Information processing device, information processing method, and program

Abstract

The present disclosure pertains to an information processing device, an information processing method, and a program making it possible to shorten the length of time needed for surveying. With respect to a surveying area to be surveyed, a complexity determination unit determines the complexity of a region that is the subject in surveying images acquired in a temporally continuous manner from an unmanned aerial vehicle. An overlap rate setting unit sets the rate of overlap among surveying images on the basis of the complexity. The features as in the present disclosure can be applied, for example, to surveying systems using a drone.

Description

Information processing device, information processing method, and program

[0001] The present disclosure relates to an information processing device, an information processing method, and a program, and more particularly to an information processing device, an information processing method, and a program that enable the time required for surveying to be reduced.

[0002] In recent years, remotely controlled unmanned aerial vehicles (drones) have been used for various purposes, such as aerial photography and surveying. The flight path of the unmanned aerial vehicle can be determined according to a user's request. For example, Patent Literature 1 discloses a flight support device that determines the flight path of the aircraft so as to satisfy requirements related to observations by sensors mounted on the aircraft.

[0003] Conventionally, the flight path of a drone when conducting surveying has been set manually based on map information, and the overlap rate of the images obtained by shooting (shooting interval and flight speed) has also been set manually.

[0004] Japanese Patent Application Laid-Open No. 2022-167127

[0005] To create precise 3D point cloud data through surveying, it is necessary to take photographs with a high overlap rate in areas where feature points are difficult to find. However, a high overlap rate increases flight time, which increases the time required for surveying.

[0006] The present disclosure has been made in consideration of such circumstances, and aims to shorten the time required for surveying.

[0007] The information processing device disclosed herein is an information processing device that includes a complexity determination unit that determines the complexity of the area that is the subject of survey images acquired continuously over time from an unmanned aerial vehicle for a survey area to be surveyed, and an overlap rate setting unit that sets the overlap rate between the survey images based on the complexity.

[0008] The information processing method disclosed herein is an information processing method in which an information processing device determines the complexity of the areas that are the subject of survey images acquired continuously over time from an unmanned aerial vehicle for a survey area to be surveyed, and sets the overlap rate between the survey images based on the complexity.

[0009] The program disclosed herein is a program for causing a computer to execute a process of determining the complexity of the areas that are the subject of survey images acquired continuously over time from an unmanned aerial vehicle for a survey area to be surveyed, and setting the overlap rate between the survey images based on the complexity.

[0010] In the present disclosure, the complexity of the areas that are the subject of survey images acquired continuously over time from an unmanned aerial vehicle for a survey area to be surveyed is determined, and the overlap rate between the survey images is set based on the complexity.

[0011] 1 is a diagram illustrating an example of overlap rates and flight paths according to conventional technology. FIG. 2 is a diagram illustrating an example of overlap rates and flight paths according to technology related to the present disclosure. FIG. 3 is a diagram illustrating an example configuration of a surveying system to which technology related to the present disclosure is applied. FIG. 4 is a block diagram illustrating an example functional configuration of a flight plan determination device. FIG. 5 is a flowchart illustrating the operation of a flight plan determination device. FIG. 6 is a flowchart illustrating an example of surveying processing. FIG. 7 is a diagram illustrating division of a surveying area. FIG. 8 is a flowchart illustrating details of complexity determination processing. FIG. 9 is a diagram illustrating an example of the number of pixels of an area corresponding to a surveying image in a surveying area. FIG. 10 is a flowchart illustrating details of overlap rate and flight path setting processing. FIG. 11 is a diagram illustrating an example of complexity search. FIG. 12 is a diagram illustrating an example of complexity search. FIG. 13 is a diagram illustrating an example of complexity search. FIG. 14 is a diagram illustrating setting of a direction of travel based on the continuity of complexity. FIG. 15 is a diagram illustrating an example of setting an adjacent course. FIG. 16 is a diagram illustrating an example of setting an adjacent course. FIG. 17 is a diagram illustrating an example hardware configuration of a computer.

[0012] The following describes modes for carrying out the technology according to the present disclosure (hereinafter referred to as embodiments). The description will be made in the following order.

[0013] 1. Problems with the prior art and an overview of the technology according to the present disclosure 2. Configuration of a surveying system to which the technology according to the present disclosure is applied 3. Configuration and operation of a flight plan determination device 4. Examples of surveying processing in a surveying system 5. Modified examples and application examples 6. Example computer hardware configurations

[0014] 1. Problems with the Related Art and Overview of the Technology Relating to the Present Disclosure In recent years, remotely controlled unmanned aerial vehicles (drones) have been used for various purposes, such as aerial photography, surveying, etc. The flight path of an unmanned aerial vehicle can be determined in response to a user's request.

