A flight path planning system for aircraft

Abstract

A flight path planning system for an aircraft, comprising: a geographic information collection module for extracting geographic information within a flyable range from a geographic information system; a meteorological information collection module for extracting meteorological information within the flyable range from a meteorological information system; a multi-layer map generation module for generating a multi-layer planning map based on the geographic information and meteorological information within the flyable range; the map information of each layer including the traffic type and traffic cost multiplier of each traffic node in the map of that layer; a path planning module for calculating the optimal path from the starting point to the target point based on the positions of the flight starting point and the target point and adopting an improved path planning algorithm to obtain a planned flight path for the aircraft; a storage unit for storing the planned flight path for the aircraft; and a display unit for displaying the flight path of the aircraft from the starting point to the target point.

Description

Technical Field

[0001] The present invention relates to the technical field of path planning, and in particular to a flight path planning system for an aircraft. Background Art

[0002] Obstacles that block access are obstacles that are impossible to traverse directly. These include natural obstacles like cliffs and mountains, as well as man-made obstacles like buildings and road controls. The only way to navigate these obstacles is to detour, which also increases the cost of the route. Obstacles that slow access are obstacles that significantly reduce the speed of travel. These include natural obstacles like rivers and swamps, as well as man-made obstacles like speed limits and flow restrictions. These obstacles can reduce travel efficiency and even change the method of travel, such as switching from land to water. In particular, when the cost of slowing access increases excessively, slowing access can be considered part of the obstruction category, as it also results in a detour.

[0003] In the existing flight path determination methods, only obstacles that hinder passage are considered, that is, "detours" are required when encountering obstacles, and relevant considerations of obstacles that mitigate passage are missing. When obstacles that mitigate passage are introduced, the increased cost of "detours" may far exceed the cost of "crossing" complex obstacles; at the same time, the existing path determination methods are all limited to the two-dimensional plane, that is, they do not consider height dimension or hierarchical dimension information. For example, in reality, there is no ascent or descent, and in the virtual world, it is manifested as a lack of Z-axis information, that is, height information. The lack of dimensional information will inevitably reduce the flexibility and optimality of path planning. Summary of the Invention

[0004] In view of the above analysis, an embodiment of the present invention aims to provide a flight path planning system for an aircraft to solve the problem that the existing path planning method only considers obstacles that hinder passage and lacks altitude information, resulting in low flexibility in path planning and inability to accurately find the optimal path.

[0005] In one aspect, an embodiment of the present invention provides a flight path planning system for an aircraft, comprising:

[0006] Geographic information acquisition module, used to extract geographic information within the flight range from the geographic information system;

[0007] Meteorological information collection module, used to extract meteorological information within the flight range from the meteorological information system;

[0008] A multi-layer map generation module is used to generate a multi-layer planning map based on geographic information and meteorological information within the flight range; each layer of map information includes the traffic type and traffic cost multiplier of each traffic node in the map layer; the traffic types include normal traffic type, slowed traffic type and obstructed traffic type;

[0009] a path planning module, configured to calculate an optimal path from the starting point to the target point based on the locations of the flight starting point and the target point and adopt an improved path planning algorithm based on the multi-layer planning map to obtain a planned flight path for the aircraft;

[0010] A storage unit, used to store a planned flight path of an aircraft;

[0011] The display unit is used to display the flight path of the aircraft from the starting point to the target point.

[0012] Based on the further improvement of the above technical solution, the display unit is used to fuse the flight path into a three-dimensional flight scene according to the position information of each pass node in the flight path, and display the fused three-dimensional flight path.

[0013] Furthermore, the multi-layer map generation module includes:

[0014] A hierarchical segmentation module is used to vertically segment the three-dimensional space within the flight range to form multiple segmentation layers;

[0015] Grid division module, used to perform grid division in each segmentation layer, with one grid block being a pass node;

[0016] The map generation module is used to mark the traffic type and traffic cost multiplier of each traffic node according to the geographical information and meteorological information corresponding to each traffic node, and obtain a multi-layer planning map.

[0017] Furthermore, the map generation module obtains a multi-layer planning map in the following manner, including:

[0018] If the geographical information corresponding to the current pass node contains mountains or buildings, the current pass node will be marked as a pass-blocking type; otherwise:

[0019] If the meteorological information corresponding to the current pass node contains clouds, the pass type and pass cost multiplier of the current pass node are determined according to the cloud type and cloud map information;

[0020] Otherwise, mark the current pass node as a normal pass type.

