Imaging planning system and imaging planning method

Abstract

An imaging planning system 20 comprises a planning unit 21 that plans an imaging plan for imaging a plurality of imaging points by using a plurality of artificial satellites, wherein the planning unit 21 generates one DAG by combining DAGs representing the imaging order in which one artificial satellite images the plurality of imaging points so that a predetermined condition is satisfied for the plurality of artificial satellites, performs topological sorting on the one generated DAG, and acquires the longest path in one DAG for which topological sorting is performed.

Description

[Technical Field]

[0001] The present invention relates to an imaging planning system and an imaging planning method, and more particularly to an imaging planning system and an imaging planning method for allocating imaging locations to a plurality of satellites and determining the imaging order. [Background technology]

[0002] A plan for one orbiting satellite (hereinafter simply referred to as a satellite) to capture images of multiple points on Earth can be obtained by expressing the order in which the images will be captured as a DAG (Directed Acyclic Graph) and finding the longest path from the DAG. Note that in this specification, "satellite" refers to an artificial satellite.

[0003] Fig. 15 is an explanatory diagram showing an example of creating an imaging plan for one satellite. As shown in the left part of Fig. 15, in this example, a case is considered in which a plan is created for one orbiting satellite to capture images of imaging points 1 to 5 on the Earth.

[0004] As shown on the right side of Figure 15, in this example, the imaging order of imaging points 1 to 5 of the orbiting satellite is represented by a DAG. The nodes (circles) that make up the DAG shown in Figure 15 represent imaging points. The edges (arrows) that make up the DAG shown in Figure 15 represent the order in which imaging can be performed. The meaning of each notation is the same in other figures.

[0005] Specifically, the order in which images can be captured is expressed by edges, taking into account the constraints of the orbiting satellites. For example, the DAG shown in Figure 15 indicates that an orbiting satellite can capture image point 1, followed by image point 3 or image point 5.

[0006] 15 indicates that the orbiting satellite can image imaging point 4 or imaging point 5 after imaging point 2. Also, the DAG shown in FIG. 15 indicates that the orbiting satellite can image imaging point 4 or imaging point 5 after imaging point 3.

[0007] In addition, the larger the weight of the nodes constituting the DAG shown in Fig. 15, the more prioritized the imaging location the node represents. As shown in Fig. 15, the weights of imaging locations 1 to 5 are "1", "2", "2", "1", and "1", respectively.

[0008] If the imaging points are imaged in the order that maximizes the total weight set as above, the orbiting satellite can image the greatest number of imaging points. The order that maximizes the total weight, i.e., the longest path in the DAG, is "imaging point 1 → imaging point 3 → imaging point 4."

[0009] As shown in Figure 15, when an imaging plan is created using DAG, an imaging plan is created that captures more imaging points.

[0010] Furthermore, Patent Document 1 describes a task communication method that can use a one-to-one synchronous communication API (Application Programming Interface) without causing deadlock in inter-task synchronous communication in a process that is composed of multiple tasks and synchronous communication.

[0011] Also, Patent Document 2 describes a method for determining an image layout, which includes a step of accessing a plurality of image elements having an ordered sequence.

[0012] Furthermore, Patent Document 3 describes a method for planning image acquisition of a ground area by a spacecraft, which is optimal for matching the local and cumulative constraints of the spacecraft and enables consideration of ground areas that need to be acquired multiple times or in one go. [Prior art documents] [Patent documents]

[0013] [Patent Document 1] Japanese Patent Application Laid-Open No. 2013-205966 [Patent Document 2] Special Publication No. 2016-524243 [Patent Document 3] Special Publication No. 2018-522775 Summary of the Invention [Problem to be solved by the invention]

[0014] Constellation operations are also being conducted, where multiple satellites take images at high frequency, rather than just a single satellite. However, the task of planning an image capture using multiple satellites is complex and time-consuming.

[0015] For example, when multiple satellites share an imaging location, it is necessary to consider the fact that even at the same imaging location, imaging times differ depending on the satellite, and that multiple satellites can image in parallel.

[0016] 16 is an explanatory diagram showing the problems involved in planning an imaging plan using multiple satellites. Fig. 16 shows a DAG representing the imaging order of satellite 1 and a DAG representing the imaging order of satellite 2.

[0017] For example, the two imaging points 1 shown in Fig. 16 are imaged by different satellites and at different times. Even if the imaging points are the same, if the satellites that image them and the times that they are imaged are different, they cannot be treated as one node.

[0018] Therefore, the condition that "only one of them can be photographed" is imposed on the two imaging points 1 shown in Fig. 16. Also, the condition that "only one of them can be photographed" is imposed on the two imaging points 3 shown in Fig. 16.

[0019] Also, for example, imaging point 2 and other imaging points shown in Fig. 16 can both be imaged even if the imaging times are the same, as long as the satellites taking the images are different. Therefore, the condition that "both can be imaged at the same time" is imposed on imaging point 2 and other imaging points shown in Fig. 16.

