Spatiotemporal collaborative path search optimization method and system in mission activity threat cost assessment

Abstract

The present invention belongs to the technical field of task environment path optimization, and particularly relates to a space-time collaborative path search optimization method and system in task activity threat cost assessment. In the space-time coordinate system, within the reachable space-time prism range of the task, the space-time comprehensive environmental impact model is rasterized, and the space-time unit cubes divided along the coordinate axis with the same space and time interval are used as space-time voxels, and the geometric centers of the space-time voxels are used as nodes according to the time intervals. Time points at different times are connected by uniform linear motion to construct space-time path segments; the target space-time voxel center point is screened by adjusting the space-time voxel space interval, and the path between each starting space-time point and the corresponding screened target voxel center point is used as a candidate path; the minimum cost path between the starting space-time point and the target voxel center point in all time periods is found by path search, and then the optimal path of the task comprehensive threat cost is obtained, which can effectively reduce the amount of calculation and improve the efficiency of task path planning.

Description

Technical Field

[0001] The present invention belongs to the technical field of task environment path optimization, and in particular relates to a spatiotemporal collaborative path search optimization method and system in task activity threat cost assessment. Background Art

[0002] In a specific field, a mission refers to a single-stage action in physical space. A mission is a broad concept. It is an orderly collection of a series of interrelated actions carried out by an action unit to fulfill its responsibilities or achieve a specific purpose under certain environmental and spatiotemporal constraints, including actions in multiple stages in physical and non-physical space, and the connection and coordination between the stages. There is a mutual influence or dependency between the actions at each stage. It is a complex union. In addition to the basic environmental impact, the more important thing is the clever strategy. The spatiotemporal environmental effectiveness evaluation for combat missions is not a complex problem that can be solved by any field of knowledge alone. It involves many environmental problems, analysis methods, solutions, and knowledge in related fields. The main purpose of environmental impact analysis is to analyze the objective influence of environmental factors. The corresponding analysis conclusions have no direct relationship with specific tasks, but the results can support further comprehensive impact analysis for specific tasks. The spatiotemporal prism problem studies the boundary problem of human activities, that is, the maximum spatiotemporal range that can appear within a period of time when the speed of human movement is affected by the environment. Studying the space-time prism in off-road activities can evaluate the off-road accessibility as a whole, analyze the space-time range, key points, space-time tolerance and other issues that may occur in off-road activities, so as to achieve the purpose of evaluating the task effectiveness as a whole. The purpose of global path planning in space and time is to find a continuous space-time path connecting the starting and target space-time points. As with the shortest time path planning, it can be approximated by several segments of space straight lines connected end to end. An important step in this process is to construct a path to search for alternative space-time path segments. In the shortest time path, in order to achieve the purpose of minimizing the time cost, the maximum safe speed in each voxel can be used to construct the corresponding space-time straight line segment as an alternative route segment. For the space-time path with the minimum comprehensive threat cost based on voxels, although the path selection is locally limited by the maximum speed and is generally limited by the space-time prism, since the comprehensive threat level cost is not a boundary problem, there are many possible optional paths in the feasible area. At the same time, since it is necessary to search for the path with the minimum cost in both space and time, the calculation is very large and time-consuming. Summary of the invention

[0003] To this end, the present invention provides a spatiotemporal collaborative path search optimization method and system in the threat cost assessment of task activities, which utilizes the spatiotemporal trajectory of task activities in the spatiotemporal coordinate system to obtain optional paths of the comprehensive threat cost of task execution plans, adjusts the spatial interval of spatiotemporal voxels to perform minimum cost search in the feasible spatiotemporal domain defined by the space-time prism to select the optimal path for task activities, and limits the optional paths by limiting the number of voxels inside the space-time prism and the space-time voxel spacing, which can effectively control the amount of calculation and improve the efficiency of the comprehensive threat cost assessment of tasks, so as to achieve the purpose of scientifically and effectively selecting the optimal plan in task activities.

[0004] According to the design scheme provided by the present invention, a spatiotemporal collaborative path search optimization method in task activity threat cost assessment is provided, comprising:

[0005] In the space-time coordinate system, within the range of the space-time prism that the task can reach, the space-time comprehensive environmental impact model used to describe the law of space-time environmental impact is rasterized, and the space-time unit cubes divided with the same space and time interval along the coordinate axis of the space-time coordinate system are used as space-time voxels. The geometric centers of the space-time voxels are used as nodes according to the time intervals, and the time points at different times are connected by uniform linear motion to construct the space-time path segments;

[0006] In the space-time path section, the target space-time voxel center point corresponding to the starting space-time point is screened by adjusting the space-time voxel spatial interval, and the path between each starting space-time point and the corresponding screened target space-time voxel center point is used as a candidate path;

[0007] For the candidate paths, the time interval is used as the calculation time period. Starting from the first time period, the calculation time period is used as the hierarchy. The minimum cost path between the starting space-time point and the target space-time voxel center point in all calculation time periods is found through hierarchical path search. The optimal path with the comprehensive threat cost between the start and end of the task activity is obtained based on the minimum cost path in all calculation time periods.

[0008] As a spatiotemporal collaborative path search optimization method in the task activity threat cost assessment of the present invention, further, the spatiotemporal comprehensive environmental impact model expands the time dimension on the basis of the spatial environmental cost law, and uses the spatiotemporal coordinate system to record the cumulative growth rate of the environmental cost during task execution due to the environment, situation and capability factors of the spatial point at the time point, wherein the spatiotemporal coordinate system establishes a three-dimensional rectangular coordinate system by determining a point on the surface as the origin, the eastward direction as the X-axis, the northward direction as the Y-axis, and time T as the vertical upward Z-axis, and uses the three-dimensional rectangular coordinate system as the spatiotemporal coordinate system.

[0009] As a spatiotemporal collaborative path search optimization method in the task activity threat cost assessment of the present invention, further, in the model rasterization processing, the space is rasterized at the same spatial interval along the X-axis and Y-axis of the spatiotemporal coordinate system, and each spatial grid determines a spatial grid center; it is divided at the same time interval along the T-axis, and the minimum space-time unit after the time and space rasterization is used as the space-time voxel for simplifying the complexity of environmental spatial changes and temporal changes.

