a position / attitude determination unit 14, and a recording control unit 15. Because the image data acquisition unit 11, condition setting unit 12, target designation unit 13, position / attitude determination unit 14, and recording control unit 15 are... Figure 1 , Figure 3 and Figure 10 Those similar to those in the previous section will be omitted from the description. Here, the firing feasibility determination unit 30 and the control unit 31 will be described.

[0124] The shooting feasibility determination unit 30 determines whether the shooting of the target has been successful based on the second image data. For example, if the target is included in the second image data and the user can confirm the target, the shooting feasibility determination unit 30 determines that the shooting of the target has been successful. On the other hand, for example, if the target is not included in the second image data, or if the target is included in the second image data but is too dark to be confirmed, the shooting of the target is determined to have not been successful.

[0125] The control unit 31 controls the moving body based on the determination result of the shooting feasibility determination unit 30. More specifically, when the shooting feasibility determination unit 30 determines that the shooting of the target has been successful, the control unit 31 controls the moving body to leave the target space.

[0126] On the other hand, if the shooting feasibility determination unit 30 determines that the shooting target has not been successfully photographed, the identification conditions are reset, and the control unit 31 controls the moving body to perform shooting of the shooting target again.

[0127] With this configuration, even if the weather is sunny when the identification conditions are set but changes to rain when the second image is taken, accurate second image data can still be acquired by resetting the identification conditions and taking another shot. Therefore, users can more reliably confirm the target.

[0128] Furthermore, if the shooting feasibility determination unit 30 determines that the shooting of the target has not been successful, the control unit 31 can control the moving body to leave the target space after a predetermined time has elapsed since the start of shooting the target. Using this configuration, for example, if, due to adverse weather conditions, even multiple shots cannot acquire second image data that confirms the target, second image data of another target can be acquired first.

[0129] Furthermore, if the shooting feasibility determination unit 30 determines that the shooting of the target has not been successful, the control unit 31 can control the moving body to leave the target space after shooting the target a predetermined number of times. Using this configuration, for example, even in unstable weather conditions, accurate second image data can be acquired by taking multiple shots.

[0130] Here, the recording system 40 may further include a proximity detection unit for detecting that another moving object is approaching the moving object that has already been photographed. For example, the proximity detection unit acquires... Figure 3The illustrated position estimation unit 116 of each moving body measures its own position data and detects that another moving body is approaching. Additionally, the proximity detection unit can be configured to detect the approach of another moving body by providing proximity sensors within the moving body and to acquire information indicating that another moving body is approaching.

[0131] If the shooting feasibility determination unit 30 determines that the shooting of the target has not been successful, the control unit 31 may perform the following processing. If the proximity detection unit detects that another moving body is approaching, the control unit 31 controls the moving body that has already shot the target to leave the target space, so that the other moving body and the moving body that has already shot the target do not interfere with each other.

[0132] Furthermore, in the control unit 31, the timing for causing the moving body that has already photographed the target to leave the target space can be any timing, as long as the other moving body does not interfere with the moving body that has already photographed the target. For example, if another moving body enters the target space, the control unit 31 can cause the moving body that has already photographed the target to leave the target space. As another example, the control unit 31 can cause the moving body that has already photographed the target to leave the target space before the other moving body moves to a position overlapping with the moving body that has already photographed the target.

[0133] With this configuration, even if another mobile body flies to photograph the target, the mobile bodies can acquire second image data without interfering with each other, and the user can confirm the target.

[0134] <Recording Method>

[0135] The recording method according to this disclosure will be described next. Figures 13 to 15 This is a flowchart illustrating the recording method according to this disclosure. Steps ST1 to ST5 are similar to... Figure 2 The recording method is illustrated, and therefore its description will be omitted.

[0136] like Figure 13 As illustrated, after step ST5, the shooting feasibility determination unit 30 determines whether the shooting of the target has been successful (step ST6). For example, if the shooting feasibility determination unit 30 determines that the shooting of the target has been successful (step ST6 is yes), the recording control unit 15 records the second image data in a memory such as RAM or ROM. Figure 13 The diagram shows (step ST7).

[0137] On the other hand, if the shooting feasibility determination unit 30 determines that the shooting of the target has not been successful (step ST6 No), then as follows Figure 14As illustrated, the control unit 31 determines whether a predetermined time has elapsed since the start of capturing the second image data (step ST11). If the predetermined time has elapsed since the start of capturing the second image data (step ST11 Yes), the control unit 31 controls the moving object that has captured the target to leave the target space (step ST12). If the predetermined time has not elapsed since the start of capturing the second image data (step ST11 No), the control unit 31 returns to step ST2 and resets the recognition conditions.