[0020] As described above, simply connecting the DAGs that represent the imaging order for each satellite does not result in an appropriate DAG that can be used to plan imaging using multiple satellites. Patent documents 1 to 3 do not describe a technology for planning imaging using multiple satellites using a DAG.

[0021] Furthermore, the mainstream method for improving computer performance is to improve the performance of multiple cores rather than the performance of a single CPU (Central Processing Unit) core. In other words, in order to speed up the planning of imaging plans, it is important to make the planning logic easy to parallelize.

[0022] SUMMARY OF THE INVENTION It is therefore an object of the present invention to provide an imaging planning system and imaging planning method that can quickly create an imaging plan using a plurality of satellites. [Means for solving the problem]

[0023] The imaging planning system according to the present invention is an imaging planning system including a planning unit that plans an imaging plan in which multiple satellites will image multiple imaging locations, and the planning unit generates a single DAG by combining DAGs that represent the imaging order in which one satellite will image multiple imaging locations so that predetermined conditions are satisfied across the multiple satellites, performs a topological sort on the single generated DAG, and obtains the longest path in the single DAG that has been topologically sorted.

[0024] The imaging planning method according to the present invention is an imaging planning method executed in an imaging planning system that plans an imaging plan in which multiple satellites will image multiple imaging locations, and is characterized in that the imaging planning system generates a single DAG by combining DAGs that represent the imaging order in which one satellite will image multiple imaging locations so that predetermined conditions are satisfied across the multiple satellites, performs a topological sort on the single generated DAG, and obtains the longest path in the single DAG that has been topologically sorted.

[0025] A computer-readable recording medium having recorded thereon an imaging plan creation program according to the present invention stores an imaging plan creation program that, when executed by a computer, creates an imaging plan in which multiple imaging locations are imaged by multiple satellites by combining DAGs representing the imaging order in which one satellite will image multiple imaging locations so that predetermined conditions are satisfied across the multiple satellites, performs topological sorting on the single generated DAG, and obtains the longest path in the single DAG that has been topologically sorted. [Effects of the Invention]

[0026] According to the present invention, an imaging plan using a plurality of satellites can be quickly formulated. [Brief explanation of the drawings]

[0027] [Figure 1] 1 is a block diagram showing an example of the configuration of an imaging planning system according to an embodiment of the present invention. [Figure 2] 10 is a flowchart showing the operation of imaging plan planning processing by the imaging plan planning system 100 of the present embodiment. [Figure 3] 10 is a flowchart showing the operation of a DAG combining process by an imaging plan generation processing unit 110 of this embodiment. [Figure 4] 10 is an explanatory diagram showing an example of arranging nodes constituting each DAG in a grid pattern by the imaging plan generation processing unit 110. FIG. [Figure 5] FIG. 10 is an explanatory diagram showing an example of connecting a node by the imaging plan generation processing unit 110 with a node of another satellite. [Figure 6] FIG. 10 is an explanatory diagram showing another example of connecting a node by the imaging plan generation processing unit 110 with a node of another satellite. [Figure 7] 10 is a flowchart showing the operation of a route generation process by an imaging plan generation processing unit 110 of this embodiment. [Figure 8]10 is an explanatory diagram showing an example of topological sorting performed on a DAG by the imaging plan generation processing unit 110. FIG. [Figure 9] 10 is a flowchart showing the operation of a general node score update process. [Figure 10] 10 is a flowchart showing the operation of node score update processing by the imaging plan generation processing unit 110 of this embodiment. [Figure 11] 10 is a flowchart showing the operation of imaging order acquisition processing by the imaging plan generation processing unit 110 of this embodiment. [Figure 12] 10 is an explanatory diagram showing an example of deleting a node from the longest route by the imaging plan generation processing unit 110. FIG. [Figure 13] 1 is an explanatory diagram showing an example of the hardware configuration of an imaging planning system 100 according to the present invention. [Figure 14] 1 is a block diagram showing an overview of an imaging planning system according to the present invention. [Figure 15] FIG. 1 is an explanatory diagram showing an example of creating an imaging plan using one satellite. [Figure 16] FIG. 1 is an explanatory diagram showing the problems that arise when planning an imaging project using multiple satellites. DETAILED DESCRIPTION OF THE INVENTION

[0028] [Configuration Description] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. Fig. 1 is a block diagram showing an example of the configuration of an imaging plan planning system according to an embodiment of the present invention. As shown in Fig. 1, an imaging plan planning system 100 according to this embodiment includes an imaging plan generation processing unit 110.

[0029] As mentioned above, when multiple orbiting satellites are assigned to capture multiple imaging locations without overlapping, it is necessary to consider which satellites should image which locations and in what order. Furthermore, the number of possible imaging order combinations for each satellite is enormous.