[0010] As a spatiotemporal collaborative path search optimization method in the task activity threat cost assessment of the present invention, further, in the gridded spatiotemporal voxel environment, the shortest time required for the corresponding spatiotemporal point to reach the center of the adjacent space grid is obtained based on the shortest time required to travel along a straight line in space at the maximum safe speed allowed by the environment and reach the center of the target space grid, the earliest arrival spatiotemporal point at the center of each space grid is solved to approximate the lower pyramid surface of the space-time prism, and the latest stay spatiotemporal point at the center of each space grid is solved to approximate the upper pyramid surface of the space-time prism; and the spatiotemporal trajectory of the corresponding segment of movement in the solution process is used as the connection between the current space-time point and the center of the target space grid, and A continuous space-time trajectory is composed of multiple space-time straight line segments connected end to end; each space-time straight line segment is in a different space-time voxel, and except for the current space-time point and the center of the target space grid, the space-time starting point and ending point of each segment are the space-time coordinates of the space-time trajectory entering and exiting the space-time voxel; the space-time trajectory tracking uses the space-time coordinates of the last space-time voxel passed through as the space-time starting point of the next space-time straight line segment in sequence, and calculates the space-time coordinates when passing through the space-time voxel in combination with the spatial movement direction, the space-time range of the space-time voxel and the maximum speed of traveling in a specific direction in the space-time voxel, until it reaches the center of the target space grid in space to obtain the space-time prism used to describe the reachable area of ​​the target object.

[0011] As a spatiotemporal collaborative path search optimization method in the task activity threat cost assessment of the present invention, further, the spatiotemporal trajectory of the task activity is tracked by using the spatiotemporal voxels in the spatiotemporal comprehensive environmental impact model, and the spatiotemporal coordinates of the spatiotemporal points where the task executes enters or passes through the space-time voxels are used to obtain the travel length and residence time in each space-time voxel on the space-time trajectory. The comprehensive environmental cost of the task execution plan is obtained through the cost growth rate of each space-time voxel passed by the space-time trajectory, the residence time in the corresponding space-time voxel, and the travel length; and the total cost accumulation value used to evaluate the pros and cons of the task activity plan is obtained based on the sum of the cost values ​​generated when the space-time trajectory passes through each space-time voxel.

[0012] As a spatiotemporal collaborative path search optimization method in the task activity threat cost assessment of the present invention, further, in adjusting the spatial interval of the spatiotemporal voxels, the spatial interval of the spatiotemporal voxels is increased by using equal-space sampling or reducing the spatiotemporal resolution of the spatiotemporal voxels.

[0013] As a spatiotemporal collaborative path search optimization method in the task activity threat cost assessment of the present invention, further, in adjusting the spatiotemporal voxel spatial interval, an integer multiple of the spatiotemporal voxel spatial interval is used as a mask reference length in the space of the spatiotemporal coordinate system, and the target spatiotemporal voxel center point is sampled using a mask method, and the spatial coordinates of the sampling point are recorded on the mask; the spatiotemporal voxel center point containing key position information is appended and recorded on the mask; the starting spatiotemporal point and the target voxel center point are selected in the mask record to obtain candidate paths for spatiotemporal path search.

[0014] Furthermore, the present invention also provides a spatiotemporal collaborative path search optimization system in task activity threat cost assessment, comprising: a region construction module, a node screening module and a path selection module, wherein:

[0015] The regional construction module is used to rasterize the space-time comprehensive environmental impact model used to describe the law of space-time environmental impact within the range of the space-time prism that can be reached by the task in the space-time coordinate system, and use the space-time unit cubes divided by the same space and time interval along the coordinate axis of the space-time coordinate system as space-time voxels, and use the geometric center of the space-time voxels as nodes according to the time interval to connect the time points at different times through uniform linear motion to construct the space-time path segment;

[0016] A node screening module is used to screen the target space-time voxel center point corresponding to the starting space-time point by adjusting the space-time voxel space interval within the space-time path section, and take the path between each starting space-time point and the corresponding screened target space-time voxel center point as a candidate path;

[0017] The path selection module is used to select candidate paths, taking the time interval as the calculation time period, starting from the first time period, and taking the calculation time period as the hierarchy, to find the minimum cost path between the starting time-space point and the target time-space voxel center point in all calculation time periods through hierarchical path search, and obtain the optimal path with the comprehensive threat cost between the start and end of the task activity based on the minimum cost path in all calculation time periods.

[0018] Beneficial effects of the present invention:

[0019] The present invention constructs a search for alternative space-time path segments by using voxel geometric centers as nodes, integer multiples of voxel unit time intervals as time intervals, and uniform linear motion to connect the starting point and the target space-time point. The number of voxels inside the space-time prism is used to limit the optional paths. When performing the minimum cost search in the feasible space-time domain, the amount of calculation will increase with the maximum safe speed of the off-road mission and its off-road time length, and the maximum safe speed changes only slightly in the application. The time length of the off-road mission is controlled by the mission requirements and is difficult to predict. In this case, the amount of calculation in the minimum cost path search is controlled by adjusting the space-time voxel spatial interval; the amount of calculation is further controlled by using spatial position masks or reducing the resolution of space-time voxels to achieve optimal path planning that integrates space and time. Compared with manual planning methods, this method is more scientific, optimized, and more efficient, and has good application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the spatiotemporal collaborative path search optimization process in the task activity threat cost assessment in the embodiment;

[0021] Figure 2 It is a schematic diagram of the space-time coordinate system in the embodiment;

[0022] Figure 3 This is a schematic diagram of the space-time environment model after rasterization processing in the embodiment;

[0023] Figure 4 This is a schematic diagram of the space-time trajectory calculation process in the embodiment;

[0024] Figure 5 It is a schematic diagram of the space-time path and the space-time prism space in the embodiment;

[0025] Figure 6 Schematic diagram of a space-time path segment to be selected for a space-time path search node in an embodiment;

[0026] Figure 7 This is a schematic diagram of the process of reducing the amount of calculation by using a spatial position mask in the embodiment;

[0027] Figure 8 This is a diagram showing the relationship between the time consumption of the time-space minimum cost path planning and the time difference between the starting and target points in the embodiment;

[0028] Fig. 9 This is a schematic diagram of the experimental results of B133 in the embodiment. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solutions and advantages of the present invention clearer and more understandable, the present invention is further described in detail below in conjunction with the accompanying drawings and technical solutions.

