Field path planning method and device based on earth surface model

Abstract

The embodiment of the invention provides a field path planning method and device based on a digital earth surface model. The field path planning method comprises the following steps: acquiring earth surface data in a field preset area; establishing a digital earth surface model according to the acquired earth surface data in the field preset area; and performing path planning on a preset starting point and a preset ending point by using a field path planning algorithm and utilizing the gradient data and the earth surface obstacle data of the digital earth surface model to obtain an optimal field path from the starting point to the ending point. The path in the field seismic exploration process is planned, so that the path searching process in the field environment is efficient, the resource waste in the seismic exploration process is reduced, and the seismic exploration time is saved.

Description

Technical Field

[0001] The present invention relates to the field of oil exploration, and particularly to a method and device for field path planning based on a surface model. Background Art

[0002] Field work is an important basic task in seismic exploration. Its basic task is to carry out field construction according to specific geological tasks, and to collect seismic data completely and accurately to prepare for data processing and data analysis in the next stage.

[0003] During the process of field work, route optimization plays a crucial role in improving production efficiency and reducing production costs. However, since people's current general activity range is in cities, most of the roads involved in current navigation software are urban roads, and there are deficiencies in the rarely visited wild areas. Therefore, there is an urgent need for a path planning method for the wild environment. Summary of the Invention

[0004] In view of the above problems, the present invention is proposed to provide a method and device for field path planning based on a surface model that overcomes the above problems or at least partially solves the above problems.

[0005] In a first aspect, an embodiment of the present invention provides a method for field path planning based on a digital surface model, including:

[0006] Collect surface data within a preset area in the wild.

[0007] Establish a digital surface model based on the collected surface data within the preset area in the wild.

[0008] Use a field path planning algorithm, and utilize the slope data and surface obstacle data of the digital surface model to perform path planning on a preset starting point and a preset ending point, and obtain the optimal field path between the starting point and the ending point.

[0009] In an embodiment, the step of using a field path planning algorithm, and utilizing the slope data and surface obstacle data of the digital surface model to perform path planning on a preset starting point and a preset ending point, and obtain the optimal field path between the starting point and the ending point includes:

[0010] Respectively use the preset starting point and the preset ending point as the starting point and the ending point of the optimal field path.

[0011] Divide the preset area in the wild into grids.

[0012] According to the slope data of the digital surface model, perform a binarization operation on the slope to obtain the binarized slope.

[0013] Determine impassable grids based on the surface obstacle data of the digital surface model and the binarized slope.

[0014] Create a first grid set and a second grid set; the second grid set contains the impassable grids, and the first grid set contains the reachable grids except the impassable grids.

[0015] Filter out the reachable grids within a preset range around the grid where the starting point of the path is located from the first grid set.

[0016] Calculate the sum of the costs from each of the reachable grids to the grid where the starting point of the path is located and to the grid where the ending point of the path is located respectively.

[0017] Determine the reachable grid with the minimum value of the sum of the costs as the current grid, delete the grids other than the current grid from the reachable grids in the first grid set, and add them to the second grid set.

[0018] Repeat the above operations until the current grid is the grid where the ending point of the path is located, and the path finding ends.

[0019] Connect the grids from the grid where the starting point of the path is located to the grid where the ending point of the path is located in order to form the optimal field path.

[0020] In one embodiment, between a preset starting point and a preset ending point, it further includes: at least one designated intermediate point; performing path planning for the preset starting point and the preset ending point to obtain the optimal field path between the starting point and the ending point, including:

[0021] Using a field path planning algorithm, using the slope data of the digital surface model to perform path planning in the order of the preset starting point, at least one of the intermediate points, and the preset ending point to obtain the optimal field path.

[0022] In one embodiment, the using the field path planning algorithm, using the slope data of the digital surface model to perform path planning in the order of the preset starting point, at least one of the intermediate points, and the preset ending point to obtain the optimal field path includes:

[0023] Divide the optimal field path to be generated into several sub - segments according to the preset starting point, the at least one intermediate point, and the preset ending point.

[0024] For each sub - segment, use the preset starting point and the intermediate point, or the intermediate point to the next intermediate point, or the intermediate point to the preset ending point as the starting point and the ending point of this sub - segment.