[0030] The imaging planning system 100 of this embodiment expresses the order in which multiple satellites will take images in parallel as a DAG, and uses a method for solving the longest route that incorporates a mechanism to avoid overlap, thereby enabling the rapid creation of plans for imaging multiple imaging locations by dividing the work among multiple orbiting satellites.

[0031] In this embodiment, we consider the case where a plan is made to capture multiple imaging points on the Earth by dividing the work among multiple orbiting satellites. As shown in Figure 1, a DAG representing the order in which the multiple imaging points will be captured is prepared as input data for each orbiting satellite.

[0032] The imaging plan generation processing unit 110 of this embodiment combines the DAGs for each prepared orbiting satellite. Next, the imaging plan generation processing unit 110 calculates the longest route and obtains the imaging points and imaging order assigned to each satellite. As shown in FIG. 1, the imaging plan generation processing unit 110 outputs data indicating the imaging order of the imaging points for each satellite as output data.

[0033] [Explanation of operation] Hereinafter, the operation of the imaging plan formulation system 100 of this embodiment for formulating an imaging plan using a plurality of orbiting satellites will be described with reference to Fig. 2. Fig. 2 is a flowchart showing the operation of the imaging plan formulation process by the imaging plan formulation system 100 of this embodiment.

[0034] First, the imaging plan generation processing unit 110 of the imaging plan planning system 100 receives a plurality of input data each indicating a DAG for each satellite (step S110).

[0035] Next, the imaging plan generation processing unit 110 executes a DAG combining process to combine the DAGs for each satellite indicated by the plurality of input data into one DAG (step S120).

[0036] Next, the imaging plan generation processing unit 110 executes a path generation process to find the longest path from the DAG combined in step S120 (step S130).

[0037] Next, the imaging plan generation processing unit 110 executes an imaging order acquisition process to obtain the imaging order for each satellite from the longest route obtained in step S130 (step S140).

[0038] Next, the imaging plan generation processing unit 110 outputs the imaging order for each satellite calculated in step S140 (step S150). After outputting the imaging order for each satellite, the imaging plan planning system 100 ends the imaging plan planning process.

[0039] Next, the DAG combining process of step S120, which is a sub-process constituting the imaging plan formulation process shown in Fig. 2, will be described with reference to Fig. 3. Fig. 3 is a flowchart showing the operation of the DAG combining process by the imaging plan generation processing unit 110 of this embodiment.

[0040] The imaging plan generation processing unit 110 arranges the nodes that make up each DAG in a grid in order of the earliest imaging time for the input DAG for each satellite (step S121).

[0041] Next, the imaging plan generation processing unit 110 connects all of the arranged nodes to the nodes of other satellites in order of earliest imaging time (step S122). After the connection, the imaging plan generation processing unit 110 returns to the imaging plan formulation processing shown in FIG.

[0042] Fig. 4 is an explanatory diagram showing an example of arranging the nodes constituting each DAG in a grid pattern by the imaging plan generation processing unit 110. Fig. 4 shows an example of arranging the nodes constituting each DAG of satellites 1 to m by the imaging plan generation processing unit 110 in step S121.

[0043] As shown in FIG. 4, the imaging plan generation processing unit 110 calculates each node constituting the DAG at imaging times t1 to t n The imaging plan generation processing unit 110 also arranges a plurality of nodes with the same imaging time in a horizontal row. The imaging plan generation processing unit 110 performs the above-mentioned arrangement processing for each DAG.

[0044] Fig. 5 is an explanatory diagram showing an example of connecting a node to a node of another satellite by the imaging plan generation processing unit 110. Fig. 5 shows an example of connecting the nodes constituting the DAGs of satellite 1 and satellite 2 by the imaging plan generation processing unit 110 in step S122.

[0045] When connecting a node, the imaging plan generation processing unit 110 selects, as a connection destination, a node of another satellite whose imaging time is the same as the imaging time of the connection source node or a node whose imaging time is in the future. As indicated by the dashed arrow in Fig. 5, the imaging plan generation processing unit 110 does not select, as a connection destination, a node whose imaging time is earlier than the imaging time of the connection source node.

[0046] 5, when connecting to a destination node with the same imaging time, the imaging plan generation processing unit 110 copies the destination node and output edges (only edges that output to nodes of the same satellite). Next, the imaging plan generation processing unit 110 connects the source node, the copied destination node, and the copied output edge, respectively.

[0047] Furthermore, as shown in FIG. 5, when connecting to a destination node whose imaging time is in the future, the imaging plan generation processing unit 110 directly connects the originating node and the destination node.

[0048] When connections are made as shown in Fig. 5, no closed loop is generated. That is, the imaging plan generation processing unit 110 can represent the order in which multiple satellites take images in parallel as a DAG.

[0049] 5 shows an example in which the imaging plan generation processing unit 110 connects the nodes that make up the DAG of satellite 1 to the nodes that make up the DAG of satellite 2. However, the imaging plan generation processing unit 110 can also perform connections in the reverse direction, i.e., from the nodes that make up the DAG of satellite 2 to the nodes that make up the DAG of satellite 1.