[0030] The present invention provides a method for optimizing the spatiotemporal collaborative path search in the threat cost assessment of mission activities. Figure 1 As shown, including:

[0031] S101. Within the reachable space-time prism of the task in the space-time coordinate system, the space-time comprehensive environmental impact model used to describe the space-time environmental impact law is rasterized, and the space-time unit cubes divided with the same space and time interval along the coordinate axis of the space-time coordinate system are used as space-time voxels, and the geometric centers of the space-time voxels are used as nodes according to the time intervals, and the time points at different times are connected by uniform linear motion to construct the space-time path segments;

[0032] S102, within the space-time path section, the target space-time voxel center point corresponding to the starting space-time point is screened by adjusting the space-time voxel spatial interval, and the path between each starting space-time point and the corresponding screened target space-time voxel center point is used as a candidate path;

[0033] S103. For the candidate paths, the time interval is used as the calculation time period. Starting from the first time period, the calculation time period is used as a hierarchy. The minimum cost path between the starting time-space point and the target time-space voxel center point in all calculation time periods is found through hierarchical path search. The optimal path of the comprehensive threat cost between the start and end point of the task activity is obtained based on the minimum cost path in all calculation time periods.

[0034] The search for alternative space-time path segments is constructed by using the geometric center of voxels as nodes inside the space-time prism, the integer multiples of the voxel unit time interval as the time interval, and the starting point and the target space-time point connected by uniform linear motion. The number of voxels inside the space-time prism is used to limit the optional paths. When the minimum cost search is performed in the feasible space-time domain, the amount of calculation will increase with the maximum safe speed of the off-road mission and the length of the off-road time. In addition, the maximum safe speed varies only slightly in the application, and the length of the off-road mission is subject to the mission requirements and is difficult to predict. In this case, the amount of calculation in the minimum cost path search is controlled by adjusting the spatial interval of the space-time voxels.

[0035] Furthermore, in the embodiments of this case, when constructing an environmental comprehensive impact model based on space-time voxels, the time dimension is expanded on the basis of the law of spatial cost of the task environment to realize the situation where any point in space changes continuously in time with respect to that point. By rasterizing the model, the comprehensive environmental cost on the space-time trajectory of the task execution plan is obtained, and a comprehensive and reasonable comprehensive environmental assessment of the task plan is performed to achieve the purpose of scientifically and effectively selecting corresponding strategies in task execution. The number of voxels inside the space-time prism is used to limit the optional paths and effectively control the amount of calculation.

[0036] The two-dimensional space environmental impact model can show the laws of environmental costs in different spaces, but it cannot reflect the impact of environmental changes over time. To this end, in the embodiment of this case, the spatiotemporal comprehensive environmental impact model expands the time dimension based on the laws of spatial environmental costs, and uses the spatiotemporal coordinate system to record the cumulative growth rate of environmental costs in task execution caused by the environment, situation and capability factors of spatial points at different time points, wherein the spatiotemporal coordinate system is established by determining a point on the surface as the origin, the eastward direction as the X-axis, the northward direction as the Y-axis, and time T as the vertical upward Z-axis to establish a three-dimensional rectangular coordinate system, and the three-dimensional rectangular coordinate system is used as the spatiotemporal coordinate system.

[0037] like Figure 2 As shown in the figure, (a) represents the space-time coordinate system of two-dimensional space, and (b) represents the space coordinate system of three-dimensional space. Both coordinate systems are three-dimensional coordinate systems, but the coordinates have completely different meanings. The definition of the space-time coordinate system of two-dimensional space is consistent with the similar coordinate system in space-time geography. In order to uniformly express the dynamic changes of spatial environment over time, the embodiment of this case uses a space-time comprehensive environmental impact model to establish Figure 2 The space-time coordinate system described in the above is used to record the environmental impact law at any time and space. The space-time growth rate of the comprehensive environmental cost is recorded at any position (x, y, t) in the space-time coordinate system. The rate of change of the cumulative cost of task execution caused by the environment, situation, and capabilities at time t recorded at the spatial point (x, y). The meaning of is related to the cost. For the shortest time planning, It is the minimum time required to move a unit distance, that is, the shortest time consumption cost rate As for the comprehensive path cost analysis, is the space-time comprehensive threat cost rate

[0038] The space-time is divided into space-time unit cubes with the same space and time intervals along the coordinate axes of the space-time coordinate system, and the space-time unit cubes are used as space-time voxels.

[0039] Mission along L m The total space-time cost Applicable to the task execution plan moving along any space-time trajectory. By integrating the overall space-time cost formula, the relevant environmental cost can be obtained, but the changes in time and space of the environment are irregular, and there are difficulties in the actual calculation process. Therefore, in the embodiment of this case, the space-time environment is rasterized, such as Figure 3 As shown, along the XYT three axes, the space-time is divided into space-time unit cubes (space-time voxels, abbreviated as voxels) with the same space and time interval. It is approximately considered that the space-time growth rate of the comprehensive cost of the environment in the same space-time unit is The environment affiliation problem in the rasterization process can be set as follows: in space, the rasterized environment belongs to the part of the environment that has the greatest impact on the task, and in time, the state of the environment belongs to the state of the environment at the geometric center of the voxel. It expresses the time-space rate of cost accumulation. In addition to being related to the time-space environment, it may also be related to other factors, such as the driving direction during task execution, historical trajectory, etc. Therefore, even after the environment is rasterized, It is not necessarily a numerical value, but represents a law of cost accumulation.

[0040] In theory, the process of understanding the impact of the environment is to But in fact, for all voxels in the space-time region It is unrealistic to perform all the calculations once, and the cost of performing such a huge amount of environmental assessment is huge, which will lead to explosion problems in the calculation process. To address this problem, in the embodiment of this case, the spatiotemporal trajectory can be used, that is, which voxel is used in the assessment process to generate which voxel, how many voxels are used, and how much environmental assessment is performed.