[0025] Calculate the optimal field path for each segment, and sequentially connect the sub - segments of all the optimal field paths experienced from the preset starting point to the preset ending point to obtain the optimal field path;

[0026] Each sub - segment of the optimal field path is obtained in the following way:

[0027] Divide the preset field area into grids;

[0028] According to the slope data of the digital surface model, perform a binarization operation on the slope to obtain the binarized slope;

[0029] Determine the impassable grids according to the surface obstacle data of the digital surface model and the binarized slope;

[0030] Create a first grid set and a second grid set; the second grid set contains the impassable grids, and the first grid set contains the reachable grids except the impassable grids;

[0031] Screen out the reachable grids within a preset range around the grid where the starting point of the sub - segment is located from the first grid set;

[0032] Calculate the sum of the costs of reaching the grid where the starting point of the sub - segment is located and the grid where the ending point of the sub - segment is located from each of the reachable grids respectively;

[0033] Determine the reachable grid with the minimum value of the sum of the costs as the current grid, delete the grids other than the current grid from the reachable grids in the first grid set, and add them to the second grid set;

[0034] Repeat the above operations until the current grid is the grid where the ending point of the sub - segment is located, and the path - finding ends;

[0035] Connect the grids from the grid where the starting point of the sub - segment is located to the grid where the ending point of the sub - segment is located in order to form the sub - segment optimal field path.

[0036] In one embodiment, the optimal field path includes: the optimal field path passable by humans, or the optimal field path passable by vehicles;

[0037] If the optimal field path is the optimal field path passable by humans, then the binarization operation on the slope includes:

[0038] Set the human - passable slope threshold range according to human passability; perform a binarization operation on the slope according to the human - passable slope threshold range;

[0039] If the optimal field path is the optimal field path passable by vehicles, then the binarization operation on the slope includes:

[0040] Set the vehicle passable slope threshold range according to the passability of the vehicle; perform binarization operation on the slope according to the vehicle passable slope threshold range.

[0041] In one embodiment, the wild path planning method based on the surface model further includes:

[0042] If data of newly added surface obstacles is collected, add the data of the newly added surface obstacles to the digital surface model according to the data of the newly added surface obstacles.

[0043] In a second aspect, an embodiment of the present invention provides a wild path planning device based on a surface model, including:

[0044] A collection module, configured to collect surface data within a preset wild area;

[0045] A model module, configured to establish a digital surface model according to the surface data within the preset wild area collected;

[0046] A path finding module, using a wild path planning algorithm, and using the slope data and surface obstacle data of the digital surface model to perform path planning on a preset starting point and a preset ending point, and obtaining the optimal wild path between the starting point and the ending point.

[0047] In one embodiment, the path finding module is specifically configured to:

[0048] Respectively use the preset starting point and the preset ending point as the starting point and the ending point of the optimal wild path; divide the preset wild area into grids; perform binarization operation on the slope according to the slope data of the digital surface model to obtain the binarized slope; determine the impassable grids according to the surface obstacle data of the digital surface model and the binarized slope; create a first grid set and a second grid set; the second grid set contains the impassable grids, and the first grid set contains the reachable grids except the impassable grids; screen out the reachable grids within a preset range around the grid where the starting point of the path is located from the first grid set; respectively calculate the sum of the costs from each reachable grid to the grid where the starting point of the path is located and to the grid where the ending point of the path is located; determine the reachable grid with the smallest value of the sum of the costs as the current grid, delete the reachable grids except the current grid from the first grid set, and add them to the second grid set; repeat the above operations until the current grid is the grid where the ending point of the path is located, and the path finding ends; connect in sequence from the grid where the starting point of the path is located to the grid where the ending point of the path to form the optimal wild path.

[0049] In one embodiment, the pathfinding module is further configured to divide the optimal wild path to be generated into several sub-segments according to the preset starting point, the at least one intermediate point, and the preset ending point; for each sub-segment, use the preset starting point and the intermediate point, or the intermediate point to the next intermediate point, or the intermediate point to the preset ending point, as the starting point and the ending point of the sub-segment; calculate the optimal wild path of each segment respectively, and connect the sub-segments of all the optimal wild paths experienced from the preset starting point to the preset ending point in sequence; obtain the optimal wild path; the optimal wild path of each sub-segment is obtained in the following manner: divide the preset wild area into grids; perform a binarization operation on the slope according to the slope data of the digital surface model to obtain the binarized slope; determine the impassable grids according to the surface obstacle data of the digital surface model and the binarized slope; create a first grid set and a second grid set; the second grid set contains the impassable grids, and the first grid set contains the reachable grids other than the impassable grids; screen out the reachable grids within a preset range around the grid where the starting point of the sub-segment is located from the first grid set; calculate the sum of the costs of reaching the grid where the starting point of the sub-segment is located and the grid where the ending point of the sub-segment is located from each of the reachable grids respectively; determine the reachable grid with the minimum value of the sum of the costs as the current grid, delete the reachable grids other than the current grid from the first grid set, and add them to the second grid set; repeat the above operations until the current grid is the grid where the ending point of the sub-segment is located, and the pathfinding ends; connect the grids from the grid where the starting point of the sub-segment is located to the grid where the ending point of the sub-segment is located in sequence to form the optimal wild path of the sub-segment.