[0021] Furthermore, the path planning module calculates the optimal path from the starting point to the target point by:

[0022] S21, putting the starting point into the intention node set;

[0023] S22. Select the node with the smallest total cost value in the intention node set as the current parent node, and move the current parent node to the visited node set and the planned node set;

[0024] S23. Based on the travel type and travel cost multiplier of each node, calculate the total cost of the nodes in the neighboring nodes of the current parent node that are not in the visited node set and are not classified as blocking travel; add the nodes in the neighboring nodes of the current parent node that are not in the visited node set and are not classified as blocking travel to the set of intended nodes; the total cost of a node is the sum of the cost of the path from the starting point to the current node via the parent node and the estimated cost from the current node to the target node;

[0025] S24. If the target node is included in the neighboring nodes of the current parent node, the target node is moved to the visited node set and the planned node set; in the planned node set, the optimal path is found based on the parent-child relationship between the nodes;

[0026] S25. Otherwise, return to step S22.

[0027] Furthermore, the path planning module adds nodes that are not in the visited node set and are not obstructing traffic from the neighboring nodes of the current parent node to the intended node set in the following manner:

[0028] For each neighboring node p of the current node that is not in the visited node set and is not a blocking node i (x,y):

[0029] If the node p i (x,y) is not in the intended node set, then directly add node p i (x,y) is added to the intention node set, and node p is recorded i (x,y) total cost, path cost, estimated cost and p i The parent node of (x,y) is the current parent node;

[0030] If the node p i (x,y) is already in the intended node set, then if the node p calculated based on the current parent node i The path cost of (x,y) is less than the node p recorded in the intention node set i The estimated cost of (x, y) is to set the node p in the intention node set i The parent node of (x,y) updates the current parent node and sets p i The total cost and path cost of (x,y) are updated to the total cost and path cost calculated based on the current parent node, respectively.

[0031] Furthermore,

[0032] When the neighboring nodes are on the same layer as the target node, the estimated cost is calculated using the following formula:

[0033] When the neighboring nodes and the target node are in different layers, the estimated cost is calculated using the following formula:

[0034] in, D m =|x c -x e |+|y c -y e |,λ represents the cost of crossing a unit distance, (x c ,y c ) represents the plane coordinates of the adjacent nodes, (x e ,y e ) represents the plane coordinates of the target node, w1 and w2 represent weight coefficients, d represents the inter-layer switching cost, i represents the sequence number of the layer where the neighboring node is located, and j represents the sequence number of the layer where the target node is located.

[0035] Furthermore,

[0036] If the neighboring node is on the same layer as the parent node, the path cost is calculated using the following formula

[0037] If the neighboring node and the parent node are in different layers, the path cost is calculated using the following formula

[0038] in, represents the path cost of the parent node at the i-th layer, Represents the path cost of the parent node at the jth layer. If the parent node is the starting node, the path cost of the parent node is 0. represents the path cost of the neighboring node at the i-th layer, d represents the inter-layer switching cost, Represents the cost from the parent node to the adjacent node.

[0039] Furthermore,

[0040] According to the formula Calculate the cost from the parent node to the neighboring node

[0041] Among them, l represents the travel cost multiplier of the adjacent node, λ represents the cost value of crossing the unit distance, (x c ,y c) represents the plane coordinates of the adjacent nodes, (x f ,y f ) represents the plane coordinates of the parent node.

[0042] Furthermore, in the planning node set, the planning path is found based on the parent-child relationship between nodes, including:

[0043] S241, taking the target node as the current node;

[0044] S242, adding the current node to the path node set; if the current node is the starting node, then stop searching, and the node sequence in the path node set is the planned path;

[0045] S243. Otherwise, search for the parent node of the current node in the planned node set, take the parent node of the current node as the current node, and return to step S242.

[0046] Compared with the existing technology, the present invention takes the dimensional information of height into consideration and divides the traffic type into normal traffic type, slowed traffic type and obstructed traffic type. Therefore, path planning is no longer just a detour. Path planning in the Z-axis space can also be considered, so that different types of obstacles can be flexibly avoided and better paths can be selected at different levels, making the optimal path result more accurate. This method is more adaptable to environments with obstacles and has a shorter path cost at the planned location.

[0047] In the present invention, the above-mentioned technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of the present invention will be described in the following description, and some advantages will become apparent from the description or be learned through practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the contents particularly pointed out in the description and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings are only for the purpose of illustrating particular embodiments and are not to be considered limiting of the present invention. Like reference symbols denote like parts throughout the drawings.

[0049] Figure 1 A block diagram of a flight path planning system for an aircraft according to an embodiment of the present invention;

[0050] Figure 2 A schematic diagram of a low-level map in a multi-level map according to an embodiment of the present invention;

[0051] Figure 3 A schematic diagram of a high-level map in a multi-level map according to an embodiment of the present invention;

[0052] Figure 4This is a schematic diagram of the path planning result of only a single-layer map in an embodiment of the present invention;

[0053] Figure 5 A schematic diagram of a low-level path in a path planning result of a multi-layer map in an embodiment of the present invention;

[0054] Figure 6 A schematic diagram of a high-level path in a path planning result of a multi-layer map in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, and are not used to limit the scope of the present invention.