[0041] The significance of discretization is to simplify complex laws of change. When the gridded space-time interval is of appropriate size, it can be approximately considered that the environment in the space-time it represents is similar, and all its cost laws are also consistent. Figure 3 As shown, if (x0, y0, t0) is the geometric center point of the green voxel shown in the figure, w′(·) is the approximate expression of the cost w(·) in the voxel, then w can be approximately expressed by the following formula:

[0042]

[0043] As a spatiotemporal collaborative path search optimization method in the task activity threat cost assessment in an embodiment of the present invention, further, in the gridded spatiotemporal voxel environment, the shortest time required for the corresponding spatiotemporal point to reach the center of the adjacent spatial grid is obtained based on the shortest time required to travel along a straight line in space at the maximum safe speed allowed by the environment and reach the center of the target spatial grid, the earliest arrival spatiotemporal point at the center of each spatial grid is solved to approximate the lower pyramid surface of the space-time prism, and the latest stay spatiotemporal point at the center of each spatial grid is solved to approximate the upper pyramid surface of the space-time prism; and the spatiotemporal trajectory of the corresponding segment of motion in the solution process is used as the connection between the current space-time point and the center of the target spatial grid. , and a continuous space-time trajectory composed of multiple space-time straight line segments connected end to end; each space-time straight line segment is in a different space-time voxel, and except for the current space-time point and the center of the target space grid, the space-time starting point and ending point of each segment are the space-time coordinates of the space-time trajectory entering and exiting the space-time voxel; the space-time trajectory tracking uses the space-time coordinates of the last space-time voxel passed through as the space-time starting point of the next space-time straight line segment, and calculates the space-time coordinates when passing through the space-time voxel in combination with the spatial movement direction, the space-time range of the space-time voxel and the maximum speed of traveling in a specific direction in the space-time voxel, until it reaches the center of the target space grid in space to obtain the space-time prism used to describe the reachable area of ​​the target object. The space-time voxels are used to track the space-time trajectory of task activities in the space-time comprehensive environmental impact model. The space-time coordinates of the space-time points where the task enters or passes through the space-time voxels are used to obtain the travel length and residence time in each space-time voxel on the space-time trajectory. The comprehensive environmental cost of the task execution plan is obtained through the cost growth rate of each space-time voxel passed by the space-time trajectory, the residence time in the corresponding space-time voxel, and the travel length; and the total cost accumulation value used to evaluate the pros and cons of the task activity plan is obtained based on the sum of the cost values ​​generated when the space-time trajectory passes through each space-time voxel.

[0044] To evaluate the cost of task execution schemes based on the spatiotemporal comprehensive environmental impact model, we first need to obtain which spatiotemporal voxels the known scheme will pass through, as well as the length of time it stays in each spatiotemporal voxel and the spatial distance it moves. This process is the spatiotemporal tracking process of the movement trajectory. Movement in the spatiotemporal comprehensive environmental impact model can be regarded as a series of continuous straight-line motions, and any complex motion trajectory can be approximated in this way. Figure 4 The figure shows a straight-line motion from a spacetime point S to a spacetime point E in a spacetime. A portion of voxels A0, B0, and B1 are drawn in the figure, where A0 and B0 are adjacent in space and time, and B0 and B1 are adjacent in space and time. Spacetime point S is the space point A on its spacetime trajectory L A A spacetime point on the spacetime trajectory L. BA space-time point on the voxel. Assume that the task execution plan starts from S and follows the space-time trajectory shown in the figure, passing through space-time points M0 and M1 to reach E. The space-time coordinates of the endpoints of each straight line segment in the specific plan are known (such as the space-time coordinates of S and E in the figure are known), and the driving speed and direction of this section of the task journey are known. If the space-time coordinates of each space-time point entering or passing through the voxel are calculated (such as the space-time coordinates of M0 and M1 in the figure), the travel length and residence time of the space-time trajectory in each voxel of the path (such as the three voxels of A0, B0, and B1 in the figure) can be calculated.

[0045] When solving the specific model, the driving direction i can be calculated by the spatial coordinates of A and B using the formula i = arctan ((y B -y A ) / (x B -x B )) is calculated. This value does not change when each voxel between these two points moves. The speed in the x and y axes is According to the solution, we can get: Let upper(x) and floor(x) be the downward and upward rounding functions, respectively. We can define forward(x) and backward(x) as the backward and forward rounding functions, respectively. The grid intervals of x, y, and t axes are d x ,d y ,d t , let the coordinates of the start of movement in the j-th space-time voxel be marked as (x j ,y j ,t j ), the maximum remaining movement time within the voxel and the geometric center coordinates of the voxel It can be expressed as:

[0046]

[0047] exist During this period, without considering the spatial boundaries of the voxels, the maximum travel distances in the x and y axes are Without considering the time boundary of space-time voxels, the maximum driving distances in the x and y axes are If other axes are not considered, the shortest time to pass through the T axis, X axis, and Y axis is The corresponding formula is Then the earliest exit time Δt j Expressed as The axial direction corresponds to the shortest time.

[0048] After completing the above calculations, if This means that the end point has not been reached after passing through the jth voxel, and the user will continue to move into the j+1th voxel. The coordinates when entering are Repeat the above steps in the next voxel until the nth voxel can reach the end point, in which case Δt n Corrected to And end the calculation.

[0049] The above method can be used to track the motion of the straight line segment in the voxel and obtain the space-time coordinates of the space-time trajectory when it enters and passes through each voxel. The trajectory is a uniform linear motion in the voxel, that is, the straight line segment connecting the space-time points entering and passing through the voxel (such as Figure 4 The straight line segment M0M1 in the middle) can be used to track which voxels a specific off-road plan will pass through, as well as the length of time it stays in each voxel and the spatial distance it moves.

[0050] If the space-time trajectory of the task execution plan obtained by mobile trajectory tracking will pass through n space-time voxels in sequence, the cost growth rate of the i-th space-time voxel is The trajectory stayed in this spacetime voxel for the time The length of the travel space is Then the cost W that the task execution plan will generate in the i-th voxel of the model is i for

[0051] Time geography is a universal method for understanding the interdependence between humans, nature, and technology. It is generally studied in a conceptual coordinate system consisting of n-dimensional space and 1-dimensional time. Time and space are orthogonal, and individual activities are unidirectional and irreversible in the time dimension. The basic elements of time geography are space-time paths and space-time prisms. The space-time prism problem studies the boundary problem of human activities, that is, the maximum space-time range that can appear when the speed of human movement is affected by the environment within a period of time. Studying the space-time prism in off-road activities can evaluate the off-road accessibility as a whole, analyze the space-time range size, key points, space-time tolerance capabilities, and other issues that may appear in off-road activities, so as to achieve the purpose of evaluating the mission effectiveness as a whole.