[0050] In a third aspect, an embodiment of the present invention provides a computing device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the wild path planning method based on the surface model when executing the program.

[0051] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and the computer program implements the wild path planning method based on the surface model when executed by a processor.

[0052] The beneficial effects of the above technical solutions provided by the embodiments of the present invention at least include:

[0053] An embodiment of the present invention provides a method and device for field path planning based on a digital terrain model. The method includes collecting surface data within a preset field area; establishing a digital terrain model based on the collected surface data within the preset field area; using a field path planning algorithm to plan a path between a preset starting point and a preset ending point by utilizing the slope data and surface obstacle data of the digital terrain model, so as to obtain the optimal field path between the starting point and the ending point. The embodiment of the present invention can realize the automatic generation of passable paths in the field environment, make the seismic exploration process in the field environment more concise, efficiently find the exploration locations to be reached, reduce resource waste, and save the time consumed in the seismic exploration process.

[0054] Other features and advantages of the present invention will be described in the following specification, and will, in part, be obvious from the specification, or be learned by practicing the present invention. The objectives and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written specification, claims, and drawings.

[0055] The technical solutions of the present invention will be further described in detail below through the accompanying drawings and embodiments. Description of the Drawings

[0056] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, but do not constitute a limitation to the present invention. In the drawings:

[0057] Figure 1 is a flowchart of the method for field path planning based on a digital terrain model provided by an embodiment of the present invention;

[0058] Figure 2 is a path planning diagram with two intermediate points provided by an embodiment of the present invention;

[0059] Figure 3 is a diagram of a passable area with vehicle and pedestrian separation provided by an embodiment of the present invention;

[0060] Figure 4 is a path diagram of vehicle and pedestrian separation planning provided by an embodiment of the present invention;

[0061] Figure 5 is a diagram of an area with newly added obstacles provided by an embodiment of the present invention;

[0062] Figure 6 is a diagram of path planning according to newly added obstacles provided by an embodiment of the present invention;

[0063] Figure 7 is a structural block diagram of the device for field path planning based on a digital terrain model provided by an embodiment of the present invention. Detailed Embodiments

[0064] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art.

[0065] To solve the problem of detouring due to the complex field environment during seismic exploration described above, an embodiment of the present invention provides a field path planning method based on a digital surface model, and its flowchart is as Figure 1 described, including:

[0066] Step S11: Collect surface data within a preset field area;

[0067] Step S12: Establish a digital surface model according to the collected surface data within the preset field area;

[0068] Step S13: Use a field path planning algorithm, utilize the slope data and surface obstacle data of the digital surface model, perform path planning on the preset starting point and the preset ending point, and obtain the optimal field path between the starting point and the ending point.

[0069] In the above step S11, the surface data may include, for example: data of slope, aspect, surface roughness, and surface obstacles.

[0070] In step S12, the digital surface model may be, for example, a digital elevation model (DEM, Digital Elevation Model) and a digital surface model (DSM, Digital Surface Model); among them, the digital elevation model realizes the digital simulation of the ground terrain through limited terrain elevation data (that is, the digital expression of the terrain surface morphology), and is a kind of entity ground model representing the ground elevation in the form of an ordered numerical array; while the digital surface model is a ground elevation model including the heights of surface buildings, bridges, and trees, etc., and is a digital elevation model that further covers other surface information except the ground on the basis of the digital elevation model.

[0071] Specifically, according to the collected surface data within the preset field area, to establish a digital surface model, the following method can be adopted, for example:

[0072] Store the surface data of a series of sampling points within the preset field area in a computer in a discrete form according to certain rules to form a finite-term vector sequence. The aforementioned surface roughness data and surface obstacle data can be represented by coding or layering, for example.

[0073] In the embodiments of the present invention, the establishment of the digital surface model can be completed by using the existing technology, and the embodiments of the present invention do not limit this.