[0056] A specific embodiment of the present invention discloses a flight path planning system for an aircraft, such as Figure 1 As shown, it includes the following modules:

[0057] The geographic information acquisition module is used to extract geographic information within the flight range from the geographic information system. For example, the geographic elevation data within the flight range, including terrain information and terrain height information, is extracted from the geographic information system.

[0058] The meteorological information acquisition module is used to extract meteorological information within the flight range from the meteorological information system. For example, meteorological cloud map information is obtained from meteorological satellite systems or ground observation stations. The meteorological cloud map information includes cloud type, cloud distribution range, and cloud droplet concentration.

[0059] A multi-layer map generation module is used to generate a multi-layer planning map based on geographic information and meteorological information within the flight range; each layer of map information includes the traffic type and traffic cost multiplier of each traffic node in the map layer; the traffic types include normal traffic type, slowed traffic type and obstructed traffic type;

[0060] a path planning module, configured to calculate an optimal path from the starting point to the target point based on the locations of the flight starting point and the target point and adopt an improved path planning algorithm based on the multi-layer planning map to obtain a planned flight path for the aircraft;

[0061] A storage unit, used to store a planned flight path of an aircraft;

[0062] The display unit is used to display the flight path of the aircraft from the starting point to the target point.

[0063] By taking the Z-axis dimensional information into consideration and classifying the traffic type into normal traffic type, slowed traffic type and obstructed traffic type, path planning is no longer just a detour. Path planning in the Z-axis space can also be considered, so that different types of obstacles can be flexibly avoided and better paths can be selected at different levels, making the optimal path result more accurate. This method is more adaptable to environments with obstacles and has a shorter path cost at the planned location.

[0064] Specifically, the multi-layer map generation module includes:

[0065] A hierarchical segmentation module is used to vertically segment the three-dimensional space within the flight range to form multiple segmentation layers;

[0066] For single-level path planning tasks, the task plane can be abstracted into a two-dimensional plane. This plane is then segmented, with each block acting as a traversable node. Based on the nature of the block, it is labeled as either a traversable area or an obstacle area. For example, if a 2km×2km area is abstracted, and to ensure consistency and proportionality in length and width, a 100m×100m area is assumed, then X=20 and Y=20.

[0067] For three-dimensional path planning tasks, it is necessary to first divide the space on the Z axis to obtain different segmentation layers. Each segmentation layer can be abstracted as a two-dimensional plane.

[0068] Grid division module, used to perform grid division in each segmentation layer, where one grid block is a pass node;

[0069] The grid partitioning module divides each layer according to a uniform segmentation scale, with each block representing a traversable node. For example, if the three-dimensional space is 300 km long and wide, with a height of 100 meters per layer, the three-dimensional space is divided into layers. Each layer is divided into 100m × 100m areas, i.e., each layer is grid-divided, with each grid block representing a traversable node.

[0070] The map generation module is used to mark the traffic type and traffic cost multiplier of each traffic node according to the geographical information and meteorological information corresponding to each traffic node, and obtain a multi-layer planning map.

[0071] According to the properties of the area block, the type of the area block and the traffic cost multiplier are marked to obtain multi-layer map information, wherein the type of the area block includes normal traffic type, slowed traffic type and obstructed traffic type.

[0072] During implementation, the path planning is aviation path planning, which can obtain geographic information and meteorological information in the three-dimensional flight space.

[0073] For example, geographic elevation data within the flight range can be extracted from the geographic information system, and meteorological cloud map information can be obtained from the meteorological satellite system or ground observation station. The meteorological cloud map information includes cloud type, cloud distribution range, and infrared cloud map.

[0074] Clouds are divided into three families and ten genera, as shown in Table 1.

[0075] Table 1 Cloud classification

[0076]

[0077] Specifically, the map generation module obtains a multi-layer planning map in the following manner, including:

[0078] If the geographical information corresponding to the current pass node contains mountains or buildings, the current pass node will be marked as a pass-blocking type; otherwise:

[0079] If the meteorological information corresponding to the current pass node contains clouds, the pass type and pass cost multiplier of the current pass node are determined according to the cloud type and cloud map information;

[0080] Otherwise, mark the current pass node as a normal pass type.

[0081] That is, for each pass node, it is determined based on geographic information whether the pass node contains mountains or buildings. If so, the current pass node is marked as a pass-blocking type.

[0082] If it does not include mountains and buildings, the meteorological information is used to determine whether the current pass node contains clouds. If so, the pass type and pass cost multiplier of the current pass node are determined based on the cloud type and cloud map information.

[0083] For example, if the cloud type belongs to the middle cloud family, the current pass node is marked as a blocking pass type. If it does not belong to the middle cloud family, the pass type and pass cost multiplier of the current pass node are determined based on the cloud map information.

[0084] During implementation, the cloud image is a satellite image, which is grayscale. Higher grayscale values, or whiter pixels, indicate thicker clouds or heavier water vapor, and thus higher travel costs. Therefore, the type of the current travel node can be determined based on the grayscale value of the satellite image.