[0052] like Figure 5 As shown, the space-time trajectory of a stationary object can be represented in the space-time coordinate system as a straight line parallel to the time axis (such as L s ); the space-time path of a continuously moving object appears as a continuous curve (such as L m ); spacetime point P′ Start and P′ end The space-time region U between the departure space-time point and the arrival space-time point P′ is called endA certain space-time prism, expressing the space-time range in which the moving object may appear during this period of time, P′ end P′ Start They are called the upper and lower anchor points of the space-time prism respectively; PPA is the abbreviation of Potential Path Area, which represents the spatial range in which an individual may appear within the time budget. A (x A ,y A ,t A ),P B (x B ,y B ,t B ) is a uniform linear motion between two points, and the speed calculation formula is:

[0053]

[0054] This value is exactly L m The slope of the space surface. The smaller the slope value, the faster the speed of movement in space. s As shown, if an object is stationary, it should appear as a straight line parallel to the time axis.

[0055] The expression of reachability by space-time prism is mainly based on the following principle: if the space-time area that can be reached by any space-time trajectory that does not exceed the maximum speed from the starting point is recorded as N; if the space-time area that can be reached by any space-time trajectory that does not exceed the maximum speed before the end point is recorded as R, then the following is shown:

[0056] U={(x,y,t)|(x,y,t)∈N∩(x,y,t)∈R}

[0057] Anchor point P S ' tart With P e ' ndThe determined space-time prism U is a space-time that satisfies both the space-time that can be reached from the specified starting point at a specified time and the space-time that can reach the end point before another specified time. It reflects the possibility of an individual traveling and moving within the starting point, the end point and a certain time budget. The space-time area expressed by the space-time prism is the space-time area that can be reached by the task activities in this case. The space-time area that is not within this range is subject to time budget, environmental influences and rule restrictions, and it is impossible to reach from the starting point or the end point on time. The space-time prism is used to obtain the range of the reachable area in the task execution plan under predictable space-time conditions, and the space-time prism is used to represent the space-time boundaries that may appear in the task execution plan, which is convenient for evaluating the feasibility, reliability, space-time redundancy and other issues of the task when it is executed in the corresponding space-time. Considering the continuous change of the environment over time, it will not lead to a large number of invalid calculations, and solve the problem that a large number of space-times in the traditional algorithm are actually impossible to reach in a changing environment.

[0058] In this case, the geometric center of the voxel is used as the node inside the space-time prism, and the time interval is an integer multiple of the voxel unit time interval. The method of connecting the starting point and the target space-time point with uniform linear motion is used to construct a search for alternative space-time path segments and perform space-time path search. Since the number of voxels inside the space-time prism is limited, the number of selected paths is limited, which can effectively control the amount of calculation. When performing the next path search for a certain voxel center, refer to Figure 6 As shown, the selectable space-time path segments can be constructed according to the following steps:

[0059] (1) Taking the starting space-time point as the starting point and the integer multiple voxel unit time interval as a calculation time period, calculate the space-time boundary range that the starting space-time point can reach within this period;

[0060] (1) Find all voxels that contain the target time in the spatial range that can be reached by the starting time-space point and in the overall off-road reachable time-space domain, and use the geometric center points of these voxels as the center points of the target voxels;

[0061] (2) Use a space-time straight line (uniform linear motion) to connect the starting space-time point to all target space-time points. The corresponding connecting line is the alternative space-time trajectory for the next step of searching at the starting space-time point.

[0062] The space-time path segment obtained in the embodiment of this case is used as a candidate space-time path segment. The slope of the candidate space-time line is used to calculate the speed and direction of travel, and the space-time trajectory of the space-time voxels related to the path is calculated along the space-time line. It can be approximately considered that the environmental influence law within a space-time voxel is unchanged. The cost growth rate of the candidate path segment H in the i-th space-time voxel is The trajectory stayed in this spacetime voxel for the time The length of the travel space is Therefore, the cost incurred in the i-th voxel is If H passes through q voxels, and the cumulative comprehensive threat cost of H's previous segment H-1 is D H-1 , then the cumulative comprehensive threat level cost of H is D H according to Calculate. H It represents the minimum cumulative comprehensive threat level cost required to reach the center of the currently calculated target voxel through path H starting from the starting point of the task activity.

[0063] When searching for a path, the calculation can be performed hierarchically according to the calculation time period. Starting from the first calculation time period inside the reachable domain, the calculation is performed according to the following steps: starting from each node on the lower boundary of the reachable domain within the time period, the alternative spatiotemporal path to the center point of the target voxel in the time period is calculated. If the current calculation time period is not the first time period, the alternative paths from the center points of all target voxels in the previous calculation time period to the center point of the target voxel in the current time period should also be calculated; evaluating that there are multiple alternative paths connecting each target voxel center point in the current calculation time period, only one path with the minimum cumulative comprehensive threat cost is retained, and the other alternative paths are discarded. The minimum cumulative threat cost to the center point of the current target voxel is evaluated in combination with the minimum comprehensive threat cost of the corresponding starting point; if within a calculation time period, the reachable spatiotemporal domain contains part of the upper boundary of the spatiotemporal prism, each node on the upper boundary is used as the center point of the target voxel to participate in the above calculation, and the overall cumulative comprehensive threat cost from the corresponding node on the upper boundary to the final target point of the off-road is evaluated and recorded; entering the next calculation time period until all calculations in the reachable domain are completed; finding the path with the minimum cumulative comprehensive threat cost of all paths to the end point of the off-road is the path with the optimal cost.

[0064] Since it is necessary to search for the path with the minimum cost in space and time, the amount of calculation is very large. In this application, the scenario is set as a classic scenario with isotropic speed and no change over time. This scenario is independent of the situation, the speed of driving in all directions is the same, and the speed does not change over time. The environment is set as: a gentle isotropic environment with flat terrain and no obstacles. The speed of any task undertaker in all directions is 1m / s and does not change over time. The situation is set as: no situation, and only the task undertaker is considered in the environment. The ability is set as: a setting for scenario analysis, the driving speed is independent of the direction and is specified by the environment; no rest or food is taken during off-road. The task type is set as: non-war action, off-road action is only affected by the environment, mainly considering issues related to economic consumption, considering less risks, and is independent of the situation. It is assumed that the starting point and the target point have the same spatial position, the off-road time length is 2T, the space-time intervals of the voxels are marked as Δt and Δx respectively, the calculation time period length is selected as nΔt, and the maximum safe speed of off-road is v. Then within a calculation time length, the maximum number of possible space-time trajectory segments to be selected for a certain starting space-time point is set to m, m = floor(π(vnΔt / Δx) 2 ), then in the kth calculation time period of the lower half pyramid (k=1,2,...,floor(T / (nΔt))), there may be M paths to be selected k =m·floor(π(kvnΔt / Δx) 2 ). Therefore, the equivalent relationship between the total number of paths M that need to evaluate the comprehensive threat cost within the entire space-time prism is M~(v / Δx) 4 T 3 nΔt, its computational complexity is the fourth order of (v / Δx), the third order of the half time T, and the first order of nΔt.