[0138] Here, when the proximity detection unit detects that another moving object is approaching a moving object that has already been photographed, the following operations can be performed.

[0139] If the shooting feasibility determination unit 30 determines that the shooting of the target has not been successful (step ST6 No), such as Figure 15 As illustrated, the proximity detection unit determines whether another moving object is approaching the moving object that has already photographed the target (step ST21). If the proximity detection unit detects that another moving object is approaching the moving object that has already photographed the target (step ST21 Yes), the control unit 31 controls the moving object that has already photographed the target to leave the target space (step ST22). If the proximity detection unit has not detected that another moving object is approaching the moving object that has already photographed the target (step ST21 No), the control unit 31 returns to step ST2 and resets the recognition conditions.

[0140] Here, different flowcharts are used to illustrate whether a predetermined time has elapsed since the start of capturing the second image data and whether another moving body is approaching the moving body that has already captured the target. However, this is not the only case, and both whether a predetermined time has elapsed since the start of capturing the second image data and whether another moving body is approaching the moving body that has already captured the target can be determined. For example, if the approach detection unit does not detect another moving body approaching the moving body that has already captured the target (step ST21 No), the control unit 31 can perform the determination in step ST11.

[0141] Back Figure 13 The description will continue. After step ST7, the shooting feasibility determination unit 30 determines whether all shooting targets have been photographed (step ST8). If the shooting feasibility determination unit 30 determines that all shooting targets have been photographed (step ST8 Yes), the recording method ends. On the other hand, if the shooting feasibility determination unit 30 determines that not all shooting targets have been photographed (step ST8 No), the process returns to step ST1, and the image data acquisition unit 11 acquires first image data to perform shooting of the next shooting target.

[0142] As described above, in the recording system 40 according to this disclosure, the shooting feasibility determination unit 30 determines whether the shooting of the target has been successful based on the second image data, and the control unit 31 controls the moving body based on the determination result of the shooting feasibility determination unit 30. With this configuration, even if the shooting of the target has not been successful, the identification conditions are reset, and the second image data can be accurately acquired by shooting again. Therefore, the user can more reliably confirm the shooting target.

[0143] Furthermore, even if the target has not yet been successfully photographed, the recording system 40 according to this disclosure can control the moving body that has been photographing the target to leave the target space if a predetermined time has elapsed since the start of the second image capture or if another moving body is approaching. With this configuration, the recording system 40 according to this disclosure can prevent collisions between moving bodies, even if another moving body is flying to photograph the target.

[0144] <Configuration Example>

[0145] Figure 16 This is a block diagram illustrating a configuration example of management device 201 and mobile bodies 101, 102, and 311 (hereinafter referred to as management device 201, etc.) according to this disclosure. Reference Figure 16 The management device 201 includes a network interface 1201, a processor 1202, and a memory 1203. The network interface 1201 can be used to communicate with network nodes. The network interface 1201 may include, for example, a network interface card (NIC) compliant with the IEEE 802.3 family. IEEE stands for Institute of Electrical and Electronics Engineers.

[0146] Processor 1202 reads from memory 1203 and executes software (computer program) to perform the processing of management device 201, etc., as described in the flowcharts of the above example embodiments. Processor 1202 may be, for example, a microprocessor, a microprocessor unit (MPU), or a central processing unit (CPU). Processor 1202 may include multiple processors.

[0147] Memory 1203 is composed of a combination of volatile and non-volatile memory. Memory 1203 may include storage located remotely from processor 1202. In this case, processor 1202 can access memory 1203 via an input / output (I / O) interface (not shown).

[0148] exist Figure 16In the example, memory 1203 is used to store software module groups. Processor 1202 is able to perform the processing of the management device 201, etc., described in the above example embodiment by reading from memory 1203 and executing these software module groups.

[0149] For reference Figure 16 As described, each processor in the management device 201, etc., executes one or more programs that include a group of commands for enabling the computer to perform the algorithms described with reference to the accompanying drawings.