[0074] In the above step S13, using the field path planning algorithm, and using the slope data and surface obstacle data of the digital surface model, path planning is performed on the preset starting point and the preset ending point to obtain the optimal field path between the starting point and the ending point. The flowchart is as Figure 2 shown. For example, it can be performed in the following manner, including:

[0075] Step S21: Respectively use the preset starting point and the preset ending point as the starting point and the ending point of the optimal field path;

[0076] Step S22: Divide the preset field area into grids;

[0077] Step S23: According to the slope data of the digital surface model, perform a binarization operation on the slope to obtain the binarized slope;

[0078] Step S24: Determine the impassable grids according to the surface obstacle data of the digital surface model and the binarized slope;

[0079] Step S25: Create a first grid set and a second grid set; the second grid set contains the impassable grids, and the first grid set contains the reachable grids except the impassable grids;

[0080] Step S26: Screen out the reachable grids within a preset range around the grid where the starting point of the path is located from the first grid set;

[0081] Step S27: Calculate the sum of the costs of reaching the grid where the starting point of the path is located and the grid where the ending point of the path is located from each reachable grid respectively;

[0082] Step S28: Determine the reachable grid with the smallest value of the sum of the costs as the current grid, delete the grids other than the current grid from the reachable grids in the first grid set, and add them to the second grid set;

[0083] Repeat the above operations until the current grid is the grid where the ending point of the path is located, and the path finding ends;

[0084] Connect the grids from the grid where the starting point of the path is located to the grid where the ending point of the path is located in sequence to form the optimal field path.

[0085] In the above step S13, between the preset starting point and the preset ending point, it may further include: at least one designated intermediate point;

[0086] Accordingly, if there is at least one specified intermediate point, path planning is performed on the preset starting point and the preset ending point to obtain the optimal field path between the starting point and the ending point. For example, the following method can be used:

[0087] Use the field path planning algorithm, and perform path planning in the order of the preset starting point, at least one of the intermediate points, and the preset ending point using the slope data of the digital surface model to obtain the optimal field path.

[0088] Among them, the passing order between intermediate points can be, for example, in the order of the distance from the starting point, passing through in the order from near to far from the starting point; or the passing order can be selected according to requirements.

[0089] During the seismic exploration process, when some specific locations need to be passed through on the way to the ending point for operations, intermediate points will be artificially added; although intermediate points are added, the starting point and the ending point remain unchanged. Therefore, the aforementioned intermediate points can be regarded as points that must be passed through during the path planning of the starting point and the ending point.

[0090] Specifically, use the field path planning algorithm, and perform path planning in the order of the preset starting point, at least one intermediate point, and the preset ending point using the slope data of the digital surface model to obtain the optimal field path. The flowchart is as Figure 3 shown, including:

[0091] Step S31: Divide the optimal field path to be generated into several sub-segments according to the preset starting point, at least one intermediate point, and the preset ending point;

[0092] Step S32: For each sub-segment, use the preset starting point and intermediate point, or the intermediate point to the next intermediate point, or the intermediate point to the ending point as the starting point and ending point of this sub-segment;

[0093] Step S33: Calculate the optimal field path for each segment respectively, and connect the sub-segments of all the optimal field paths experienced from the preset starting point to the preset ending point in sequence; to obtain the optimal field path.

[0094] The sub-segments involved in the foregoing steps can be divided into three types according to the differences between their starting points and ending points:

[0095] A sub-segment with the preset starting point as the starting point and the intermediate point as the ending point;

[0096] A sub-segment with the intermediate point as the starting point and the intermediate point as the ending point;

[0097] A sub-segment with the intermediate point as the starting point and the preset ending point as the ending point.

[0098] Among them, the sub-segment with the intermediate point as the starting point and the intermediate point as the ending point is the case when there are more than two intermediate points.

[0099] Specifically, the optimal field path for each sub-segment can be obtained in the following manner:

[0100] Divide the preset field area into grids;

[0101] According to the slope data of the digital surface model, perform a binary operation on the slope to obtain the binary slope;

[0102] Determine the impassable grids based on the surface obstacle data of the digital surface model and the binary slope;

[0103] Create a first grid set and a second grid set; the second grid set contains the impassable grids, and the first grid set contains the reachable grids except the impassable grids;

[0104] Screen out the reachable grids within a preset range around the grid where the starting point of the sub-segment is located from the first grid set;

[0105] Calculate the sum of the costs of reaching the grid where the starting point of the sub-segment is located and the grid where the ending point of the sub-segment is located from each reachable grid respectively;

[0106] Determine the reachable grid with the minimum sum of cost values as the current grid, delete the grids other than the current grid among the reachable grids from the first grid set, and add them to the second grid set;

[0107] Repeat the above operations until the current grid is the grid where the ending point of the sub-segment is located, and the path finding ends; the optimal field path of the sub-segment is formed by sequentially connecting the grids from the grid where the starting point of the sub-segment is located to the grid where the ending point of the sub-segment is located.