[0015] As shown in Figure 1, conventionally, the flight path FP of a drone used in surveying is manually set based on map information, etc. Furthermore, the overlap rate (shooting interval and flight speed) of images obtained by photography is also manually set to a fixed value before the start of the survey. For example, in aerial photogrammetry using a drone, the standard overlap rate, which represents the amount of overlap between images captured in the direction of travel (course), is 60% or more, and the standard side overlap rate, which represents the amount of overlap between images captured in adjacent courses in the direction of travel, is 30% or more.

[0016] To create precise 3D point cloud data through surveying, it is necessary to take images with a high overlap rate in areas where feature points are difficult to find. However, increasing the overlap rate increases flight time and the time required for surveying. In addition, the number of images taken increases, which increases the amount of image data and the time required for image processing.

[0017] In contrast, in the technology disclosed herein, the complexity representing the complexity of the subject is determined for the survey area to be surveyed, and the overlap rate is set to be high or low based on that complexity.

[0018] Specifically, as shown in Figure 2, in areas with low complexity, i.e., areas where it is difficult to find feature points, the overlap rate is set high, and in areas with high complexity, i.e., areas where it is easy to find feature points, the overlap rate is set low. In addition, the drone flight path FP is automatically set so that the direction of travel is a course with a succession of equal complexity.

[0019] This allows the overlap rate to be set appropriately according to the complexity, so the flight time can be shortened without increasing the overlap rate more than necessary, thereby reducing the time required for surveying.

[0020] 2. Configuration of a Surveying System to which the Technology According to the Present Disclosure is Applied> FIG. 3 is a diagram showing an example of the configuration of a surveying system to which the technology according to the present disclosure is applied.

[0021] The surveying system 1 in Figure 3 is composed of a drone 10, an edge device 20, and a tablet terminal 30.

[0022] The drone 10 is an unmanned aerial vehicle according to the present disclosure, and flies according to a predetermined flight plan. The drone 10 is equipped with various sensors, such as a global positioning system (GPS) sensor, an inertial measurement unit (IMU), a barometer, and a light detection and ranging (LiDAR), as well as a camera 11. The camera 11 captures survey images of a survey area (the earth's surface) to be surveyed as a subject under the control of a computer (not shown) equipped in the drone. The camera 11 may also be configured to capture survey images based on the control of, for example, an internal processor, rather than under the control of a computer equipped in the drone. The survey images captured by the camera 11 are assumed to be still images captured continuously over time, but may also be moving images.

[0023] The edge device 20 is configured by a cloud server provided on the cloud, a general-purpose computer such as a PC (Personal Computer), etc. The edge device 20 generates various data such as a 3D point cloud, an orthoimage, and a DEM (Digital Elevation Model) based on the measurement images captured by the camera 11 mounted on the drone 10.

[0024] The tablet terminal 30 is operated by a user who pilots and controls the drone 10. A smartphone or a desktop PC may be provided instead of the tablet terminal 30. The tablet terminal 30 presents the user with a UI for operating the drone 10 and displays various data generated by the edge device 20. The tablet terminal 30 can also accept input and editing of a flight plan supplied to the drone 10 from the edge device 20.

[0025] In the surveying system 1 to which the technology disclosed herein is applied, the overlap rate is set based on the complexity determined for the surveying area to be surveyed, thereby reducing the time required for surveying.

[0026] 3. Configuration and Operation of Flight Plan Determination Device The configuration and operation of a flight plan determination device, which is an embodiment of an information processing device according to the present disclosure, will be described.

[0027] (Example of Functional Configuration of Flight Plan Determination Device) FIG. 4 is a block diagram showing an example of the functional configuration of the flight plan determination device.

[0028] 4 may be realized by any of the drone 10, edge device 20, and tablet terminal 30 that constitute the surveying system 1. For example, each functional block of the flight plan determination device 100 described below may be realized entirely by the edge device 20, or may be realized by sharing between the edge device 20 and the tablet terminal 30. Furthermore, each functional block of the flight plan determination device 100 may be realized entirely by the tablet terminal 30. In this case, the surveying system 1 may be configured only by the drone 10 and the tablet terminal 30.

[0029] Each functional block shown in FIG. 4 is realized by the information processing device constituting the flight plan determination device 100 executing a predetermined program.

[0030] The flight plan determination device 100 is configured to include a determination information acquisition unit 111 , a complexity determination unit 112 , an overlap rate setting unit 113 , a flight path setting unit 114 , and a flight plan determination unit 115 .