[0150] Furthermore, some or all of the processes described above in the recording system according to this disclosure can be implemented as a computer program. Such a program can be stored and supplied to a computer using various types of non-transitory computer-readable media. Non-transitory computer-readable media include various types of tangible recording media. Examples of non-transitory computer-readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, or hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD read-only memory (ROM), CD-R, CD-R / W, and semiconductor memories (e.g., mask ROM, programmable ROM (PROM), erasable PROM (EPROM), flash memory ROM, or random access memory (RAM)). Programs can be supplied to a computer using various types of transient computer-readable media. Examples of transient computer-readable media include electrical signals, optical signals, and electromagnetic waves. Transient computer-readable media can provide programs to a computer via wired communication lines—such as electrical wires and optical fibers or wireless communication lines.

[0151] While this disclosure has been specifically shown and described with reference to exemplary embodiments thereof, this disclosure is not limited to these exemplary embodiments. Those skilled in the art will understand that various changes in form and detail may be made without departing from the spirit and scope of this disclosure as defined by the claims. Furthermore, each exemplary embodiment may be suitably combined with other exemplary embodiments.

[0152] Each of the accompanying drawings is merely an example for illustrating one or more exemplary embodiments. Each drawing is not associated with only one specific exemplary embodiment, but may be associated with one or more other exemplary embodiments. As will be understood by those skilled in the art, various features or steps described with reference to any of the accompanying drawings may be combined with features or steps illustrated in one or more other drawings, for example, to create exemplary embodiments that are not explicitly illustrated or described. All features or steps illustrated in any of the accompanying drawings for illustrative exemplary embodiments are not necessarily mandatory, and some features or steps may be omitted. The order of steps described in any of the accompanying drawings may be appropriately changed.

[0153] Some or all of the above example embodiments may be described as the following supplementary notes, but are not limited to them.

[0154] (Supplementary Note 1)

[0155] A recording system, comprising:

[0156] The image data acquisition unit is used to acquire first image data from a camera located on a moving body that has moved into the target space, based on pre-recorded position data.

[0157] The condition setting unit is used to set identification conditions for identifying the captured target based on at least one of the date and time when the first image data was captured and the location of the target space.

[0158] The target designation unit is used to designate the target to be captured from the first image data.

[0159] A position / attitude determination unit is used to determine the position / attitude of the moving object relative to the target based on identification conditions in order to capture second image data including the target.

[0160] The recording control unit is used to record the second image data.

[0161] (Supplementary Note 2)

[0162] The recording system described in Supplementary Note 1 further includes: a shooting feasibility determination unit, used to determine whether the shooting of the target has been successful based on the second image data.

[0163] (Supplementary Note 3)

[0164] The recording system described in Supplementary Note 2 further includes a control unit for controlling the moving body based on the determination result of the shooting feasibility assessment unit, wherein...

[0165] If the feasibility assessment unit determines that the shooting of the target has been successful, the control unit will control the moving object to leave the target space.

[0166] If the feasibility assessment unit determines that the shooting of the target has not been successful, the identification conditions are reset and the control unit controls the moving body to shoot the target again.

[0167] (Supplementary Note 4)

[0168] According to the recording system described in Supplementary Note 3, if the shooting feasibility determination unit determines that the shooting of the target has not been successful, the control unit controls the moving body to leave the target space after a predetermined time has elapsed since the shooting of the target began.

[0169] (Supplementary Note 5)

[0170] The recording system described in Supplementary Note 3 or 4 further includes a proximity detection unit for detecting that another moving object is approaching a moving object that has already photographed the target.

[0171] In the case where the shooting feasibility determination unit determines that the shooting of the target has not been successful, the control unit controls the moving body that has already shot the target to leave the target space after the proximity detection unit detects that another moving body is approaching, so that the other moving body and the moving body that has already shot the target do not interfere with each other.

[0172] (Supplementary Note 6)

[0173] According to the recording system described in Supplementary Note 1 or 2, wherein

[0174] The first image data includes multiple shooting targets, and

[0175] The target designation unit creates a planned path for the target to be captured from the first image data based on the identification conditions.

[0176] (Supplementary Note 7)

[0177] According to the recording system described in Supplementary Note 1 or 2, the condition setting unit sets identification conditions based on the location of the target space and the date and time when the first image data was captured.

[0178] (Supplementary Note 8)

[0179] The recording system described in Supplementary Note 1 or 2 also includes a weather information acquisition unit for collecting weather information.

[0180] The condition setting unit also sets identification conditions based on weather information of the date and time when the first image data was taken.

[0181] (Supplementary Note 9)

[0182] According to the recording system described in Supplementary Note 1 or 2, the position / attitude determination unit uses a trained model to determine the position / attitude of the moving object. The trained model has learned to determine the position / attitude of the moving object using identification conditions and first image data including the target being captured as input.