[0050] FIG. 6 is an explanatory diagram showing another example of connecting a node by the imaging plan generation processing unit 110 with a node of another satellite.

[0051] As shown in FIG. 6, when there are multiple rows of nodes constituting a DAG in which nodes are arranged in a grid pattern on a destination satellite, the imaging plan generation processing unit 110 selects a destination node for each row and performs a connection operation.

[0052] For example, the imaging plan generation processing unit 110 connects the nodes that make up the DAG of satellite 1 to the nodes in column 1 and column 2 that make up the DAG of satellite 2. Note that the way in which the imaging plan generation processing unit 110 connects the nodes shown in Fig. 6 is the same as the way in which the imaging plan generation processing unit 110 connects the nodes shown in Fig. 5.

[0053] Next, the route generation process of step S130, which is a sub-process constituting the imaging plan formulation process shown in Fig. 2, will be described with reference to Fig. 7. Fig. 7 is a flowchart showing the operation of the route generation process by the imaging plan generation processing unit 110 of this embodiment.

[0054] The imaging plan generation processing unit 110 combines the multiple start nodes and multiple end nodes in the single DAG generated in step S120 into one group. After combining the nodes, the imaging plan generation processing unit 110 performs topological sorting on the single generated DAG (step S131).

[0055] Next, the imaging plan generation processing unit 110 updates the scores of the nodes to the maximum value in the order of topological sorting from the grouped start node to the grouped end node (step S132).

[0056] Next, the imaging plan generation processing unit 110 generates the longest path by tracing the input source nodes recorded in the nodes from the grouped end nodes to the grouped start nodes (step S133).

[0057] After generating the longest path, the imaging plan generation processing unit 110 returns to the imaging plan formulation processing shown in Fig. 2. The method of finding the longest path after topologically sorting the DAG shown in Fig. 7 is a general method of finding the longest path from a DAG.

[0058] Fig. 8 is an explanatory diagram showing an example of topological sorting performed on a DAG by the imaging plan generation processing unit 110. Fig. 8 shows an example of topological sorting performed by the imaging plan generation processing unit 110 in step S131. Note that Fig. 8 shows some of the nodes and edges among the nodes and edges that constitute the DAG.

[0059] As shown in the left part of Fig. 8, the imaging plan generation processing unit 110 combines a plurality of start nodes and a plurality of end nodes in one DAG generated in step S120 into one. Two rounded rectangles shown in Fig. 8 represent the combined start node and the combined end node, respectively.

[0060] After combining the multiple start nodes and multiple end nodes into one, the imaging plan generation processing unit 110 performs topological sorting on the DAG. The right part of Fig. 8 shows the DAG after the topological sorting.

[0061] Regarding the processing of step S132, the imaging plan generation processing unit 110 generally obtains the score of a node by "score of input source node+weight of input source node".

[0062] Hereinafter, an operation for updating the scores of nodes constituting a general DAG to the maximum value will be described with reference to Fig. 9. Fig. 9 is a flowchart showing the operation of a general node score update process. For convenience of explanation, the imaging plan generation processing unit 110 is the subject of each process shown in Fig. 9.

[0063] The imaging plan generation processing unit 110 initializes the scores of all nodes constituting the DAG to 0 (step S001). Next, the imaging plan generation processing unit 110 enters a node loop (step S002).

[0064] The imaging plan generation processing unit 110 that has entered the node loop extracts one node whose score has not yet been updated from the topologically sorted DAG. That is, the imaging plan generation processing unit 110 enters an edge loop (step S003).

[0065] The imaging plan generation processing unit 110 that has entered the edge loop extracts one input edge that has not yet been processed from among the input edges to the extracted node.

[0066] An input source node is recorded in the input edge. The imaging plan generation processing unit 110 determines whether or not the score of the extracted node is smaller than the sum of the "score of the input source node" and the "weight of the input source node" recorded in the extracted input edge (step S004).

[0067] If the score of the node is equal to or greater than the sum of the "score of the input source node" and the "weight of the input source node" (False in step S004), the imaging plan generation processing unit 110 returns to the processing in step S003 and processes the next input edge.

[0068] If the score of the node is smaller than the sum of the "score of the input source node" and the "weight of the input source node" (True in step S004), the imaging plan generation processing unit 110 updates the score of the node to "score of the input source node+weight of the input source node" (step S005).

[0069] Next, the imaging plan generation processing unit 110 updates the input source node to the extracted node to the input source node recorded in the extracted input edge (step S006). After updating, the imaging plan generation processing unit 110 returns to the processing of step S003 and processes the next input edge.

[0070] The imaging plan generation processing unit 110 repeatedly executes the processes of steps S004 to S006 until all input edges to the extracted node have been processed. When all input edges to the extracted node have been processed, the imaging plan generation processing unit 110 exits the edge loop (step S007).