[0085] For example, for a satellite cloud image with a grayscale value range of 0-255, if the average grayscale value within the current passage node range is in the range of 0-39, the cloud cover is very small and the passage cost is close to that of a cloudless state, so it is marked as a normal passage type; if the average grayscale value is in the range of 201-255, the cloud cover is heavy and the passage is greatly obstructed, so it is marked as an obstructed passage type; if the average grayscale value is in the range of 40-200, it is marked as a slowed passage type, and the passage cost multiplier = (average grayscale value) / 40 + the passage cost multiplier of the normal passage type.

[0086] If there are no mountains, buildings or clouds in the current pass node, the current pass node will be marked as a normal pass type.

[0087] The embodiment of the present application divides node types into considerations of the obstruction of mountains, buildings and clouds to flight. During implementation, the same method can be used to divide the traffic nodes into traffic types according to the environment of the specific planned space.

[0088] The multi-layer map space is denoted as Where i represents the i-th layer map, and N represents the total number of layers. Each point in the i-th layer space time The coordinates of different area blocks in the corresponding space are the coordinates of the pass node. The area blocks can be either passable blocks or obstacle blocks. i (x,y) represents the type of the area block and the travel cost multiplier.

[0089]

[0090] Remember to satisfy L i The set of region blocks where (x,y)=Inf is The traversable area is H i =P i -B i .

[0091] For obstacles such as mountains, clouds, etc., the obstacles that hinder passage will change with the increase of vertical height, such as Figure 2 、 3 As shown, Figure 2 This is a schematic diagram of the obstacle situation at a lower level in a multi-layer map. Figure 3This is a diagram of obstacles in a multi-layer map. In the figure, black blocks (with coordinates) are nodes that block traffic, such as block (7,9). Gray blocks with numbers are nodes that slow traffic, with the numbers representing the cost multiplier. For example, the node with coordinates (11,2) has a cost multiplier of 3. White blocks without numbers are nodes that normally pass traffic, with a default cost multiplier of 1. The starting point is (1,1) and the destination point is (20,20). To ensure that the path does not exceed the boundary during the tracking process, the boundary is also considered an obstacle block with a cost of Inf. That is, the gray blocks in the border area of the figure are also nodes that block traffic.

[0092] Multi-level path planning is inevitable to reduce the total cost and can flexibly avoid different types of obstacles.

[0093] After obtaining the multi-layer map information, the path planning module calculates the optimal path from the starting point to the target point in the following manner.

[0094] First, define three sets T, V, and R to represent the target node set, the visited node set, and the route node set, respectively. Initially, these three sets are set to be empty sets.

[0095] The specific planning process is:

[0096] S21, putting the starting point into the intention node set;

[0097] S22. Select the node with the smallest total cost value in the intention node set as the current parent node, and move the current parent node to the visited node set and the planned node set;

[0098] When this step is executed for the first time, there is only the start node in the intended node set, so the start node is used as the parent node and the parent node is moved to the visited node set and the planned node set. That is, the parent node is deleted from the intended node set and added to the visited node set and the planned node set.

[0099] The path cost of the starting node is 0.

[0100] If the number of nodes in the intention node set is greater than 1, the nodes need to be sorted, and the node with the smallest total cost value is selected as the parent node based on the sorting result.

[0101] It should be noted that the total cost of a node is the sum of the cost of the path from the starting point to the current node via the parent node and the estimated cost of the path from the current node to the target node.

[0102] Specifically, in step S22, the node with the smallest total cost value is selected as the current parent node in the set of intended nodes, including:

[0103] Sort the nodes in the intention node set in ascending order of total cost value; if the total cost values of the nodes are the same, sort them in order of the estimated cost values from the nodes to the target node from the smallest to the largest; if the estimated cost values are the same, sort them in order from the last node to the first node in the intention node set, and take the first intention node after sorting as the current parent node.

[0104] In order to obtain the optimal path, first sort the nodes in the intention node set in ascending order of total cost value; if the total cost values of the nodes are the same, sort them in order from the estimated cost value of the nodes to the target node. If the estimated cost values are the same, in order to improve the calculation efficiency, sort them in the order from the last node to the first node when they join the intention node set.

[0105] The intention node that is ranked first after sorting is taken as the current parent node.

[0106] S23. Calculate the total cost of nodes in the neighboring nodes of the current parent node that are not in the visited node set and are not classified as obstructing the passage according to the passage type and passage cost multiplier of each node; add the nodes in the neighboring nodes of the current parent node that are not in the visited node set and are not classified as obstructing the passage to the set of intended nodes;

[0107] The neighboring nodes of the current parent node include the neighboring nodes in the same layer as the current parent node, and the neighboring nodes in the adjacent layers as the current parent node;

[0108] It should be noted that it is usually difficult for a moving object to rise or fall vertically. Therefore, in one embodiment of the present invention, the neighboring nodes of the current node do not include nodes in adjacent layers of the layer where the current parent node has the same x and y coordinates as the current parent node.