[0031] The determination information acquisition unit 111 acquires determination information used for determining complexity by the complexity determination unit 112 from external information supplied from the outside and internal information held internally. The external information may include an overall image, which will be described later, and the internal information may include map information, which will be described later. The acquired determination information is supplied to the complexity determination unit 112.

[0032] The complexity determination unit 112 uses the determination information from the determination information acquisition unit 111 to determine the complexity of the areas that will be the subject of the measurement images acquired continuously over time from the drone 10 for the measurement area to be measured. The complexity can also be considered an index that indicates the difficulty of finding feature points for each area (area that will be the subject of the measurement images) within the measurement area. The complexity determined for each area is supplied to the overlap rate setting unit 113 and the flight path setting unit 114.

[0033] The overlap rate setting unit 113 sets the overlap rate between the survey images acquired successively in time from the drone 10 based on the complexity of each region within the measurement area determined by the complexity determination unit 112 .

[0034] The flight path setting unit 114 sets the flight path (direction of travel) of the drone 10 based on the complexity of each region within the measurement area determined by the complexity determination unit 112.

[0035] The flight plan determination unit 115 determines a flight plan for the drone 10 based on the overlap rate set by the overlap rate setting unit 113 and the flight path set by the flight path setting unit 114. The determined flight plan is supplied to the drone 10.

[0036] (Operation of Flight Plan Determination Apparatus) The operation of the flight plan determination apparatus 100 of FIG. 4 will be described with reference to the flowchart of FIG.

[0037] In step S111, the determination information acquisition unit 111 acquires determination information used by the complexity determination unit 112 to determine the complexity. For example, the determination information acquisition unit 111 acquires an overall image of the entire survey area as the determination information. The overall image may be captured by the drone 10 (camera 11) immediately before the survey is performed, or may be captured in advance by another drone. The determination information acquisition unit 111 may also acquire map information of the entire survey area as the determination information.

[0038] In step S112, the complexity determination unit 112 determines the complexity of the measurement area using the determination information acquired by the determination information acquisition unit 111.

[0039] If the judgment information is an overall image in which the entire survey area is photographed, the complexity judgment unit 112 judges the complexity based on the degree of variation in pixel values ​​(color and brightness values) corresponding to the acquisition range in which the survey image is acquired in the overall image.

[0040] Furthermore, when the determination information is an overall image of the entire measurement area, the complexity determination unit 112 may determine the complexity based on classification information for each pixel included in the overall image. In this case, the complexity determination unit 112 determines the complexity using, as classification information, subject attributes (labels or categories) assigned to each pixel of the overall image by semantic segmentation using deep learning.

[0041] Furthermore, when the determination information is map information of the entire survey area, the complexity determination unit 112 may determine the complexity based on land use information included in the map information.

[0042] In step S113, the overlap rate setting unit 113 sets an overlap rate between the survey images based on the complexity determined by the complexity determination unit 112. The overlap rate set by the overlap rate setting unit 113 may be both the overlap rate on the flight path (in the direction of travel) of the drone 10 and the side overlap rate between flight paths (between adjacent courses), or may be only the overlap rate.

[0043] The survey images acquired continuously over time from the drone 10 may be camera images (RGB images). In this case, the overlap rate setting unit 113 sets the overlap rate higher as the complexity decreases, and sets the overlap rate lower as the complexity increases.

[0044] Furthermore, the survey images acquired continuously over time from the drone 10 may be distance images acquired by a distance sensor such as a LiDAR. In this case, the overlap rate setting unit 113 sets the overlap rate lower as the complexity decreases, and sets the overlap rate higher as the complexity increases.

[0045] In step S114, the flight path setting unit 114 sets a flight path for the drone 10 based on the complexity determined by the complexity determination unit 112. Specifically, the flight path setting unit 114 sets the flight path for the drone 10 so that the direction of travel is a course through which areas of the same complexity continue throughout the entire survey area.

[0046] In step S115, the flight plan determination unit 115 determines a flight plan including the flight speed and acquisition interval of the drone 10 by adjusting the flight speed and acquisition interval of the survey image based on the overlap rate set by the overlap rate setting unit 113.

[0047] Then, the drone 10 performs flight and photographing based on the flight plan determined by the flight plan determination unit 115, thereby achieving surveying of the entire survey area.

[0048] According to the above process, the overlap rate is set appropriately according to the complexity, so the flight time of the drone 10 can be shortened without increasing the overlap rate more than necessary, thereby shortening the time required for surveying. Furthermore, because the flight time of the drone 10 can be shortened, it is possible to reduce battery consumption of the drone 10 and reduce the number of flights of the drone 10.