[0108] In the embodiments of the present invention, passable can be divided into passable for humans and passable for vehicles. Passable for humans means the area that humans can pass through by means of climbing, etc.; passable for vehicles means the area that vehicles can reach under operation. The present invention needs to plan the optimal path for these two situations respectively.

[0109] The aforementioned sequential connection means using the ending point of the previous sub-segment as the starting point of the next sub-segment, thereby connecting the sub-segments in sequence;

[0110] Connect the optimal field paths of all sub-segments in sequence according to the above method to obtain the final optimal field path.

[0111] The above intermediate points can be, for example, Figure 2 operation points 1 and 2 in Figure 2 The preset starting point and ending point can be, for example, Figure 2The broken line in

[0112] In the above-mentioned method for outdoor path planning based on digital surface model, the cost of different paths can be, for example, Euclidean distance or Manhattan distance.

[0113] The above-mentioned optimal outdoor path can include, for example: the optimal outdoor path passable by people, or the optimal outdoor path passable by vehicles;

[0114] Correspondingly, if the optimal outdoor path is the optimal outdoor path passable by people, the following method can be used to perform binarization operation on the slope:

[0115] Set the threshold range of the slope passable by people according to the passability of people; perform binarization operation on the slope according to the threshold range of the slope passable by people;

[0116] If the optimal outdoor path is the optimal outdoor path passable by vehicles, the following method can be used to perform binarization operation on the slope:

[0117] Set the threshold range of the slope passable by vehicles according to the passability of vehicles; perform binarization operation on the slope according to the threshold range of the slope passable by vehicles.

[0118] When considering the slope, the aforementioned vehicle-passable threshold and the human-passable threshold, since people can perform activities such as rock climbing and uphill climbing, that is, the flexibility of people is higher than that of vehicles, so the threshold range of the slope passable by people will be larger than the threshold range of the vehicle-passable threshold.

[0119] The aforementioned binarization operation can be, for example:

[0120] Set the threshold range of binarization according to requirements, divide the image into two different colors according to the threshold range, one color is within the threshold range, and the color outside the threshold range is the other color. To make the difference obvious, for example, black and white can be selected to represent.

[0121] The regional map after performing binarization operation on the slope according to the threshold range of the slope passable by people can be referred to, for example, Figure 3 as shown in the figure on the left side of the boundary line. In Figure 3 it, the gray area is the obstacle area, the black area is the area impassable by people, and the white area is the area passable by people; the result after performing binarization operation on the slope according to the threshold range of the slope passable by vehicles can be referred to, for example, Figure 3 as shown in the figure on the right side of the boundary line. In Figure 3 it, the gray area is the obstacle area, the black area is the area impassable by vehicles, and the white area is the area passable by vehicles.

[0122] Correspondingly, after binarizing the slope passable by people, use the method for outdoor path planning based on surface model for Figure 4Path planning is carried out for the middle area, and the obtained path is referred to Figure 4 as shown in the left two figures in the middle, where the broken line inside the white circle is the optimal wild path that can be passed by people; correspondingly, after binarizing the vehicle-passable slope, the wild path planning method based on the surface model is used to Figure 4 carry out path planning for the middle area, and the obtained path is referred to Figure 4 as shown in the right two figures in the middle, where the broken line inside the black circle is the optimal wild path that can be passed by vehicles.

[0123] Due to the complex wild environment, obstacles may be missed during the process of collecting data in the early stage or new obstacles may appear when passing through a section. Therefore, new obstacles need to be added manually. In this way, for example, data of new obstacles can also be added in the above-mentioned wild path planning method based on the surface model. For example, the following method can be adopted:

[0124] If data of newly added surface obstacles is collected, according to the data of newly added surface obstacles, add the data of newly added surface obstacles in the digital surface model.

[0125] The above-mentioned adding the data of newly added surface obstacles in the digital surface model can be carried out in the following way, for example:

[0126] Determine the position of the newly added obstacle in the digital surface model according to the data of the newly added obstacle;

[0127] According to the data of the newly added obstacle, build a set of edge-passable range points in sequence along the edge of the newly added obstacle;

[0128] Build a base map;

[0129] Determine the obstacle and non-obstacle areas according to the edge-passable range points of the newly added obstacle;

[0130] Load the data of the digital surface model in the form of grids, take the elevation data of each grid as the value in the grid, and calculate the slope of each grid according to the values in each grid;

[0131] According to the position of the newly added obstacle in the digital surface model, the edge-passable range points, the base map, the obstacle area, the non-obstacle area, and the slope degree of each grid, use a tool to add the newly added obstacle area.