[0109] For example, the current parent node is Figure 2 The point (7,7) in the , its neighboring nodes include Figure 2 The 8 points around the midpoint (7,7) also include Figure 3 8 points around the midpoint (7,7).

[0110] According to the travel type and travel cost multiplier of each node, calculate the total cost value of the nodes in the neighboring nodes of the current parent node that are not in the visited node set and are not of the type that blocks travel.

[0111] For example, Figure 2 The middle node (6, 7) is a barrier that blocks access, so its total cost does not need to be calculated and it is not added to the intended node set. If the point (7, 8) is already in the visited node set, its total cost does not need to be calculated and it is not added to the intended node set.

[0112] For neighboring nodes that are not in the visited node set and are not obstructive to traffic, the total cost value needs to be calculated based on the current parent node.

[0113] First, the path cost is calculated based on the position relationship between the adjacent nodes and the parent node.

[0114] Specifically, if the neighboring node is on the same layer as the parent node, the path cost is calculated using the following formula:

[0115]

[0116] in, Represents the path cost of the parent node, i represents the sequence number of the layer where the parent node and the adjacent node are located. If the parent node is the starting node, the path cost of the parent node is 0; Represents the path cost of the adjacent nodes; Represents the cost from the parent node to the adjacent node.

[0117] That is, the path cost of a neighboring node is the sum of the path cost of the parent node and the cost from the parent node to the neighboring node.

[0118] If the neighboring node and the parent node are in different layers, the path cost is calculated using the following formula

[0119] in, represents the path cost of the parent node, i represents the sequence number of the layer where the adjacent node is located, j represents the sequence number of the layer where the parent node is located, and d represents the inter-layer switching cost.

[0120] Specifically, according to the formula Calculate the cost from the parent node to the neighboring node

[0121] Among them, l represents the travel cost multiplier of the adjacent node, λ represents the cost value of crossing the unit distance, (x c ,y c ) represents the plane coordinates of the adjacent nodes, (x f ,y f ) represents the plane coordinates of the parent node.

[0122] Then, the estimated cost is calculated based on the positional relationship between the neighboring nodes and the target point

[0123] Specifically, if the neighboring nodes are on the same layer as the target node, the estimated cost is calculated using the following formula:

[0124] If the neighboring nodes and the target node are in different layers, the estimated cost is calculated using the following formula:

[0125] in, D m =|x c -x e |+|y c -y e |,λ represents the cost of crossing adjacent nodes, (x c ,y c ) represents the plane coordinates of the adjacent nodes, (x e ,y e ) represents the plane coordinates of the target node, d represents the inter-layer switching cost, i represents the sequence number of the layer where the neighboring node is located, j represents the sequence number of the layer where the target node is located, w1 and w2 represent the weight coefficients, and

[0126] D o Denotes the Euler distance between two points, D m Represents the Manhattan distance between two points. Manhattan distance is directionally insensitive and typically yields a higher distance value than Euler distance. However, solutions with two identical paths but in opposite order may not be the shortest path. Furthermore, points equidistant from the target are perpendicular to the line connecting the two points, resulting in slower approach to the target. Euler distance has a clearer direction and higher approach efficiency, but is more prone to local optimality than Manhattan distance, especially when there are obstacles on the path that are concave. Combining Euler distance with Manhattan distance allows for faster approach to the target without being stuck in a local optimality for too long. Giving Manhattan distance a higher weight than Euler distance significantly improves the speed of escaping local optimality.

[0127] Total cost of neighboring nodes That is, the total cost is the sum of the path cost and the estimated cost.

[0128] After calculating the total cost of the neighboring nodes of the current parent node that are not in the visited node set and are not nodes that block passage, these neighboring nodes are added to the intended node set.

[0129] Therefore, the nodes in the intention node set carry the values of their total cost, path cost, and estimated cost as well as their corresponding parent nodes, which facilitates the subsequent determination of the path.

[0130] When adding a node that is not in the visited node set and is not a barrier to passage among the neighboring nodes of the current parent node to the intended node set, the following processing is required:

[0131] For each neighboring node p of the current node that is not in the visited node set and is not a blocking nodei (x,y):

[0132] If the node p i (x,y) is not in the intended node set, then directly add node p i (x,y) is added to the intention node set, and node p is recorded i (x,y) total cost, path cost, estimated cost and p i The parent node of (x,y) is the current parent node;

[0133] If the node p i (x,y) is already in the intended node set, then if the node p calculated based on the current parent node i The path cost of (x,y) is less than the node p recorded in the intention node set i The estimated cost of (x, y) is to set the node p in the intention node set i The parent node of (x,y) updates the current parent node and sets p i The total cost and path cost of (x,y) are updated to the total cost and path cost calculated based on the current parent node, respectively.