[0065] The above is the equivalent formula for the computational amount of searching for the minimum cost path when the space-time prism is a regular pyramid. The computational amount of the space-time prism for oblique pyramids and other special-shaped pyramids will be even smaller. In general, the computational amount of searching for the minimum cost in the feasible space-time domain defined by the space-time prism will increase rapidly with the increase of v and T, and decrease rapidly with the increase of Δx. In general applications, v, n, and Δt change to a limited extent, but the change of T is mainly controlled by the task requirements, which is difficult to predict and may be large. The only way to reduce the computational amount is to increase Δx, and the order of Δx is greater than the order of T. Although increasing Δx will reduce the level of detail of the plan, the rate of reduction is faster than the rate of increase of the computational amount. This means that no matter how large T is, by adjusting Δx, within a certain amount of computation, a solution that keeps the total level of detail unchanged (for example, the number of straight line segments constituting the path remains unchanged) can be obtained. Therefore, in the embodiment of the present case, in adjusting the spatial interval of space-time voxels, the spatial interval of space-time voxels is further increased by using equal-interval sampling or reducing the space-time resolution of space-time voxels, and then the candidate paths for space-time path search are obtained by screening the center points of space-time voxels to achieve the effect of increasing Δx.

[0066] The main reason for the high amount of search calculations is that each starting time-space point corresponds to a large number of target voxel center points, but the costs of these candidate paths are not very different in most cases. Therefore, the method of discarding non-critical target points in some target voxel center points can be used to quickly reduce the amount of calculations. This method is similar to increasing the distance between the two target voxel center points, which indirectly achieves the effect of increasing Δx. The simplest way to exclude target voxel center points is to sample the target voxel center points at equal intervals, but the regular exclusion of certain points can easily lead to the loss of key information, such as the loss of key nodes such as bridges and river crossings. Furthermore, in the embodiment of the present case, the method of reducing the amount of calculations through spatial position masks, the main reason for the high amount of search calculations is that each starting time-space point corresponds to a large number of target voxel center points, but the costs of these candidate paths are not very different in most cases. Therefore, the method of discarding non-critical target points in some target voxel center points can be used to quickly reduce the amount of calculations. This method is similar to increasing the distance between the two target voxel center points, which indirectly achieves the effect of increasing Δx. Specifically, as Figure 7 As shown in the figure: the spatial center points of the voxels are sampled at an integer multiple of Δx spacing (referred to as the mask reference length in this article, denoted as Δy) in space, and the spatial coordinates of the sampling points are recorded on the mask; the voxel center point coordinates containing key position information are supplemented and recorded additionally on the mask; in the process of space-time path search, when selecting the starting space-time point and the target voxel center point, only the spatial coordinate positions recorded on the mask are considered.

[0067] The method of reducing resolution can reduce the computational complexity of spatiotemporal path search. Compared with the method of using masks, a more direct method is to reduce the spatiotemporal resolution of voxels. The method of reducing resolution directly increases Δx, and reduces the computational complexity of comprehensive threat cost evaluation on each path, which quickly reduces the computational complexity at a speed of 4 orders, but the disadvantage is that the accuracy is poorer than the method of using masks.

[0068] Furthermore, based on the above method, an embodiment of the present invention also provides a spatiotemporal collaborative path search optimization system in task activity threat cost assessment, comprising: a region construction module, a node screening module and a path selection module, wherein:

[0069] The regional construction module is used to rasterize the space-time comprehensive environmental impact model used to describe the law of space-time environmental impact within the range of the space-time prism that can be reached by the task in the space-time coordinate system, and use the space-time unit cubes divided by the same space and time interval along the coordinate axis of the space-time coordinate system as space-time voxels, and use the geometric center of the space-time voxels as nodes according to the time interval to connect the time points at different times through uniform linear motion to construct the space-time path segment;

[0070] A node screening module is used to screen the target space-time voxel center point corresponding to the starting space-time point by adjusting the space-time voxel space interval within the space-time path section, and take the path between each starting space-time point and the corresponding screened target space-time voxel center point as a candidate path;

[0071] The path selection module is used to select candidate paths within the reachable domain defined by the reachable space-time prism. It takes the time interval as the calculation time period, starts from the first time period, and uses the calculation time period as the unit level to find the minimum cost path between the starting space-time point and the target space-time voxel center point in all calculation time periods through hierarchical path search. Based on the minimum cost path in all calculation time periods, the optimal path with the comprehensive threat cost between the start and end point of the task activity is obtained.

[0072] This solution can reflect the impact of continuously changing environment, situation, capability and other comprehensive factors through the space-time comprehensive environmental impact model. The reachable domain analysis using space-time prism can support spatial overlapping and intersecting paths, and cleverly use time difference to solve spatial conflict problems. It can support various tasks with different preferences to achieve the best performance evaluation of the comprehensive threat cost of task activities, and when searching for the path with the minimum cost within the space and time range, the nodes are screened by adjusting the space-time voxel space interval to control the calculation amount. It has high calculation efficiency and is easy to implement and apply in actual scenarios.

[0073] In order to verify the effectiveness of the scheme in this case, the following is a further explanation of the effectiveness of the scheme in this case combined with a computational comparison experiment. There are 8 experiments in total, and the specific parameters are shown in Table 1.

[0074] Table 1. Computational comparison experiment details of minimum comprehensive threat cost path analysis

[0075]

[0076]

[0077] Among them, in this comparison time, the classic scene is the same as the above scene setting, and will not be repeated. The long-distance off-road complex simulation environment is set as follows: independent of the situation, anisotropic, and a complex simulation scene with a large amount of scene data. The environment will change continuously over time, and the ferry's passability will change periodically, taking into account biological habits. It is used to verify the complex changes in passability under the influence of the environment and biological habits. Contains the following combinations:

[0078] Environmental setting: Comprehensive simulation environment. The terrain used in this environment setting is ASTER GDEM 2DEM data, with a latitude and longitude range of E 120°~121°, N 41°~42°. The data of rivers, lakes and artificial building facilities are collected from OpenStreetMap. The assumptions of clay content of the four related soil types are shown in Table 2.