[0071] The imaging plan generation processing unit 110 repeatedly executes the processes of steps S003 to S007 in the order of the topologically sorted nodes until the scores of all the topologically sorted nodes are updated.

[0072] When all the scores of the topologically sorted nodes have been updated, the imaging plan generation processing unit 110 exits the node loop (step S008). Upon exiting the node loop, the imaging plan generation processing unit 110 ends the node score update processing.

[0073] In this embodiment, the general node score update process shown in Fig. 9 is modified as shown in Fig. 10. Hereinafter, the operation of the imaging plan generation processing unit 110 of this embodiment for updating the scores of the nodes constituting the DAG to the maximum value will be described with reference to Fig. 10. Fig. 10 is a flowchart showing the operation of the node score update process by the imaging plan generation processing unit 110 of this embodiment.

[0074] The imaging plan generation processing unit 110 initializes the scores of all nodes constituting the DAG to 0 (step S901). Next, the imaging plan generation processing unit 110 enters a node loop (step S902).

[0075] The imaging plan generation processing unit 110 that has entered the node loop extracts one node whose score has not yet been updated from the topologically sorted DAG. That is, the imaging plan generation processing unit 110 enters an edge loop (step S903).

[0076] The imaging plan generation processing unit 110 that has entered the edge loop extracts one input edge that has not yet been processed from among the input edges to the extracted node.

[0077] An input source node is recorded in the input edge. The imaging plan generation processing unit 110 determines whether or not the satellite that images the extracted node is different from the satellite that images the input source node recorded in the extracted input edge (step S904). For convenience, the "satellite that images the node" is written as the "satellite of the node" in FIG. 10.

[0078] If the satellite imaging the extracted node and the satellite imaging the input source node recorded in the extracted input edge are different (True in step S904), the imaging plan generation processing unit 110 sequentially traces the input source nodes of the input source node recorded in the extracted input edge. By sequentially tracing the input source nodes, the imaging plan generation processing unit 110 searches for a node imaged by the same satellite as the satellite imaging the extracted node (step S905).

[0079] If a node imaged by the same satellite has not been found (No in step S906), the imaging plan generation processing unit 110 proceeds to the processing of step S908.

[0080] If a node imaged by the same satellite is found (Yes in step S906), the imaging plan generation processing unit 110 determines whether or not the node from which the satellite is extracted after the found node cannot be imaged (step S907).

[0081] If the satellite cannot image the extracted node (Yes in step S907), the imaging plan generation processing unit 110 returns to the processing in step S903 and processes the next input edge.

[0082] If the satellite can image the extracted node (No in step S907), the imaging plan generation processing unit 110 proceeds to the processing of step S908.

[0083] If the satellite imaging the extracted node is the same as the satellite imaging the input source node recorded in the extracted input edge (False in step S904), the imaging plan generation processing unit 110 initializes the variable weight to 0 (step S908).

[0084] Next, the imaging plan generation processing unit 110 sequentially traces the input source nodes of the input source nodes recorded in the extracted input edge. By tracing the input source nodes sequentially, the imaging plan generation processing unit 110 searches for a node indicating the same imaging point as the imaging point indicated by the extracted node (step S909).

[0085] If a node indicating the same imaging point is not found (No in step S910), the imaging plan generation processing unit 110 proceeds to the processing of step S912.

[0086] If a node indicating the same imaging point is found (Yes in step S910), the imaging plan generation processing unit 110 sets the weight of the node indicating the same imaging point found in the variable weight (step S911).

[0087] Next, the imaging plan generation processing unit 110 determines whether the score of the extracted node is smaller than the difference between the sum of the "score of the input source node" and the "weight of the input source node" recorded in the extracted input edge and the variable weight (step S912).

[0088] If the score of the node is greater than or equal to the difference between the sum of the "score of the input source node" and the "weight of the input source node" and the variable weight (False in step S912), the imaging plan generation processing unit 110 returns to the processing of step S903 and processes the next input edge.

[0089] If the score of the node is smaller than the difference between the sum of the "score of the input source node" and the "weight of the input source node" and the variable weight (True in step S912), the imaging plan generation processing unit 110 updates the score of the node to "score of the input source node + weight of the input source node - variable weight" (step S913).

[0090] Next, the imaging plan generation processing unit 110 updates the input source node to the extracted node to the input source node recorded in the extracted input edge (step S914). After updating, the imaging plan generation processing unit 110 returns to the processing of step S903 and processes the next input edge.

[0091] The imaging plan generation processing unit 110 repeatedly executes the processes of steps S904 to S914 until all input edges to the extracted node have been processed. When all input edges to the extracted node have been processed, the imaging plan generation processing unit 110 exits the edge loop (step S915).

[0092] The imaging plan generation processing unit 110 repeatedly executes the processes of steps S903 to S915 in the order of the topologically sorted nodes until the scores of all the topologically sorted nodes are updated.