[0134] That is, if the neighboring nodes of the current parent node are already in the intended node set, then the total cost of the nodes already in the intended node and the total cost of the currently calculated neighboring nodes are used to determine whether to update the information of the nodes already in the intended node set.

[0135] Specifically, if node p i (x,y) is already in the intended node set, then if the adjacent node p calculated based on the current parent node i The total cost of (x,y) is less than the node p recorded in the intention node set i The total cost of (x, y), then, the node p recorded in the set i The total cost and path cost of (x, y) are updated to the total cost and path cost calculated based on the current parent node, and the node p is i The parent node of (x,y) is updated to the current parent node.

[0136] S24. If the target node is included in the neighboring nodes of the current parent node, the target node is moved to the visited node set and the planned node set; in the planned node set, the planned path is obtained by searching based on the parent-child relationship between the nodes;

[0137] If the target node is included in the neighboring nodes of the current parent node, after moving the target node to the visited node set and the planned node set, a path from the starting point to the target node exists in the planned node set. Therefore, the planned path can be found based on the parent-child relationship between the nodes in the planned node set.

[0138] Specifically, the planned path is found based on the parent-child relationship between nodes, including:

[0139] S241, taking the target node as the current node;

[0140] S242, adding the current node to the path node set; if the current node is the starting node, then stop searching, and the node sequence in the path node set is the planned path;

[0141] S243. Otherwise, search for the parent node of the current node in the planned node set, take the parent node of the previous node as the current node, and return to step S242.

[0142] That is, starting from the target node, search for the parent node of the node in sequence until the starting node is found, thereby obtaining the planned path.

[0143] S25. Otherwise, return to step S22.

[0144] If the target node is not included in the neighboring nodes of the current parent node, the process returns to step S22 to continue searching.

[0145] After obtaining the planned path from the starting point to the target point, the planned path can be saved in a storage unit. On the one hand, it is convenient to call when displaying, and on the other hand, it can be recommended first when there are the same starting and ending points.

[0146] Specifically, the display unit is used to fuse the flight path into a three-dimensional flight scene according to the position information of each passing node in the flight path, and display the fused three-dimensional flight path.

[0147] The 3D flight scene model can be constructed using various 3D modeling tools, and this application does not impose any restrictions. Since a transit node actually represents an area block in the xyz 3D coordinate system, the corresponding area in the 3D flight scene can be marked based on the transit node sequence in the flight path, thereby integrating the flight path into the 3D flight scene and displaying the fused 3D flight scene for subsequent viewing and analysis.

[0148] by Figure 2 、 3 The effect of the present invention is described by taking the two layers of map information in as an example. Figure 2 The map layer number is 1. Figure 3 The map layer number is 2, where the starting point is p 1 (1,1), the target point is p 1 (20,20), the cost of crossing the unit distance λ = 10, the inter-layer switching cost d = 5, w1 = 0.2, w2 = 0.8.

[0149] The following describes the planning process and effects of the multi-constraint multi-level path planning method of the present invention based on the above examples.

[0150] First, the starting point p 1 (1,1) is put into the intention node set.

[0151] Select the node with the smallest total value in the intention node set as the current parent node, that is, p 1 (1,1) is the current parent node, and p 1 (1,1) moves to the visited node set and the planned node set. At this time, the intended node set is empty.

[0152] Current parent node p 1 The nodes adjacent to (1,1) that are not in the visited node set and are not obstructive nodes include p 1 (1,2),p 1 (2,1),p 1 (2,2),p 2 (1,2),p 2 (2,1),p 2 (2,2),

[0153] According to the formula:

[0154]

[0155] or or

[0156] D m =|x c -x e |+|y c -y e |

[0157] Calculate the path cost, estimated cost, and total cost for each neighboring point:

[0158]

[0159]

[0160]

[0161] will p 1 (1,2),p 1 (2,1),p 1 (2,2),p 2 (1,2),p 2 (2,1),p 2 (2,2)Add the intention node set.

[0162] Since the target node is not included in the neighboring nodes of the current parent node, the node with the smallest total cost value is selected as the current parent node in the intention node section. 1 The total cost of (2,2) is the smallest, so it is used as the current parent node and p is calculated. 1 (2,2) will p 1 (2,2) Move to the visited node set and the planned node set.

[0163] Current parent node p 1 The nodes in the neighboring nodes of (2,2) that are not in the visited node set and are not obstructive nodes include p 1 (1,2),p 1 (1,3), p 1 (2,3), p 1 (3,3), p 1 (3,2),p 1 (3,1),p 1 (2,1),p 2 (1,1),p 2 (1,2),p 2 (1,3), p 2 (2,3), p 2 (3,3), p 2 (3,2),p 2 (3,1),p 2 (2,1). Calculate the path cost, estimated cost, and total cost for each neighboring point using the formula in step 23.