[0183] (Supplementary Note 10)

[0184] The recording system described in Supplementary Note 1 or 2 further includes a shooting condition setting unit for setting shooting conditions for shooting second image data based on identification conditions.

[0185] (Supplementary Note 11)

[0186] According to the recording system described in Supplementary Note 1 or 2, the moving body is an autonomously flying object capable of autonomous flight.

[0187] (Supplementary Note 12)

[0188] A recording method executed by a computer, comprising:

[0189] Based on pre-registered location data, first image data is collected from a camera provided by a moving body that has moved to the target space;

[0190] Identification conditions for identifying the captured target are set based on at least one of the date and time when the first image data was captured and the location of the target space.

[0191] The target is specified from the first image data, and the position / orientation of the moving object relative to the target is determined based on the identification conditions to capture a second image including the target; and

[0192] Record the second image data of the target being photographed.

[0193] (Supplementary Note 13)

[0194] The recording method described in Supplementary Note 12 further includes determining whether the shooting of the target has been successful based on the second image data.

[0195] (Supplementary Note 14)

[0196] The recording method described in Supplementary Note 13 further includes:

[0197] Once it is determined that the photographing of the target has been successful, control is applied to cause the moving object to leave the target space; and

[0198] If it is determined that the shooting of the target has not been successful, the recognition conditions are reset and control is applied so that the moving body can shoot the target again.

[0199] (Supplementary Note 15)

[0200] The recording method described in Supplementary Note 14 further includes: if it is determined that the shooting of the target has not been successful, controlling the moving body to leave the target space after a predetermined time has elapsed since the start of the shooting of the target.

[0201] (Supplementary Note 16)

[0202] According to the recording method described in Supplementary Note 14 or 15, it further includes:

[0203] Detecting another moving object approaching a moving object that has already photographed the target, and

[0204] If it is determined that the shooting of the target has not been successful, control is performed to make the moving body that has been shooting the target leave the target space after detecting the approach of another moving body, so that the other moving body and the moving body that has been shooting the target do not interfere with each other.

[0205] (Supplementary Note 17)

[0206] According to the recording method described in Supplementary Note 12 or 13, wherein

[0207] The first image data includes multiple targets; and

[0208] Based on the identification criteria, a motion planning path for the target is created from the first image data.

[0209] (Supplementary Note 18)

[0210] The recording method described in Supplementary Note 12 or 13 further includes setting identification conditions based on the location of the target space and the date and time when the first image data was captured.

[0211] (Supplementary Note 19)

[0212] According to the recording method described in Supplementary Note 12 or 13, it further includes:

[0213] Collecting weather information; and

[0214] The identification criteria are set based on weather information from the date and time the first image data was taken.

[0215] (Supplementary Note 20)

[0216] The recording method described in Supplementary Note 12 or 13 further includes: using a trained model to determine the position / orientation of the moving object, the trained model having learned to determine the position / orientation of the moving object using identification conditions and first image data including the target being captured as input.

[0217] (Supplementary Note 21)

[0218] The recording method described in Supplementary Note 12 or 13 further includes setting shooting conditions for capturing second image data based on identification conditions.

[0219] (Supplementary Note 22)

[0220] According to the recording method described in Supplementary Note 12 or 13, the moving body is an autonomously flying object capable of autonomous flight.

[0221] (Supplementary note 23)

[0222] A recording program for causing a computer to perform the following processes:

[0223] Based on pre-registered location data, first image data is collected from a camera provided by a moving body that has moved to the target space;

[0224] Identification conditions for identifying the captured target are set based on at least one of the date and time when the first image data was captured and the location of the target space.

[0225] The target is specified from the first image data, and the position / orientation of the moving object relative to the target is determined based on the identification conditions to capture a second image including the target; and

[0226] Record the second image data of the target being photographed.

[0227] (Supplementary Note 24)

[0228] According to the recording procedure described in Supplementary Note 23, the computer further performs the following processing: determining whether the shooting of the target has been successful based on the second image data.

[0229] (Supplementary Note 25)

[0230] According to the recording procedure described in Supplementary Note 24, the computer further performs the following processing:

[0231] Once it is determined that the photographing of the target has been successful, control is applied to cause the moving object to leave the target space; and

[0232] If it is determined that the photographing of the target has not been successful, the recognition conditions are reset and control is applied to enable the moving body to attempt to photograph the target again.