[0132] The above-mentioned tool can be OpenCV, for example.

[0133] As Figure 5 shown, the added obstacle area is the gray part in the figure, the white part in the figure is the non-obstacle area, and the black part is the area without change.

[0134] Correspondingly, after adding a new obstacle, perform the above-mentioned field path planning method based on the surface model, and the obtained path can be, for example, as Figure 6 shown.

[0135] Based on the same inventive concept, an embodiment of the present invention further provides a field path planning device based on a surface model, and its structural block diagram is as Figure 7 shown, including:

[0136] An acquisition module 71, configured to acquire surface data within a preset field area;

[0137] A model module 72, configured to establish a digital surface model according to the acquired surface data within the preset field area;

[0138] A path finding module 73, using a field path planning algorithm, and using the slope data and surface obstacle data of the digital surface model to perform path planning on a preset starting point and a preset ending point, and obtaining an optimal field path between the starting point and the ending point.

[0139] Based on the same inventive concept, an embodiment of the present invention further provides a field path planning device based on a surface model, and its path finding module is specifically configured to:

[0140] Respectively use the preset starting point and the preset ending point as the starting point and the ending point of the optimal field path; divide the preset field area into grids; perform a binarization operation on the slope according to the slope data of the digital surface model to obtain a binarized slope; determine non-passable grids according to the surface obstacle data of the digital surface model and the binarized slope; create a first grid set and a second grid set; the second grid set contains the non-passable grids, and the first grid set contains reachable grids other than the non-passable grids; screen out reachable grids within a preset range around the grid where the starting point of the path is located from the first grid set; calculate the sum of the costs of reaching the grid where the starting point of the path is located and the grid where the ending point of the path is located from each reachable grid respectively; determine the reachable grid with the smallest value of the sum of the costs as the current grid, delete grids other than the current grid from the reachable grids in the first grid set, and add them to the second grid set; repeat the above operations until the current grid is the grid where the ending point of the path is located, and the path finding ends; connect in sequence from the grid where the starting point of the path is located to the grid where the ending point of the path to form the optimal field path.

[0141] Based on the same inventive concept, an embodiment of the present invention further provides a field path planning device based on a surface model, and its path finding module is further configured to:

[0142] According to the preset starting point, the at least one intermediate point, and the preset ending point, divide the optimal wild path to be generated into several sub-segments; for each sub-segment, use the preset starting point and the intermediate point, or from the intermediate point to the next intermediate point, or from the intermediate point to the preset ending point, as the starting point and the ending point of this sub-segment; calculate the optimal wild path of each segment respectively, and connect the sub-segments of all the optimal wild paths experienced from the preset starting point to the preset ending point in sequence; obtain the optimal wild path; the optimal wild path of each sub-segment is obtained in the following way: divide the preset wild area into grids; according to the slope data of the digital surface model, perform a binarization operation on the slope to obtain the binarized slope; determine the impassable grids according to the surface obstacle data of the digital surface model and the binarized slope; create a first grid set and a second grid set; the second grid set contains the impassable grids, and the first grid set contains the reachable grids except the impassable grids; screen out the reachable grids within a preset range around the grid where the starting point of the sub-segment is located from the first grid set; calculate the sum of the costs of reaching the grid where the starting point of the sub-segment is located and the grid where the ending point of the sub-segment is located from each of the reachable grids respectively; determine the reachable grid with the minimum value of the sum of the costs as the current grid, delete the reachable grids except the current grid from the first grid set, and add them to the second grid set; repeat the above operations until the current grid is the grid where the ending point of the sub-segment is located, and the path finding ends; connect the grids from the grid where the starting point of the sub-segment is located to the grid where the ending point of the sub-segment is located in sequence to form the optimal wild path of the sub-segment.

[0143] Based on the same inventive concept, an embodiment of the present invention further provides a computing device, which is characterized by including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, it implements the wild path planning method based on the surface model as described above.

[0144] Based on the same inventive concept, an embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the wild path planning method based on the surface model as described above.