[0049] Furthermore, since the duplication rate is appropriately set according to the complexity, it is possible to reduce the number of images taken and the amount of image data, which in turn makes it possible to reduce the storage capacity of the memory card of the camera 11 and shorten the time required to transfer data from the drone 10 to the edge device 20.

[0050] Furthermore, since images according to the degree of complexity can be obtained, the calculation time required to create 3D point cloud data can be reduced, and the accuracy of point cloud position information can be improved compared to creating 3D point cloud data using the same amount of data.

[0051] 6, an example of the surveying process executed in the surveying system 1 will be described. In the surveying process of Fig. 6, an overall image of the entire survey area is acquired as the determination information, and the overall image is taken by the camera 11 of the drone 10 immediately before the surveying by the drone 10 is executed.

[0052] In step S131, the edge device 20 determines the number of divisions into which the entire survey area is divided. Here, the number of divisions into which the entire survey area is divided refers to the number of times that the camera 11 of the drone 10 needs to capture an image of the entire survey area.

[0053] The number of divisions into the entire survey area is determined by four parameters: the area of ​​the entire survey area, the angle of view of the camera 11, the resolution of the camera 11, and the altitude at which the drone 10 can fly. These parameters may be obtained from the drone 10 or may be input into the tablet terminal 30 by the user.

[0054] That is, the larger the area of ​​the entire survey area, the larger the number of divisions of the entire survey area, and the smaller the angle of view of the camera 11, the larger the number of divisions of the entire survey area. Also, the lower the resolution of the camera 11, the larger the number of divisions of the entire survey area, and the lower the altitude at which the drone 10 can fly, the larger the number of divisions of the entire survey area.

[0055] Here, the area of ​​the entire survey area is 200m x 100m (= 20,000m２ ), the angle of view of the camera 11 is 60°, and the resolution of the camera 11 is 4000×2000 pixels.

[0056] In this case, as shown in the left diagram of Figure 7, when the drone 10 can fly at an altitude of 174 m or more, the camera 11 can photograph the entire survey area in one go. In other words, there is no need to divide the entire survey area.

[0057] However, there is generally a limit to the altitude at which the drone 10 can fly. For example, in a situation where the altitude at which the drone 10 can fly is limited to 90 m, as shown in the right diagram of Figure 7, the drone 10 flies at an altitude of 87 m, and the camera 11 captures the entire survey area four times. In other words, the number of divisions for the entire survey area is four.

[0058] In the following description, it is assumed that the entire survey area is photographed by photographing each of the four divided sections.

[0059] That is, in step S132, the drone 10 (camera 11) photographs each of the four divided sections. The overall image of the entire survey area photographed by photographing each of the four divided sections is transferred from the drone 10 (camera 11) to the edge device 20 (flight plan determination device 100).

[0060] Thereafter, in step S133, the determination information acquisition unit 111 and the complexity determination unit 112 execute the complexity determination process by using the overall image in which the entire measurement area is photographed.

[0061] (Details of Complexity Determination Process) Here, with reference to the flowchart of FIG. 8, the complexity determination process executed in step S133 of FIG. 6 will be described in detail.

[0062] In step S151, the determination information acquisition unit 111 performs noise removal and image reduction on the entire image of the entire measurement area. This noise removal and image reduction may be performed as needed.

[0063] In step S152, the complexity determination unit 112 calculates the number of pixels in an area A in the entire image that corresponds to the measurement image (the acquisition range in which the measurement image is acquired).

[0064] As shown in Figure 9, the area of ​​the entire survey area Sa is 200m x 100m (= 20,000m ２ , the resolution of the camera 11 is 2000 × 1000 pixels, and the number of divided sections of the entire survey area is 4. In this case, the area of ​​one divided section shown by a thick frame in FIG. 9 is 100 m × 50 m (= 5000 m ２ ) corresponds to 2000 x 1000 pixels.

[0065] In this case, if the area of ​​area A corresponding to the shooting range (acquisition range) per survey image captured by camera 11 is 4m x 2m, the number of pixels in area A relative to the entire survey area will be 80 x 40 pixels (3200 pixels).

[0066] Returning to the flowchart of FIG. 8, in step S153, the complexity determination unit 112 calculates the average value of pixel values ​​(specifically, color or brightness values) in area A (3200 pixels).

[0067] In step S154, the complexity determination unit 112 calculates the absolute value (absolute deviation) of the difference between the calculated average value of the pixel values ​​and each pixel value (of the 3200 pixels).