[0164] Since point p 1 (1,2),p 1 (2,1),p 2 (1,2),p 2 (2,1) is already in the set of intended nodes. 1 When (2,2) is the parent node, p 1 The path cost of (1,2) is 24, which is greater than the point p 1 (1,1) is the path cost when the parent node is the node, so the midpoint p in the set of intended nodes is 1 The parent node and cost information of (1,2) do not need to be updated. Similarly, the point p in the set of intended nodes 1 (2,1),p 2 (1,2),p 2 The parent node and cost information of (2,1) do not need to be updated.

[0165] will p 1 (1,3), p 1 (2,3), p 1(3,3), p 1 (3,2),p 1 (3,1),p 2 (1,1),p 2 (1,3), p 2 (2,3), p 2 (3,3), p 2 (3,2),p 2 (3,1)Add the intention node set.

[0166] And so on, the search continues until the neighboring node of the current parent node contains the target node, that is, the neighboring node contains the target point p 1 (20,20), move the target point to the visited node set and the planned node set. There must be a node in the planned node set that starts from the starting point p. 1 (1,1) to the target point p 1 The path (20,20).

[0167] Since the planning node set stores the parent node information of each node, the reverse query method can be used to query and obtain the target path.

[0168] Initially, the path node set is empty.

[0169] Point p 1 (20,20) is the current node.

[0170] Set the current point p 1 (20,20) is added to the path node set, and point p is obtained by querying in the planning node combination. 1 The parent node of (20,20) is point p 1 (19,19), with point p 1 (19,19) is the current point, add the current point to the path node set and query the current point p 1 The parent node of (19,19), and so on, until the starting point is found, and the starting point is added to the path node set. The path in the path node set is the optimal path from the starting point to the target point.

[0171] The existing technology only considers high-level information because it only plans the path on one plane. Figure 2 Perform path planning according to the method of steps S21-S25 of this application, and obtain a path from the starting point to the target point containing 27 grids (p 1 (1,1),p 1 (2,2),p 1 (3,3), p 1 (4,4),p 1 (5,5),p 1(6,6),p 1 (7,7),p 1 (8,7),p 1 (9,6), p 1 (10,6),p 1 (11,6),p 1 (12,6),p 1 (13,6),p 1 (14,7), p 1 (15,8),p 1 (16,9),p 1 (17,10),p 1 (18,11),p 1 (19,12), p 1 (20,13),p 1 (20,14),p 1 (20,15),p 1 (20,16),p 1 (20,17),p 1 (20,18),p 1 (19,19), p 1 (20,20)), such as Figure 4 It should be noted that, since there is only one map layer, the neighboring nodes of the current parent node in step S23 only include the nodes in the same layer that are adjacent to the parent node.

[0172] In the form of a layered map, the path planning is performed according to the method of steps S21-S25 of this application, and the planning result is p 1 (1,1),p 1 (2,2),p 1 (3,3),p 1 (4,4),p 1 (5,5),p 1 (6,6),p 1 (7,7),p 2 (8,8), p 2 (9,9), p 2 (9,10), p 2 (10,11),p 2 (11,12),p 2 (12,13),p 1 (13,12), p 1 (13,13),p 2 (14,14),p 1 (15,15),p 1 (16,15),p 1 (17,16),p1 (18,17), p 1 (19,18), p 1 (19,19), p 1 (20,20). The planning results of the low-level and high-level are respectively Figure 5 、 Figure 6 It can be seen that using a multi-layer map can obtain a shorter path planning result.

[0173] The above method embodiment and system embodiment are based on the same principle, and their related parts can be used for reference, and can achieve the same technical effect. The specific implementation process can be found in the above embodiment and will not be repeated here.

[0174] Those skilled in the art will appreciate that all or part of the process steps of the above-described embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, such as a magnetic disk, an optical disk, a read-only memory, or a random access memory.

[0175] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with this technical field within the technical scope disclosed by the present invention should be covered by the scope of protection of the present invention.