[0145] An embodiment of the present invention provides a method and device for field path planning based on a digital surface model, including: collecting surface data within a preset field area; establishing a digital surface model according to the collected surface data within the preset field area; using a field path planning algorithm, and utilizing the slope data and surface obstacle data of the digital surface model to perform path planning for a preset starting point and a preset ending point, so as to obtain the optimal field path between the starting point and the ending point. This makes the seismic exploration process in the field environment more concise, can efficiently find the exploration locations to be reached, reduces resource waste, and saves the time consumed in the seismic exploration process.

[0146] Since the principles of the problems solved by these devices are similar to those of the aforementioned field path planning method based on the surface model, the implementation of this device can refer to the implementation of the aforementioned method, and the repeated parts will not be elaborated.

[0147] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0148] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram can be realized by computer program instructions, and the combination of the processes and / or blocks in the flowchart and / or block diagram can also be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0149] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including an instruction device, and the instruction device realizes the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0150] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so as to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing steps for implementing the functions specified in one process or a plurality of processes and / or boxes in the flow Figure 1 one process or a plurality of processes and / or boxes Figure 1 steps for implementing the functions specified in one box or a plurality of boxes. Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A method for field path planning based on a digital surface model, characterized in that, Including: Collecting surface data within a preset outdoor area; Establishing a digital surface model based on the collected surface data within the preset outdoor area; Using an outdoor path planning algorithm, and utilizing the slope data and surface obstacle data of the digital surface model to perform path planning for a preset starting point and a preset ending point, so as to obtain the optimal outdoor path between the starting point and the ending point.

2. The method according to claim 1, characterized in that, The step of using an outdoor path planning algorithm, and utilizing the slope data and surface obstacle data of the digital surface model to perform path planning for a preset starting point and a preset ending point, so as to obtain the optimal outdoor path between the starting point and the ending point includes: Respectively taking the preset starting point and the preset ending point as the starting point and the ending point of the optimal outdoor path; Dividing the preset outdoor area into grids; Performing a binarization operation on the slope according to the slope data of the digital surface model to obtain a binarized slope; Determining impassable grids according to the surface obstacle data of the digital surface model and the binarized slope; Creating a first grid set and a second grid set; the second grid set contains the impassable grids, and the first grid set contains reachable grids other than the impassable grids; Screening out the reachable grids within a preset range around the grid where the starting point of the path is located from the first grid set; Respectively calculating the sum of the costs of reaching the grid where the starting point of the path is located and the grid where the ending point of the path is located from each of the reachable grids; Determining the reachable grid with the minimum value of the sum of the costs as the current grid, deleting the grids other than the current grid from the reachable grids in the first grid set, and adding them to the second grid set; Repeating the above operations until the current grid is the grid where the ending point of the path is located, and the path finding ends; Sequentially connecting from the grid where the starting point of the path is located to the grid where the ending point of the path forms the optimal outdoor path.

3. The method according to claim 1, characterized in that, Between the preset starting point and the preset ending point, it further includes: at least one designated intermediate point; the step of performing path planning for the preset starting point and the preset ending point to obtain the optimal outdoor path between the starting point and the ending point includes: Using an outdoor path planning algorithm, and performing path planning in the order of the preset starting point, at least one of the intermediate points, and the preset ending point using the slope data of the digital surface model to obtain the optimal outdoor path.

4. The method according to claim 3, characterized in that, The step of using an outdoor path planning algorithm, and performing path planning in the order of the preset starting point, at least one of the intermediate points, and the preset ending point using the slope data of the digital surface model to obtain the optimal outdoor path includes: Dividing the optimal outdoor path to be generated into several sub-segments according to the preset starting point, the at least one intermediate point, and the preset ending point; For each sub-segment, taking the preset starting point and the intermediate point, or the intermediate point to the next intermediate point, or the intermediate point to the preset ending point as the starting point and the ending point of the sub-segment; Respectively calculating the optimal outdoor path for each segment, and sequentially connecting the sub-segments of all the optimal outdoor paths experienced from the preset starting point to the preset ending point; to obtain the optimal outdoor path; Each optimal field path for each sub-segment is obtained in the following manner: Divide the preset field area into grids; According to the slope data of the digital surface model, perform a binary operation on the slope to obtain the binary slope; Determine the impassable grids according to the surface obstacle data of the digital surface model and the binary slope; Create a first grid set and a second grid set; the second grid set contains the impassable grids, and the first grid set contains the reachable grids except the impassable grids; Select, from the first grid set, the reachable grids within a preset range around the grid where the starting point of the sub-segment is located; Calculate the sum of the costs of reaching the grid where the starting point of the sub-segment is located and the grid where the ending point of the sub-segment is located from each of the reachable grids; Determine the reachable grid with the minimum value of the sum of the costs as the current grid, delete the grids other than the current grid from the reachable grids in the first grid set, and add them to the second grid set; Repeat the above operations until the current grid is the grid where the ending point of the sub-segment is located, and the path finding ends; Connect in sequence from the grid where the starting point of the sub-segment is located to the grid where the ending point of the sub-segment is located to form the optimal field path for the sub-segment.