[0068] In step S155, the complexity determination unit 112 calculates the sum of the calculated absolute values ​​(for 3200 pixels). The calculated sum approaches 0 as the variation in pixel values ​​within area A decreases, and increases as the variation increases.

[0069] In step S156, the complexity determination unit 112 determines the complexity of region A based on the determined total value. For example, the complexity determination unit 112 classifies the total value into N levels of complexity according to its magnitude. That is, if the total value for region A is 0, the complexity of that region is the lowest.

[0070] Thereafter, in step S157, the complexity determining unit 112 determines whether the complexity has been calculated for the entire survey area.

[0071] If it is determined in step S157 that the complexity has not been calculated for the entire measurement area, the complexity determination unit 112 sets a new area A by moving area A within the entire measurement area (whole image), and the process returns to step S153. That is, steps S153 to S156 are repeated for the newly set area A, thereby calculating the complexity of the area.

[0072] If it is determined in step S157 that the complexity has been calculated for the entire survey area, the complexity determination process ends and the process returns to step S133 in FIG.

[0073] 9, a 50 x 50 area A (80 x 40 pixels) is set in the survey area Sa (4000 x 2000 pixels), and 50 x 50 complexities are calculated. When moving area A within the entire survey area, it may be moved so that a portion of the 80 x 40 pixel range overlaps, or it may be moved intermittently (discretely) at intervals of a predetermined number of pixels, in addition to being moved continuously within the 80 x 40 pixel range.

[0074] After step S133, in step S134, the overlap rate setting unit 113 and the flight path setting unit 114 execute the overlap rate and flight path setting process based on the complexity calculated for the entire survey area.

[0075] (Details of Overlap Rate and Flight Route Setting Process) Here, with reference to the flowchart of FIG. 10, the details of the overlap rate and flight route setting process executed in step S134 of FIG. 6 will be described.

[0076] In step S171, the flight path setting unit 114 calculates the continuity, which indicates the degree to which the same complexity continues, by searching the complexity obtained for the entire survey area in a single stroke in a predetermined direction.

[0077] First, the flight path planning unit 114 calculates the continuity of complexity by searching the 50 x 50 complexities CP obtained for the entire survey area Sa along a search path SP1 that scans back and forth while shifting the course horizontally, as shown in Figure 11. In the following examples, it is assumed that three levels of complexity CP are obtained, with dark (black) areas having a high complexity CP, slightly dark (gray) areas having a medium complexity CP, and light (light gray) areas having a low complexity CP.

[0078] Next, as shown in Figure 12, the flight path setting unit 114 calculates the continuity of complexity by searching for the 50 x 50 complexities CP obtained for the entire survey area Sa using a search path SP2 that vertically scans back and forth while shifting the course.

[0079] Furthermore, as shown in Figure 13, the flight path setting unit 114 calculates the continuity of complexity by searching for the 50 x 50 complexities CP obtained for the entire survey area Sa using a search path SP3 that scans in a rectangular spiral from the center of the survey area toward the outer periphery.

[0080] In addition, as shown in Figure 14, the flight path setting unit 114 calculates the continuity of complexity by searching for the 50 x 50 complexities CP obtained for the entire survey area Sa using search paths SP11, SP12, SP13, etc. that scan in different directions for each of the four divided sections.

[0081] In addition, the search path for searching the complexity CP obtained for the entire survey area is not limited to those described in Figures 11 to 14, and may be a search path that searches and scans in any direction as long as the continuity of complexity can be calculated.

[0082] 10 , in step S172, the flight path setting unit 114 sets a direction with a high continuity of low complexity as the direction of travel. At this time, the direction of travel is not limited to a direction with a high continuity of low complexity, but may also be a direction with a high continuity of medium complexity or a direction with a high continuity of high complexity.

[0083] For example, when the complexity CP shown in Figure 15A is required for a survey area, areas of low complexity (light colored areas), medium complexity (slightly dark colored areas), and high complexity (dark colored areas) are continuous vertically, so the vertical continuity is high and this vertical direction is set as the direction of travel.

[0084] Furthermore, when the complexity CP shown in Figure 15B is required for the survey area, areas of low complexity (light color), medium complexity (slightly dark color), and high complexity (dark color) are continuous horizontally, so the horizontal continuity is high and this horizontal direction is set as the direction of travel.

[0085] In this way, the direction of the flight path is set.

[0086] In step S173, the overlap rate setting unit 113 converts the complexity calculated for the entire survey area into a weighting factor for the overlap rate (overlap rate in the direction of travel). Specifically, a low complexity is converted into a large weighting factor, and a high complexity is converted into a small weighting factor.

[0087] In step S174, the flight path setting unit 114 sets the route of the adjacent course according to the complexity of the adjacent course to the complexity of the set flight direction.