[0093] When all the scores of the topologically sorted nodes have been updated, the imaging plan generation processing unit 110 exits the node loop (step S916). Upon exiting the node loop, the imaging plan generation processing unit 110 ends the node score update processing.

[0094] The imaging plan generation processing unit 110 of this embodiment updates the scores of the nodes and the input source nodes of the nodes by executing the node score update processing shown in Fig. 10 in step S132. When the scores of the nodes and the input source nodes of the nodes are updated as shown in Fig. 10, the imaging plan generation processing unit 110 can obtain the longest path from the DAG in step S133.

[0095] Also, as described above, the processing of steps S004 to S006 shown in Fig. 9 has been changed to the processing of steps S904 to S914 shown in Fig. 10. The above change is made to satisfy the conditions shown in Fig. 16 that "only one of the two can be imaged" and "both can be imaged in the same time period."

[0096] Next, the imaging order acquisition process of step S140, which is a sub-process constituting the imaging plan formulation process shown in Fig. 2, will be described with reference to Fig. 11. Fig. 11 is a flowchart showing the operation of the imaging order acquisition process by the imaging plan generation processing unit 110 of this embodiment.

[0097] The imaging plan generation processing unit 110 traces the longest route obtained in step S130 from the end node to the start node. If a node indicating an imaging point that has already appeared is detected during the tracing, the imaging plan generation processing unit 110 deletes the detected node (step S141).

[0098] Next, the imaging plan generation processing unit 110 classifies the nodes remaining on the longest route by satellite. Next, the imaging plan generation processing unit 110 arranges the nodes classified by satellite in order of earliest imaging time (step S142).

[0099] The remaining nodes are classified by satellite and arranged in order of earliest imaging time, so that the imaging plan generation processing unit 110 can determine the imaging order for each satellite. After determining the imaging order for each satellite, the imaging plan generation processing unit 110 returns to the imaging plan formulation processing shown in FIG.

[0100] Fig. 12 is an explanatory diagram showing an example of deleting a node from the longest path by the imaging plan generation processing unit 110. Fig. 12 shows an example of deleting overlapping nodes by the imaging plan generation processing unit 110 in step S141.

[0101] In the longest route shown in the left part of Fig. 12, two circles marked with "1" represent two nodes indicating the same imaging point. When the imaging plan generation processing unit 110 detects a node indicating an imaging point that has already appeared while tracing the longest route from the end node to the start node, it deletes the second circle marked with "1" as shown in the right part of Fig. 12.

[0102] As described above, the imaging plan formulation system 100 of this embodiment is an imaging plan formulation system including the imaging plan generation processing unit 110 that formulates an imaging plan in which a plurality of satellites images a plurality of imaging points.

[0103] The imaging plan generation processing unit 110 generates a single DAG by combining DAGs representing the imaging order in which one satellite will image multiple imaging points so that a predetermined condition is satisfied across multiple satellites, performs topological sorting on the single generated DAG, and obtains the longest path in the single DAG that has been topologically sorted. The predetermined condition is that no closed paths are generated.

[0104] The imaging plan generation processing unit 110 also classifies the multiple imaging points that make up the acquired longest route by the satellite that captures the images, and executes a process of arranging the classified multiple imaging points in order of imaging time for each satellite, thereby creating an imaging plan.The imaging plan generation processing unit 110 also deletes the imaging point with the earlier imaging time from among the overlapping imaging points on the acquired longest route.

[0105] In addition, the imaging plan generation processing unit 110 calculates the score of the node that constitutes one DAG after topological sorting and indicates the imaging location, and the input source node of the node, for each of all nodes that constitute one DAG.

[0106] Furthermore, the imaging plan generation processing unit 110 calculates the score of the node and the input source node of the node so that the condition that imaging is possible for only one node among a plurality of nodes indicating the same imaging point is satisfied.

[0107] Furthermore, the imaging plan generation processing unit 110 calculates the score of the node and the input source node of the node so that the condition that a plurality of nodes indicating different imaging points can all be imaged at the same imaging time is satisfied.

[0108] Furthermore, a DAG representing the imaging sequence of one satellite may have multiple columns in which multiple imaging points are arranged in the order of imaging time.

[0109] The imaging plan generation processing unit 110 of this embodiment may replace the DAG for each satellite with a DAG for each path. By replacing them, the imaging plan generation processing unit 110 can plan which path to use to capture an imaging point that can be imaged by one satellite from either of two paths. Furthermore, the imaging plan generation processing unit 110 of this embodiment can create imaging plans for multiple satellites that can be imaged from either of multiple paths.

[0110] [Effect description] When combining multiple DAGs that represent the imaging order when imaging is performed by a single satellite, the imaging plan generation processing unit 110 of this embodiment selects and copies the destination nodes to prevent a closed loop, thereby maintaining the combined graph in the DAG.