[0079] Table 2 Soil quality settings in environmental settings

[0080]

[0081] Referring to Anderson's related research, it is assumed that the study area is expected to have heavy rain from 8:30 to 11:30, and then the meteorological conditions will be good. The soil moisture content will gradually return to the original level within 28 hours after the rain. The prediction of the moisture content change of the above four soil types under the combined effects of rainfall, temperature, terrain and vegetation is shown in Table 3. The moisture content between given moments can be obtained by interpolation in time.

[0082] Table 3 Predicted values ​​of water content changes in four types of soil

[0083]

[0084] There are ferries in some river sections. The ferries are only available during the service time period. The service timetable is shown in Table 4. Bridges can be used at any time (bridge speed limit v b :40km / h).

[0085] Table 4 Ferry service schedule

[0086]

[0087] The real environment is more complex than the above simulation environment, but this setting can already represent various types of environmental impacts to a certain extent. A more complex environment will only show different rules and will not affect the scientific judgment of the experimental results. In order to facilitate data generation and control environmental variables, no more complex environments will be set.

[0088] Situation setting: Same as the above-mentioned no situation setting. Ability setting: Long-distance cross-country troop simulation ability setting.

[0089] The main performance parameters of off-road equipment are shown in Table 5, where VCI1 and VCI 50 It is the motor vehicle cone index of off-road vehicles, which refers to the rated cone index that the soil needs to meet at least once and the rated cone index that the soil needs to meet at least 50 times. When the rated cone index (RCI) of the soil is less than VCI1, the vehicle cannot pass through, and when it is greater than VCI 50 The vehicle's passability is not restricted by soil quality. The flat ground speed refers to the speed at which the vehicle generally travels when the road conditions are good, and the minimum speed refers to the minimum speed that the vehicle can accept for long-term driving. The maximum climbing grade refers to the maximum slope that the vehicle can travel in the direction of the slope. In order to ensure driving safety and sufficient power and prevent rollover, it is stipulated that the slope must be less than the maximum climbing grade regardless of the driving direction. Due to the nature of the vehicle, this setting does not allow the vehicle to pass through artificial buildings.

[0090] Table 5 Off-road parameters of motor vehicles

[0091]

[0092] According to the research on path finding of dump trucks in large open pit mines by Choi et al., the speed of the vehicle has different effects on uphill and downhill driving. As shown in Table 6, due to safety and physiological needs, it is usually necessary to arrange meals and rest in time during long-distance off-road driving. In addition, rest for 5 minutes every 55 minutes of driving.

[0093] Table 6 Meals and rest arrangements

[0094]

[0095] Mission type: non-combat performance, off-road operations are only affected by the environment, mainly considering issues related to economic consumption, with less risk considerations and not related to the situation.

[0096] High spatial resolution, low temporal resolution: spatial resolution: 90 meters; temporal resolution: 120 seconds.

[0097] Low spatial resolution, low temporal resolution: spatial resolution: 500 meters; temporal resolution: 120 seconds.

[0098] Based on the above experimental conditions and parameter settings, experiments A011, A012, A013, A014, and A015 are designed to verify the equivalent relationship between the total number of comprehensive threat cost paths M~(v / Δx) 4 T 3 nΔt, and the only difference between them is the length of the time difference between the starting point and the end point. The first 7 experiments can be repeated 5 times each, and the consumed computing time is listed in Table 7, and the relationship between the computing time of the first 5 experiments and T is plotted as a statistical Figure 8 As can be seen from the figure, as T increases, the computation time increases very quickly. After fitting, it is exactly a cubic relationship with a very high degree of conformity (R of the fitting curve is 2 Very close to 1), the experiment verified that M~(v / Δx) 4 T 3 The accuracy of nΔt.

[0099] Table 7 Average calculation time of related experiments repeated 5 times

[0100]

[0101] Experiments A035 and A115 respectively implement the method of reducing the amount of calculation by using a mask and the method of reducing the resolution. From the experimental results, it can be concluded that the method of directly or indirectly increasing Δx can quickly and effectively reduce the amount of calculation; by comparing A035 and A115, it can be seen that the mask method can ensure a certain accuracy, but the speed of reducing the amount of calculation is not as fast as the method of directly reducing the resolution; by comparing A011, A015 and A115, it can be seen that the speed of reducing the amount of calculation due to the increase in the spatial resolution Δx of the voxel is faster than the speed of increasing the amount of calculation due to the increase in T.

[0102] Different from the previous seven experiments, experiment B133 was conducted in a long-distance off-road complex simulation environment using a masking method. Its purpose was to verify that the masking method would not cause the loss of important spatial information nodes. Fig. 9 The starting point and the end point of the off-road trip are on both sides of the river, connected only by a narrow bridge. If the target voxel center point is simply sampled by a certain spatial spacing method, the bridge may be excluded, resulting in failure to reach the destination. However, when generating a spatial mask, the bridge is retained as a key point through the mask, so it can participate in the path search process. Fig. 9 The light-medium thin line represents the space-time path planned by experiment B133, and the semi-transparent space-time prism is the reachable domain of the off-road vehicle. As can be seen from the result diagram (c), the route connects the starting point and the target point through a bridge, and the result is relatively reasonable.

[0103] Based on the above system, an embodiment of the present invention further provides a server, comprising: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the above method.

[0104] Based on the above system, an embodiment of the present invention further provides a computer-readable medium on which a computer program is stored, wherein the program implements the above method when executed by a processor.

[0105] The device provided in the embodiment of the present invention has the same implementation principle and technical effects as those of the aforementioned system embodiment. For the sake of brief description, for matters not mentioned in the device embodiment, reference may be made to the corresponding contents in the aforementioned system embodiment.

[0106] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system and device described above can refer to the corresponding process in the aforementioned system embodiment, and will not be repeated here.

[0107] In all examples shown and described herein, any specific values ​​should be interpreted as merely exemplary and not as limiting, and thus other examples of the exemplary embodiments may have different values.