[0088] For example, as shown in Figure 16, if the travel direction is set from top to bottom as indicated by the solid arrow for the survey area for which the complexity CP is being calculated, the adjacent course AC that will be the travel direction after the turnaround has low complexity in the adjacent section d1. Therefore, the adjacent course AC in section d1 is set to a route that is shifted so that the side lap rate with respect to the travel direction before the turnaround (solid arrow) is large.

[0089] In the adjacent course AC, the adjacent sections d2 have medium complexity. Therefore, the adjacent course AC in section d2 is set to a route that is offset so that the side lap ratio with respect to the traveling direction before the turnaround (solid arrow) is small.

[0090] As explained with reference to Figure 16, by shifting the route of adjacent course AC depending on the complexity, the accuracy of the survey can be improved, but the survey time increases. Therefore, if reducing the time required for the survey is a priority, it is also possible to set a straight route for adjacent course AC regardless of the complexity, as shown in Figure 17.

[0091] Then, in step S175, the overlap rate setting unit 113 sets the overlap rate by weighting the reference overlap rate (reference overlap rate) in the traveling direction based on the weighting amount into which the complexity has been converted. The reference overlap rate can be set by, for example, being input by the user into the tablet terminal 30.

[0092] Once the overlap rate (overlap rate, side lap rate) and flight path (direction of travel, route of adjacent course) have been set in this manner, the process returns to step S134 in FIG.

[0093] After step S134, in step S135, the flight plan determination unit 115 determines a flight plan including the flight speed and acquisition interval of the drone 10 by adjusting the flight speed and acquisition interval of the survey image based on the overlap rate set by the overlap rate setting unit 113. The flight plan also includes the flight path set by the flight path setting unit 114.

[0094] For example, the flight plan determination unit 115 may determine a flight plan in which the flight speed is constant and the acquisition interval of the survey images is changed depending on the overlap rate. In this case, the survey images themselves are stable, and good survey results can be obtained.

[0095] The flight plan determination unit 115 may also determine a flight plan in which the acquisition interval of the survey images is constant and the flight speed is changed according to the overlap rate. If the camera 11 of the drone 10 is a camera dedicated to video images with a fixed frame rate such as 24p, it is desirable to change the flight speed.

[0096] Furthermore, if the angle of view of the camera 11 is fixed, the flight speed of the drone 10 and the interval at which survey images are acquired may be adjusted according to the flight altitude of the drone 10.

[0097] The flight plan determined in this manner is supplied to the drone 10.

[0098] Then, in step S136, the drone 10 performs flight and photographing based on the determined flight plan. That is, the drone 10 performs surveying of the entire survey area.

[0099] According to the above processing, the overlap rate is set appropriately according to the degree of complexity, so that the flight time of the drone 10 can be shortened without increasing the overlap rate more than necessary, thereby shortening the time required for surveying.

[0100] 5. Modifications and Applications Modifications and applications of the above-described embodiment will be described.

[0101] (Modification) In the surveying process described with reference to the flowchart in Fig. 6, the overall image is taken by the camera 11 of the drone 10 immediately before the surveying is performed by the drone 10. However, this is not limiting, and an aerial photograph or satellite photograph of an area including the surveying area taken in advance may be used as the overall image.

[0102] As mentioned above, when the survey area is wide or the camera resolution is low, instead of photographing the entire survey area in one go, multiple images taken for each divided section may be joined together.

[0103] In the above, in determining the flight plan, the flight speed of the drone 10 is kept constant and the acquisition interval of the survey images is changed according to the overlap rate, or the acquisition interval of the survey images is kept constant and the flight speed of the drone 10 is changed according to the overlap rate. However, it is also possible to realize photography according to the overlap rate by changing only the flight altitude of the drone 10 and keeping the flight speed of the drone 10 and the acquisition interval of the survey images constant.

[0104] When the survey images are camera images, the overlap rate is set higher as the complexity decreases, and lower as the complexity increases. In other words, areas with low complexity are photographed more often, and areas with high complexity are photographed less.

[0105] On the other hand, if the survey image is a distance image acquired by a distance sensor such as LiDAR, the overlap rate is set lower as the complexity decreases, and higher as the complexity increases. That is, there are fewer distance measurements in areas with low complexity, and more distance measurements in areas with high complexity.

[0106] (Application Example) The technology according to the present disclosure can be applied not only to surveying in a surveying system that performs aerial photogrammetry using an unmanned aerial vehicle, but also to a photography system that takes high-resolution, wide-area aerial photographs.