[0111] The imaging plan generation processing unit 110 also performs a topological sort on the combined DAG to find the longest path. When finding the longest path, the imaging plan generation processing unit 110 calculates a score taking into account overlapping points of imaging.

[0112] Next, the imaging plan generation processing unit 110 removes overlapping points from the obtained longest route. Next, the imaging plan generation processing unit 110 classifies the imaging points remaining on the longest route by satellite, and obtains the imaging order of the imaging points assigned to each satellite.

[0113] Therefore, the imaging planning system 100 of this embodiment obtains the allocation of imaging locations and the imaging order for multiple satellites by finding the longest path from the DAG. When topological sorting is performed, the longest path can be quickly obtained from the DAG. In other words, the imaging planning system 100 can quickly create imaging plans for multiple satellites.

[0114] Furthermore, the imaging plan making system 100 of this embodiment can be easily implemented using a programming language with simple logic. Furthermore, since many parts of the processing by the imaging plan generation processing unit 110 can be executed in parallel, when the imaging plan generation processing unit 110 is controlled by a many-core CPU, the imaging plan generation processing unit 110 can execute processing at higher speed.

[0115] Of the processes by the imaging plan generation processing unit 110, the processes that can be executed in parallel are the processes of steps S121, S122, and S903. The process of step S121 can be executed in parallel for each satellite. Moreover, the process of step S122 can be executed in parallel for each node. Moreover, each process in the loop of step S903 can be executed in parallel. The processes by the imaging plan generation processing unit 110 can be easily executed in parallel, and therefore can be easily accelerated.

[0116] The present invention can be used in the fields of earth observation or drone aerial photography.

[0117] A specific example of the hardware configuration of the imaging planning system 100 of this embodiment will be described below. Fig. 13 is an explanatory diagram showing an example of the hardware configuration of the imaging planning system 100 according to the present invention.

[0118] 13 includes a CPU 11, a main storage unit 12, a communication unit 13, and an auxiliary storage unit 14. The imaging planning system 100 also includes an input unit 15 for user operation and an output unit 16 for presenting the processing results or the progress of the processing contents to the user.

[0119] The imaging planning system 100 is realized by software when the CPU 11 shown in FIG. 13 executes a program that provides the functions of each component element.

[0120] That is, the CPU 11 loads the program stored in the auxiliary storage unit 14 into the main storage unit 12, executes it, and controls the operation of the imaging planning system 100, whereby each function is realized by software.

[0121] 13 may include a DSP (Digital Signal Processor) instead of the CPU 11. Alternatively, the imaging planning system 100 shown in Fig. 13 may include both the CPU 11 and a DSP.

[0122] The main memory unit 12 is used as a data working area and a data temporary saving area, and is, for example, a RAM (Random Access Memory).

[0123] The communication unit 13 has a function of inputting and outputting data to and from peripheral devices via a wired network or a wireless network (information communication network).

[0124] The auxiliary storage unit 14 is a non-transitory tangible storage medium, such as a magnetic disk, a magneto-optical disk, a CD-ROM (Compact Disk Read Only Memory), a DVD-ROM (Digital Versatile Disk Read Only Memory), or a semiconductor memory.

[0125] The input unit 15 has a function of inputting data and processing commands, and is an input device such as a keyboard, a mouse, or a touch panel.

[0126] The output unit 16 has a function of outputting data and is, for example, a display device such as a liquid crystal display device, a touch panel, or a printing device such as a printer.

[0127] As shown in FIG. 13, in the imaging planning system 100, each component is connected to a system bus 17.

[0128] In the imaging plan making system 100, the auxiliary storage unit 14 stores a program for realizing the imaging plan generation processing unit 110.

[0129] The imaging planning system 100 may be implemented with a circuit including hardware components such as an LSI (Large Scale Integration) that realizes the functions shown in FIG. 1 inside.

[0130] Furthermore, the imaging planning system 100 may be realized by hardware that does not include computer functions using elements such as a CPU. For example, some or all of the components may be realized by a general-purpose circuit, a dedicated circuit, a processor, or a combination thereof. These may be configured by a single chip (for example, the above-mentioned LSI), or may be configured by multiple chips connected via a bus. Some or all of the components may be realized by a combination of the above-mentioned circuits, etc. and a program.

[0131] Furthermore, some or all of the components of the imaging planning system 100 may be configured by one or more information processing devices each including a calculation unit and a storage unit.

[0132] When some or all of the components are realized by multiple information processing devices, circuits, etc., the multiple information processing devices, circuits, etc. may be centrally or decentralized. For example, the information processing devices, circuits, etc. may be realized as a client-server system, a cloud computing system, or the like, in which they are connected via a communication network.