5. The method according to any one of claims 2-4, characterized in that, The optimal field path includes: the optimal field path passable by people, or the optimal field path passable by vehicles; If the optimal field path is the optimal field path passable by people, then the binary operation on the slope includes: Set the human-passable slope threshold range according to the passability of people; perform a binary operation on the slope according to the human-passable slope threshold range; If the optimal field path is the optimal field path passable by vehicles, then the binary operation on the slope includes: Set the vehicle-passable slope threshold range according to the passability of vehicles; perform a binary operation on the slope according to the vehicle-passable slope threshold range.

6. The method according to claim 1, wherein The method for planning a field path based on a surface model further includes: If data on newly added surface obstacles is collected, then add the data on the newly added surface obstacles to the digital surface model according to the data on the newly added surface obstacles.

7. A field path planning device based on a surface model, wherein It includes: A collection module for collecting surface data within a preset field area; A model module for establishing a digital surface model according to the collected surface data within the preset field area; A path finding module that uses a field path planning algorithm and utilizes the slope data and surface obstacle data of the digital surface model to perform path planning for a preset starting point and a preset ending point, and obtain the optimal field path between the starting point and the ending point.

8. The device according to claim 7, wherein Specifically, the path finding module is used to use the preset starting point and the preset ending point as the starting point and the ending point of the optimal field path respectively; divide the preset field area into grids; according to the slope data of the digital surface model, perform a binary operation on the slope to obtain the binary slope; Determine the impassable grids according to the surface obstacle data of the digital surface model and the binary slope; Create a first grid set and a second grid set; the second grid set contains the impassable grids, and the first grid set contains the reachable grids except the impassable grids; Filter out the reachable grids within a preset range around the grid where the starting point of the path is located from the first grid set; calculate the sum of the costs of reaching the grid where the starting point of the path is located and the grid where the ending point of the path is located from each of the reachable grids respectively; determine the reachable grid with the minimum value of the sum of the costs as the current grid, delete the grids other than the current grid from the reachable grids in the first grid set, and add them to the second grid set; repeat the above operations until the current grid is the grid where the ending point of the path is located, and the path finding ends; connect the grids from the grid where the starting point of the path is located to the grid where the ending point of the path is located in sequence to form the optimal wild path.

9. The device according to claim 7, wherein The path finding module is further configured to: According to the preset starting point, the at least one intermediate point, and the preset ending point, divide the to-be-generated optimal wild path into several sub-segments; for each sub-segment, use the preset starting point and the intermediate point, or the intermediate point to the next intermediate point, or the intermediate point to the preset ending point, as the starting point and the ending point of this sub-segment; Calculate the optimal wild path of each segment respectively, and connect the sub-segments of all the optimal wild paths experienced from the preset starting point to the preset ending point in sequence; obtain the optimal wild path; the optimal wild path of each sub-segment is obtained in the following manner: divide the preset wild area into grids; perform a binarization operation on the slope according to the slope data of the digital surface model to obtain the binarized slope; determine the impassable grids according to the surface obstacle data of the digital surface model and the binarized slope; Create a first grid set and a second grid set; the second grid set contains the impassable grids, and the first grid set contains the reachable grids except the impassable grids; Filter out the reachable grids within a preset range around the grid where the starting point of the sub-segment is located from the first grid set; calculate the sum of the costs of reaching the grid where the starting point of the sub-segment is located and the grid where the ending point of the sub-segment is located from each of the reachable grids respectively; determine the reachable grid with the minimum value of the sum of the costs as the current grid, delete the grids other than the current grid from the reachable grids in the first grid set, and add them to the second grid set; repeat the above operations until the current grid is the grid where the ending point of the sub-segment is located, and the path finding ends; connect the grids from the grid where the starting point of the sub-segment is located to the grid where the ending point of the sub-segment is located in sequence to form the optimal wild path of the sub-segment.

10. A computing device, wherein Comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, it implements the method for planning a wild path based on a surface model according to any one of claims 1-6.

11. A computer-readable storage medium, wherein The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the method for outdoor path planning based on a surface model according to any one of claims 1-6.

Images