[0108] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0109] The flow charts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, systems and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0110] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and systems can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the device or unit can be electrical, mechanical or other forms.

[0111] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0112] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the system described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0113] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A spatiotemporal collaborative path search optimization method in task activity threat cost assessment, characterized in that: Contains the following: In the space-time coordinate system, within the range of the space-time prism that the task can reach, the space-time comprehensive environmental impact model used to describe the law of space-time environmental impact is rasterized, and the space-time unit cubes divided at the same space and time intervals along the coordinate axis of the space-time coordinate system are used as space-time voxels, and the geometric centers of the space-time voxels are used as nodes according to the time intervals. The time points at different times are connected by uniform linear motion to construct the space-time path segments; in the model rasterization processing, the space is rasterized at the same spatial interval along the X-axis and Y-axis of the space-time coordinate system, and a space grid center is determined for each space grid; the time is divided at the same time interval along the T-axis, and the time is connected. The minimum space-time unit after time and space rasterization is used as the space-time voxel for simplifying the complexity of environmental spatial and temporal changes; and in the space-time voxel environment after rasterization, the shortest time required for the corresponding space-time point to reach the center of the adjacent space grid is obtained according to the shortest time required to travel along the space straight line at the maximum safe speed allowed by the environment and reach the center of the target space grid, the earliest arrival space-time point at the center of each space grid is solved to approximate the lower pyramid surface of the space-time prism, and the latest stay space-time point at the center of each space grid is solved to approximate the upper pyramid surface of the space-time prism; and the space-time trajectory of the corresponding segment of motion in the solution process is As a continuous space-time trajectory consisting of multiple space-time straight line segments connecting the current space-time point and the center of the target space grid, and connected end to end; each space-time straight line segment is in a different space-time voxel, and except for the current space-time point and the center of the target space grid, the space-time starting point and ending point of each segment are the space-time coordinates of the space-time trajectory entering and exiting the space-time voxel; the space-time trajectory tracking sequentially uses the space-time coordinates of the last space-time voxel passed through as the space-time starting point of the next space-time straight line segment, and calculates the space-time coordinates when passing through the space-time voxel in combination with the spatial movement direction, the space-time range of the space-time voxel, and the maximum speed of traveling in a specific direction in the space-time voxel until it reaches the space. Reach the center of the target space grid to obtain the space-time prism used to describe the reachable area of ​​the target object; use the space-time voxels to track the space-time trajectory of the task activity in the space-time comprehensive environmental impact model, and use the space-time coordinates of the space-time points where the task enters or passes through the space-time voxels to obtain the travel length and residence time in each space-time voxel on the space-time trajectory. The comprehensive environmental cost of the task execution plan is obtained through the cost growth rate of each space-time voxel passed by the space-time trajectory, the residence time in the corresponding space-time voxel, and the travel length; and the total cost accumulation value used to evaluate the pros and cons of the task activity plan is obtained based on the sum of the cost values ​​generated when the space-time trajectory passes through each space-time voxel; In the space-time path segment, the starting space-time point and the target space-time voxel center point are screened by adjusting the space-time voxel spatial interval, and the path between each starting space-time point and the corresponding screened target space-time voxel center point is used as a candidate path; For the candidate paths, the time interval is used as the calculation time period. Starting from the first time period, the calculation time period is used as the hierarchy. The minimum cost path between the starting space-time point and the target space-time voxel center point in all calculation time periods is found through hierarchical path search. The optimal path with the comprehensive threat cost between the start and end of the task activity is obtained based on the minimum cost path in all calculation time periods.

2. The spatiotemporal collaborative path search optimization method in task activity threat cost assessment according to claim 1 is characterized in that: The spatiotemporal comprehensive environmental impact model expands the time dimension on the basis of the law of spatial environmental cost, and uses the spatiotemporal coordinate system to record the cumulative growth rate of environmental cost during task execution caused by the environment, situation and capability factors of spatial points at different time points, wherein the spatiotemporal coordinate system establishes a three-dimensional rectangular coordinate system by determining a point on the surface as the origin, the eastward direction as the X-axis, the northward direction as the Y-axis, and time T as the vertical upward Z-axis, and uses the three-dimensional rectangular coordinate system as the spatiotemporal coordinate system.

3. The spatiotemporal collaborative path search optimization method in task activity threat cost assessment according to claim 1 is characterized in that: In adjusting the spatial interval of the space-time voxels, the spatial interval of the space-time voxels is increased by using equal-space sampling or reducing the space-time resolution of the space-time voxels.

4. The spatiotemporal collaborative path search optimization method in task activity threat cost assessment according to claim 1 is characterized in that: In adjusting the spatial interval of space-time voxels, an integer multiple of the spatial interval of space-time voxels is used as a mask reference length in the space of the space-time coordinate system, and the center point of the target space-time voxel is sampled using a mask method, and the spatial coordinates of the sampling point are recorded on the mask; the center point of the space-time voxel containing key position information is appended and recorded on the mask; the starting space-time point and the target voxel center point are selected only at the spatial position recorded in the mask to obtain a candidate path for space-time path search.

5. A spatiotemporal collaborative path search optimization system in task activity threat cost assessment, characterized in that: The method according to claim 1 is implemented, comprising: a region construction module, a node screening module and a path selection module, wherein: The regional construction module is used to rasterize the space-time comprehensive environmental impact model used to describe the law of space-time environmental impact within the range of the space-time prism that can be reached by the task in the space-time coordinate system, and use the space-time unit cubes divided by the same space and time interval along the coordinate axis of the space-time coordinate system as space-time voxels, and use the geometric center of the space-time voxels as nodes according to the time interval to connect the time points at different times through uniform linear motion to construct the space-time path segment; A node screening module is used to screen the target space-time voxel center point corresponding to the starting space-time point by adjusting the space-time voxel space interval within the space-time path section, and take the path between each starting space-time point and the corresponding screened target space-time voxel center point as a candidate path; The path selection module is used to select candidate paths, taking the time interval as the calculation time period, starting from the first time period, and taking the calculation time period as the hierarchy, to find the minimum cost path between the starting time-space point and the target time-space voxel center point in all calculation time periods through hierarchical path search, and obtain the optimal path with the comprehensive threat cost between the start and end of the task activity based on the minimum cost path in all calculation time periods.

6. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor performs the steps of the method according to any one of claims 1 to 4.

7. A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method according to any one of claims 1 to 4.

Images