[0233] (Supplementary Note 26)

[0234] According to the recording procedure described in Supplementary Note 24, the computer further performs the following processing:

[0235] If it is determined that the shooting of the target has not been successful, control is applied to make the moving body leave the target space after a predetermined time has elapsed since the start of the shooting of the target.

[0236] (Supplementary note 27)

[0237] According to the recording procedure described in Supplementary Note 25 or 26, the computer further performs the following processing:

[0238] Detecting another moving object approaching a moving object that has already photographed the target, and

[0239] If it is determined that the shooting of the target has not been successful, control is performed to make the moving body that has been shooting the target leave the target space after detecting the approach of another moving body, so that the other moving body and the moving body that has been shooting the target do not interfere with each other.

[0240] (Supplementary Note 28)

[0241] According to the recording procedure described in Supplementary Note 23 or 24,

[0242] The first image data includes multiple targets; and

[0243] Based on the identification criteria, a motion planning path for the target is created from the first image data.

[0244] (Supplementary Note 29)

[0245] According to the recording procedure described in Supplementary Note 23 or 24, the computer further performs the following processing:

[0246] The processing sets identification conditions based on the location of the target space and the date and time when the first image data was captured.

[0247] (Supplementary Note 30)

[0248] According to the recording procedure described in Supplementary Note 23 or 24, the computer further performs the following processing:

[0249] Collecting weather information; and

[0250] The identification criteria are set based on weather information from the date and time the first image data was taken.

[0251] (Supplementary Note 31)

[0252] According to the recording procedure described in Supplementary Note 23 or 24, the computer further performs the following processing:

[0253] A trained model is used to determine the position / attitude of a moving object. This trained model has learned to use identification conditions and first image data, including the target being photographed, as input to determine the position / attitude of the moving object.

[0254] (Supplementary note 32)

[0255] According to the recording procedure described in Supplementary Note 23 or 24, the computer further performs the following processing:

[0256] The shooting conditions for capturing second image data are set based on the identification conditions.

[0257] (Supplementary Note 33)

[0258] According to the recording procedure described in supplementary notes 23 or 24, the moving body is an autonomously flying object capable of autonomous flight.

[0259] This application is based on and claims the priority benefit of Japanese Patent Application No. 2023-049090, filed on March 24, 2023, the disclosure of which is incorporated herein by reference in its entirety.

[0260] Reference Symbol List

[0261] 10, 20, 40 recording system

[0262] 11 Image Data Acquisition Unit

[0263] 12 Condition Setting Unit

[0264] 13 Target Designation Units

[0265] 14 position / attitude determination units

[0266] 15 Recording Control Unit

[0267] 16 Weather Information Collection Units

[0268] 17 Shooting Condition Setting Unit

[0269] 30 Shooting Feasibility Assessment Unit

[0270] 31 control unit

[0271] 101, 102, 311 moving bodies

[0272] 111 drive unit

[0273] 112 Communication Unit

[0274] 113 imaging units

[0275] 114 Moving Body Control Unit

[0276] 115 location data storage units

[0277] 116 self-position estimation units

[0278] 201 Management Equipment

[0279] 211 Communication Unit

[0280] 212 Second Image Data Storage Unit

[0281] 300 First Image Data

[0282] 400 Second Image Data

[0283] 1201 Network Interface

[0284] 1202 processor

[0285] 1203 memory

[0286] Checkpoints CP1, CP11, CP12, CP13, and CP51

[0287] L1 movement path

[0288] LM1 learning model

[0289] LM2 trained model

[0290] T1 and T11 power transmission towers

[0291] T51 Radio Tower

[0292] TS1 target space

Claims

1. A recording system, comprising: An image data acquisition device is used to acquire first image data from a camera provided by a moving body that has moved to the target space, based on pre-registered location data. A condition setting device is used to set identification conditions for identifying the captured target based on at least one of the date and time when the first image data was captured and the location of the target space. A target designation device, the target designation device being used to designate the shooting target from the first image data; A position / attitude determination device, wherein the position / attitude determination device is used to determine the position / attitude of the moving body relative to the shooting target based on the identification conditions, so as to capture second image data including the shooting target; and A recording control device for recording the second image data.

2. The recording system according to claim 1, further comprising a shooting feasibility determination device, the shooting feasibility determination device being used to determine, based on the second image data, whether the shooting of the shooting target has been successful.