Claims

1. A flight path planning system for an aircraft, characterized in that: include: Geographic information acquisition module, used to extract geographic information within the flight range from the geographic information system; Meteorological information collection module, used to extract meteorological information within the flight range from the meteorological information system; A multi-layer map generation module is used to generate a multi-layer planning map based on geographic information and meteorological information within the flight range; the planning map information of each layer includes the traffic type and traffic cost multiplier of each traffic node in the planning map of that layer; the traffic type includes normal traffic type, slowed traffic type and obstructed traffic type; a path planning module, configured to calculate an optimal path from the starting point to the target point based on the locations of the flight starting point and the target point and adopt an improved path planning algorithm based on the multi-layer planning map to obtain a planned flight path for the aircraft; A storage unit, used to store a planned flight path of an aircraft; A display unit is used to display the flight path of the aircraft from the starting point to the target point; The multi-layer map generation module includes: A hierarchical segmentation module is used to vertically segment the three-dimensional space within the flight range to form multiple segmentation layers; Grid division module, used to perform grid division in each segmentation layer, where one grid block is a pass node; A map generation module is used to mark the traffic type and traffic cost multiplier of each traffic node according to the geographical information and meteorological information corresponding to each traffic node, and obtain a multi-layer planning map; The path planning module calculates the optimal path from the starting point to the target point by: S21, putting the starting point into the intention node set; S22. Select the node with the smallest total cost value in the intention node set as the current parent node, and move the current parent node to the visited node set and the planned node set; S23. Based on the travel type and travel cost multiplier of each node, calculate the total cost of the nodes in the neighboring nodes of the current parent node that are not in the visited node set and are not of a type that blocks travel; add the nodes in the neighboring nodes of the current parent node that are not in the visited node set and are not of a type that blocks travel to the desired node set; the total cost of a node is the sum of the cost of the path from the starting point to the current node via the parent node and the estimated cost from the current node to the target node; S24. If the target node is included in the neighboring nodes of the current parent node, the target node is moved to the visited node set and the planned node set; in the planned node set, the optimal path is found based on the parent-child relationship between the nodes; S25. Otherwise, return to step S22.

2. The flight path planning system for an aircraft according to claim 1, characterized in that: The display unit is used to fuse the flight path into a three-dimensional flight scene according to the position information of each passing node in the flight path, and display the fused three-dimensional flight path.

3. The flight path planning system for an aircraft according to claim 1, characterized in that: The map generation module obtains a multi-layer planning map using the following methods, including: If the geographical information corresponding to the current pass node contains mountains or buildings, the current pass node will be marked as a pass-blocking type; otherwise: If the meteorological information corresponding to the current pass node contains clouds, the pass type and pass cost multiplier of the current pass node are determined according to the cloud type and cloud map information; Otherwise, mark the current pass node as a normal pass type.

4. The flight path planning system for an aircraft according to claim 1, characterized in that: The path planning module adds nodes that are not in the visited node set and are not of the type that blocks passage among the neighboring nodes of the current parent node to the intended node set in the following manner: For each neighboring node p of the current node that is not in the visited node set and is not a blocking node i (x,y): If the neighboring node p i (x,y) is not in the intended node set, then the adjacent node p is directly i (x,y) is added to the intention node set, and the neighboring node p is recorded i The total cost, path cost, estimated cost, and neighboring node p of (x,y) i The parent node of (x,y) is the current parent node; If the neighboring node p i (x, y) is already in the intended node set, then if the neighboring node p calculated based on the current parent node i The path cost of (x,y) is less than the neighboring node p recorded in the intention node set i The estimated cost of (x, y) is to set the neighboring node p in the intention node set i The parent node of (x,y) updates the current parent node and the adjacent node p i The total cost and path cost of (x,y) are updated to the total cost and path cost calculated based on the current parent node, respectively.

5. The flight path planning system for an aircraft according to claim 1, wherein: When the neighboring nodes are on the same layer as the target node, the estimated cost is calculated using the following formula: When the neighboring nodes and the target node are in different layers, the estimated cost is calculated using the following formula: in, D m =|x c -x e |+|y c -y e |,λ represents the cost of crossing a unit distance, (x c ,y c ) represents the plane coordinates of the adjacent nodes, (x e ,y e ) represents the plane coordinates of the target node, w1 and w2 represent weight coefficients, d represents the inter-layer switching cost, i represents the sequence number of the layer where the neighboring node is located, and j represents the sequence number of the layer where the target node is located.

6. The flight path planning system for an aircraft according to claim 1, wherein: If the neighboring node is on the same layer as the parent node, the path cost is calculated using the following formula If the neighboring node and the parent node are in different layers, the path cost is calculated using the following formula in, represents the path cost of the parent node at the i-th layer, Represents the path cost of the parent node at the jth layer. If the parent node is the starting node, the path cost of the parent node is 0. represents the path cost of the neighboring node at the i-th layer, d represents the inter-layer switching cost, Represents the cost from the parent node to the adjacent node.

7. The flight path planning system for an aircraft according to claim 1, wherein: According to the formula Calculate the cost from the parent node to the neighboring node Among them, l represents the travel cost multiplier of the adjacent node, λ represents the cost value of crossing the unit distance, (x c ,y c ) represents the plane coordinates of the adjacent nodes, (x f ,y f ) represents the plane coordinates of the parent node.

8. The flight path planning system for an aircraft according to claim 1, wherein: In the planning node set, the planning path is found based on the parent-child relationship between nodes, including: S241, taking the target node as the current node; S242, adding the current node to the path node set; if the current node is the starting node, then stop searching, and the node sequence in the path node set is the planned path; S243. Otherwise, search for the parent node of the current node in the planned node set, take the parent node of the current node as the current node, and return to step S242.

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