[0107] 6. Example of Computer Hardware Configuration The above-described series of processes can be executed by hardware or software. When the series of processes is executed by software, the program constituting the software is installed from a program recording medium into a computer incorporated in dedicated hardware, a general-purpose personal computer, or the like.

[0108] FIG. 18 is a block diagram showing an example of the hardware configuration of a computer that executes the above-described series of processes by a program.

[0109] The flight plan determination device 100 to which the technology according to the present disclosure can be applied is realized by a computer 300 having the configuration shown in FIG.

[0110] A CPU (Central Processing Unit) 301 , a ROM (Read Only Memory) 302 , and a RAM (Random Access Memory) 303 are interconnected by a bus 304 .

[0111] An input / output interface 305 is also connected to the bus 304. An input unit 306 including a keyboard, a mouse, etc., and an output unit 307 including a display, a speaker, etc. are connected to the input / output interface 305. In addition, a storage unit 308 including a hard disk, an SSD (Solid State Drive), a non-volatile memory, etc., a communication unit 309 including a network interface, etc., and a drive 310 that drives removable media 311 are also connected to the input / output interface 305.

[0112] In a computer configured as described above, the CPU 301 loads a program stored in the storage unit 308 into the RAM 303 via the input / output interface 305 and the bus 304 and executes the program, thereby performing the above-described series of processes.

[0113] The program executed by the CPU 301 is provided, for example, by being recorded on a removable medium 311 or via a wired or wireless transmission medium such as a local area network, the Internet, or digital broadcasting, and is installed in the storage unit 308 .

[0114] The program executed by the computer may be a program that processes in chronological order according to the order described in this specification, or may be a program that processes in parallel or at the required timing, such as when called.

[0115] The embodiments according to the present disclosure are not limited to the above-described embodiments, and various modifications are possible within the scope of the gist of the present disclosure.

[0116] For example, an embodiment according to the present disclosure can be configured as a cloud computing system in which a single function is shared and processed collaboratively by a plurality of devices via a network.

[0117] Furthermore, each step described in the above flowchart can be executed by one device, or can be shared and executed by a plurality of devices.

[0118] Furthermore, when one step includes multiple processes, the multiple processes included in that one step can be executed by one device or can be shared and executed by multiple devices.

[0119] Furthermore, the effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0120] Furthermore, the present disclosure may have the following configurations. (1) An information processing device including: a complexity determination unit that determines the complexity of an area that is a subject of measurement images acquired continuously over time from an unmanned aerial vehicle for a measurement area to be measured; and an overlap rate setting unit that sets an overlap rate between the measurement images based on the complexity. (2) The information processing device described in (1), in which the complexity determination unit determines the complexity using an overall image capturing the entire measurement area. (3) The information processing device described in (2), in which the complexity determination unit determines the complexity based on a degree of variation in pixel values ​​corresponding to an acquisition range in the overall image from which the measurement images are acquired. (4) The information processing device described in (3), in which the pixel values ​​include at least one of color and luminance. (5) The information processing device described in (2), in which the complexity determination unit determines the complexity based on classification information for each pixel included in the overall image. (6) The information processing device described in (1), in which the complexity determination unit determines the complexity using map information of the entire measurement area. (7) The information processing device according to any one of (1) to (6), wherein the overlap rate setting unit sets an overlap rate on the flight path of the unmanned aerial vehicle and a side lap rate between the flight paths as the overlap rate. (8) The information processing device according to any one of (1) to (7), wherein the overlap rate setting unit sets the overlap rate by weighting a reference overlap rate according to the complexity. (9) The information processing device according to any one of (1) to (8), further comprising a flight path setting unit that sets the flight path of the unmanned aerial vehicle based on the complexity. (10) The information processing device according to (9), wherein the flight path setting unit sets the flight path by calculating a continuity of the complexity over the entire survey area. (11) The information processing device according to (10), wherein the flight path setting unit calculates the continuity of the complexity by searching for the complexity over the entire survey area in a single stroke in a predetermined direction. (12) The information processing device according to (10) or (11), wherein the flight path setting unit sets a direction in which the degree of continuity of the complexity is high as a traveling direction of the flight path.(13) The information processing device according to (12), wherein the flight path setting unit sets adjacent courses of the flight path according to the complexity adjacent to the complexity of the direction of travel. (14) The information processing device according to any of (9) to (13), further comprising a flight plan determination unit that determines a flight plan including a flight speed of the unmanned aerial vehicle and an acquisition interval of the survey images based on the set overlap rate. (15) The information processing device according to (14), wherein the flight plan determination unit determines the flight plan in which the flight speed is constant and the acquisition interval is changed according to the overlap rate. (16) The information processing device according to (14), wherein the flight plan determination unit determines the flight plan in which the acquisition interval is constant and the flight speed is changed according to the overlap rate. (17) The information processing device according to any of (1) to (16), wherein the survey images are camera images, and the overlap rate setting unit sets the overlap rate higher as the complexity is smaller. (18) The information processing device according to any one of (1) to (16), wherein the measurement images are distance images, and the overlap rate setting unit sets the overlap rate higher as the complexity increases. (19) An information processing method, wherein an information processing device determines the complexity of an area that will be the subject of measurement images acquired successively over time from an unmanned aerial vehicle for a measurement area to be measured, and sets the overlap rate between the measurement images based on the complexity. (20) A program for causing a computer to execute a process of determining the complexity of an area that will be the subject of measurement images acquired successively over time from an unmanned aerial vehicle for a measurement area to be measured, and sets the overlap rate between the measurement images based on the complexity.