3. The recording system according to claim 2, further comprising a control device, the control device being used to control the moving body according to the determination result of the shooting feasibility determination device, wherein, If the shooting feasibility determination device determines that the shooting of the target has been successful, the control device controls the moving body to leave the target space. If the shooting feasibility determination device determines that the shooting of the target has not been successful, the identification conditions are reset, and the control device controls the moving body to shoot the target again.

4. The recording system according to claim 3, wherein if the shooting feasibility determination device determines that the shooting of the target has not been successful, the control device controls the moving body to leave the target space after a predetermined time has elapsed since the shooting of the target began.

5. The recording system according to claim 3 or 4, further comprising a proximity detection device for detecting that another moving object is approaching the moving object that has already photographed the target. in, If the feasibility determination device determines that the shooting of the target has not been successful, the control device controls the moving body that has already shot the target to leave the target space after the proximity detection device detects that the other moving body is approaching, so that the other moving body and the moving body that has already shot the target do not interfere with each other.

6. The recording system according to claim 1 or 2, wherein, The first image data includes multiple of the captured targets, and The target designation device creates a motion planning path for the shooting target from the first image data based on the identification conditions.

7. The recording system according to claim 1 or 2, further comprising a weather information acquisition device for collecting weather information. in, The condition setting device further sets the identification conditions based on weather information of the date and time when the first image data was captured.

8. The recording system according to claim 1 or 2, wherein, The position / attitude determination device uses a trained model to determine the position / attitude of the moving object. The trained model has learned to use the identification conditions and the first image data including the target being captured as input to determine the position / attitude of the moving object.

9. A recording method executed by a computer, comprising: Based on pre-registered location data, first image data is collected from a camera provided by a moving body that has moved to the target space; Identification conditions for identifying the captured target are set based on at least one of the date and time when the first image data was captured and the location of the target space. The target is specified from the first image data, and the position / orientation of the moving body relative to the target is determined according to the identification conditions, for capturing a second image including the target; and Record the second image data of the target being photographed.

10. The recording method according to claim 9, further comprising determining whether the shooting of the target has been successfully completed based on the second image data.

11. The recording method according to claim 10, further comprising: If it is determined that the shooting of the target has been successful, control is performed to make the moving body leave the target space; as well as If it is determined that the shooting of the target has not been successful, the identification conditions are reset, and the control is performed to make the moving body shoot the target again.

12. The recording method according to claim 11, further comprising, if it is determined that the shooting of the target has not been successful, controlling the moving body to leave the target space after a predetermined time has elapsed since the shooting of the target began.

13. The recording method according to claim 11 or 12, further comprising: Detecting another moving object approaching the moving object that has already photographed the target; as well as If it is determined that the shooting of the target has not been successful, control is performed to make the moving body that has already shot the target leave the target space after detecting the approach of the other moving body, so that the other moving body and the moving body that has already shot the target do not interfere with each other.

14. The recording method according to claim 9 or 10, wherein, The first image data includes multiple of the captured targets, and Based on the identification conditions, a motion planning path for the shooting target is created from the first image data.

15. A recording program for causing a computer to perform the following processes: Based on pre-registered location data, first image data is collected from a camera provided by a moving body that has moved to the target space; Identification conditions for identifying the captured target are set based on at least one of the date and time when the first image data was captured and the location of the target space. The target is specified from the first image data, and the position / orientation of the moving body relative to the target is determined according to the identification conditions, for capturing a second image including the target; and Record the second image data of the target being photographed.

16. The recording procedure according to claim 15, further comprising the computer performing the following process: determining, based on the second image data, whether the capture of the target has been successful.

17. The recording procedure according to claim 16, further comprising the computer performing the following processes: If it is determined that the photographing of the target has been successful, control is applied to cause the moving body to leave the target space; and If it is determined that the shooting of the target has not been successful, the identification conditions are reset, and the control is performed to make the moving body shoot the target again.

18. The recording procedure according to claim 17, further comprising the computer performing the following process: if it is determined that the photographing of the target has not been successful, controlling the moving body to leave the target space after a predetermined time has elapsed since the start of the photographing of the target.

19. The recording procedure according to claim 17 or 18, further comprising the computer performing the following processing: Detecting another moving object approaching the moving object that has already photographed the target; and If it is determined that the shooting of the target has not been successful, control is performed to make the moving body that has already shot the target leave the target space after detecting the approach of the other moving body, so that the other moving body and the moving body that has already shot the target do not interfere with each other.

20. The recording procedure according to claim 15 or 16, wherein, The first image data includes multiple of the captured targets, and Based on the identification conditions, a motion planning path for the shooting target is created from the first image data.

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