[0133] Next, an overview of the present invention will be described. Fig. 14 is a block diagram showing an overview of an imaging planning system according to the present invention. The imaging planning system 20 according to the present invention is an imaging planning system including a planning unit 21 (e.g., an imaging plan generation processing unit 110) that plans an imaging plan in which multiple satellites image multiple imaging points. The planning unit 21 generates one DAG by combining DAGs that represent the imaging order in which one satellite images multiple imaging points so that a predetermined condition is satisfied across the multiple satellites, performs topological sorting on the generated DAG, and obtains the longest path in the topologically sorted DAG.

[0134] The planner 21 may also classify the multiple imaging points that make up the acquired longest route by the satellite that captures the images, and may create an imaging plan by executing a process of arranging the classified multiple imaging points in order of imaging time for each satellite.The planner 21 may also delete an imaging point that was captured earlier from among overlapping imaging points on the acquired longest route.

[0135] With such a configuration, the imaging planning system can quickly plan imaging using multiple satellites.

[0136] The predetermined condition may also be that a closed path is not generated.

[0137] Such a configuration allows the imaging planning system to maintain the combined graph in the DAG.

[0138] In addition, the planning unit 21 may calculate the score of a node that constitutes a single DAG after topological sorting and indicates an imaging location, and the input source node of the node, for each of all nodes that constitute a single DAG.

[0139] Such a configuration allows the imaging planning system to find the longest path from the DAG in a general way.

[0140] Furthermore, the planner 21 may calculate the score of a node and the input source node of the node so that the condition that only one of a plurality of nodes indicating the same imaging location can be imaged is satisfied.

[0141] Furthermore, the planning unit 21 may calculate the scores of the nodes and the input source nodes of the nodes so that the condition that a plurality of nodes indicating different imaging locations can all be imaged at the same imaging time is satisfied.

[0142] With such a configuration, the imaging planning system can solve the problem of planning imaging using multiple satellites.

[0143] Furthermore, a DAG representing the imaging sequence of one satellite may have multiple columns in which multiple imaging points are arranged in the order of imaging time.

[0144] Although the present invention has been described above with reference to the embodiments, the present invention is not limited to the above embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.

[0145] This application claims priority based on Japanese Patent Application No. 2022-070489, filed on April 22, 2022, the disclosure of which is incorporated herein in its entirety. [Explanation of symbols]

[0146] 11 CPU 12 Main memory 13 Communications Department 14 Auxiliary storage 15 Input section 16 Output section 17 System Bus 20, 100 Imaging planning system 21 Planning Department 110 Imaging plan generation processing unit

Claims

1. An imaging plan planning system including a planning unit that plans an imaging plan in which a plurality of satellites capture images of a plurality of imaging points, The planning unit generating a Directed Acyclic Graph (DAG) by connecting DAGs representing an imaging order in which one satellite images the plurality of imaging points so that a predetermined condition is satisfied across the plurality of satellites; A topological sort is performed on the generated DAG. Obtain the longest path in the topologically sorted DAG. An imaging planning system characterized by:

2. The Planning Department The plurality of imaging points constituting the acquired longest route are classified by the satellites that image them; An imaging plan is created by executing a process for each satellite to sort the classified imaging points in order of imaging time. The imaging planning system according to claim 1 .

3. The planning unit deletes the imaging point with the earlier imaging time from among the overlapping imaging points on the acquired longest route. The imaging planning system according to claim 2.

4. The predetermined condition is that no cycle is generated. The imaging planning system according to claim 1 .

5. The planning unit calculates the score of a node that constitutes one DAG after topological sorting and indicates an imaging point, and the input source node of the node, for each of all nodes that constitute the one DAG. The imaging planning system according to claim 1 .

6. The planning unit calculates the score of the node and the input source node of the node so that the condition that only one of the nodes indicating the same imaging point can be imaged is satisfied.

6. The imaging planning system according to claim 5.

7. The planning unit calculates the scores of the nodes and the input source nodes of the nodes so that the condition that multiple nodes indicating different imaging points can all be imaged at the same imaging time is satisfied.

6. The imaging planning system according to claim 5.

8. The DAG representing the imaging sequence of one satellite has multiple columns in which multiple imaging points are arranged in the order of imaging time. The imaging planning system according to claim 1 .

9. An imaging plan formulation method executed in an imaging plan formulation system that formulates an imaging plan in which a plurality of satellites image a plurality of imaging points, comprising: The imaging planning system includes: generating one DAG by combining DAGs representing an imaging order in which one satellite images the plurality of imaging points so that a predetermined condition is satisfied across the plurality of satellites; A topological sort is performed on the generated DAG. Obtain the longest path in the topologically sorted DAG. An imaging planning method comprising:

10. On the computer, In order to create an imaging plan in which a plurality of satellites image a plurality of imaging points, a DAG is generated by combining DAGs representing an imaging order in which one satellite images the plurality of imaging points so that a predetermined condition is satisfied across the plurality of satellites; A topological sort is performed on the generated DAG. Obtain the longest path in the topologically sorted DAG. A photography planning program for this purpose.

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