[0121] REFERENCE SIGNS LIST 1 Surveying system, 10 Drone, 11 Camera, 20 Edge device, 30 Tablet terminal, 100 Flight plan determination device, 111 Judgment information acquisition unit, 112 Complexity judgment unit, 113 Overlap rate setting unit, 114 Flight path setting unit, 115 Flight plan determination unit

Claims

1. An information processing device comprising: a complexity determination unit that determines the complexity of an area that is the subject of survey images acquired continuously over time from an unmanned aerial vehicle for a survey area to be surveyed; and an overlap rate setting unit that sets an overlap rate between the survey images based on the complexity.

2. The information processing device according to claim 1, wherein the complexity determination unit determines the complexity using an overall image in which the entire survey area is captured.

3. The information processing device according to claim 2, wherein the complexity determination unit determines the complexity based on a degree of variation in pixel values ​​corresponding to an acquisition range in which the survey image is acquired in the entire image.

4. The information processing device according to claim 3, wherein the pixel value includes at least one of a color and a brightness value.

5. The information processing device according to claim 2, wherein the complexity determining unit determines the complexity based on classification information for each pixel included in the entire image.

6. The information processing device according to claim 1, wherein the complexity determination unit determines the complexity using map information of the entire survey area.

7. An information processing device as described in claim 1, wherein the overlap rate setting unit sets as the overlap rate an overlap rate on the flight path of the unmanned aerial vehicle and a side lap rate between the flight paths.

8. The information processing device according to claim 1, wherein the overlap rate setting unit sets the overlap rate by weighting a reference overlap rate serving as a reference in accordance with the degree of complexity.

9. The information processing device according to claim 1, further comprising a flight path setting unit that sets a flight path for the unmanned aerial vehicle based on the complexity.

10. The information processing device according to claim 9, wherein the flight path setting unit sets the flight path by calculating the continuity of the complexity in the entire survey area.

11. The information processing device according to claim 10, wherein the flight path setting unit calculates the continuity of the complexity by searching for the complexity in a single stroke in a predetermined direction throughout the entire survey area.

12. The information processing device according to claim 10, wherein the flight path setting unit sets a direction in which the degree of continuity of the complexity is high as a direction of travel of the flight path.

13. The information processing device according to claim 12, wherein the flight path setting unit sets adjacent courses of the flight path according to the complexity adjacent to the complexity of the direction of travel.

14. An information processing device as described in claim 9, further comprising a flight plan determination unit that determines a flight plan including a flight speed of the unmanned aerial vehicle and an interval for acquiring the survey images based on the set overlap rate.

15. The information processing device according to claim 14, wherein the flight plan determination unit determines the flight plan in which the flight speed is constant and the acquisition interval is changed according to the overlap rate.

16. The information processing device according to claim 14, wherein the flight plan determination unit determines the flight plan in which the acquisition interval is constant and the flight speed is changed according to the overlap rate.

17. The information processing device according to claim 1, wherein the survey image is a camera image, and the overlap rate setting unit sets the overlap rate to a higher value as the complexity is smaller.

18. The information processing device according to claim 1, wherein the survey image is a distance image, and the overlap rate setting unit sets the overlap rate to a higher value as the degree of complexity increases.

19. An information processing method in which an information processing device determines the complexity of the area that is the subject of survey images acquired continuously over time from an unmanned aerial vehicle for a survey area to be surveyed, and sets an overlap rate between the survey images based on the complexity.

20. A program for causing a computer to execute a process of determining the complexity of the area that is the subject of survey images acquired continuously over time from an unmanned aerial vehicle for a survey area to be surveyed, and setting the overlap rate between the survey images based on the complexity.