A flight path planning method considering altitude information

Abstract

The present invention relates to a flight path planning method that takes altitude information into consideration, comprising the following steps: generating a multi-layer planning map based on geographical and meteorological information within a flyable range; map information on each layer 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; and using an improved path planning algorithm to calculate the optimal path from the starting point to the target point based on the positions of the flight starting point and target point, as well as the traffic type and traffic cost multiplier of each traffic node in each map layer, thereby obtaining a planned flight path for an aircraft.

Description

Technical Field

[0001] The present invention relates to the technical field of flight path planning, and in particular to a flight path planning method considering altitude information. Background Art

[0002] There are two main reasons for the decline or disappearance of "passability": obstacles and slowdowns. Obstacles are obstacles that cannot be directly passed. They include natural obstacles such as cliffs and peaks, as well as man-made obstacles such as buildings and road controls. The only way to pass through these obstacles is to detour, which also increases the path cost. Slowdowns are obstacles that significantly reduce the speed of passage. They include natural obstacles such as rivers and swamps, as well as man-made obstacles such as speed limits and flow restrictions. These obstacles can reduce travel efficiency and even change the method of passage, such as switching from land to water. In particular, when the cost of slowdowns increases too significantly, slowdowns can be considered part of the obstructions, as they also result in the need for detours.

[0003] Existing path determination methods are limited to a two-dimensional plane, meaning they don't consider height or layer dimensions. This lack of dimensional information, such as the absence of ascent or descent in reality and the lack of Z-axis information in the virtual world, inevitably reduces the flexibility and optimality of path planning. Furthermore, existing flight path determination methods only consider obstacles that block passage, requiring a detour upon encountering an obstacle. They lack consideration for obstacles that mitigate passage. When these obstacles are introduced, the added cost of the detour can far exceed the cost of "jumping" over the complex obstacle. Summary of the Invention

[0004] In view of the above analysis, an embodiment of the present invention aims to provide a flight path planning method that takes altitude information into consideration, so as to solve the problem that the existing flight path planning method does not take altitude information into consideration, the path planning flexibility is low, and the optimal path cannot be accurately found.

[0005] In one aspect, an embodiment of the present invention provides a flight path planning method that takes altitude information into account, comprising the following steps:

[0006] Generate a multi-layer planning map based on geographical 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 type includes normal traffic type, slowed traffic type and obstructed traffic type;

[0007] According to the positions of the flight starting point and target point, as well as the traffic type and traffic cost multiplier of each traffic node in each layer of the map, an improved path planning algorithm is used to calculate the optimal path from the starting point to the target point, and the planned flight path of the aircraft is obtained.

[0008] Furthermore, a multi-layer planning map is generated based on geographical and meteorological information within the flyable range, including:

[0009] The three-dimensional space of the flight range is divided vertically to form multiple division layers;

[0010] In each segmentation layer, grid division is performed to form a multi-layer grid map, and one grid block is a pass node;

[0011] The traffic type and traffic cost multiplier of each traffic node are marked according to the geographical and meteorological information corresponding to each traffic node to obtain a multi-layer planning map.

[0012] Furthermore, the traffic type and traffic cost multiplier of each traffic node are marked according to the geographical and meteorological information corresponding to each traffic node, and a multi-layer planning map is obtained, including:

[0013] 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:

[0014] If the meteorological information corresponding to the current pass node contains clouds, if the clouds are thunderstorm clouds, the current pass node will be marked as a type that hinders passage; otherwise, the current pass node will be marked as a type that slows passage, and its passage cost multiplier will be determined accordingly;

[0015] Otherwise, mark the current pass node as a normal pass type.

[0016] Furthermore, based on the locations of the flight starting point and destination point, as well as the traffic type and traffic cost multiplier of each traffic node in each layer of the map, an improved path planning algorithm is used to calculate the optimal path from the starting point to the destination point, and the planned flight path of the aircraft is obtained, including:

[0017] S21, putting the starting point into the intention node set;

[0018] 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;

[0019] 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 the 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;

[0020] 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;

[0021] S25. Otherwise, return to step S22.

[0022] Furthermore, the node with the smallest total cost value is selected as the current parent node in the set of intention nodes, including:

[0023] 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.

[0024] Further,

[0025] 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.

[0026] Further,

[0027] If the neighboring node is on the same layer as the parent node, the path cost is calculated using the following formula

[0028] If the neighboring node and the parent node are in different layers, the path cost is calculated using the following formula

[0029] 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.

[0030] Further,

[0031] According to the formula Calculate the cost from the parent node to the neighboring node

[0032] Among them, l represents the cost multiplier of the adjacent node, λ represents the cost value of crossing a 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.

[0033] Further,

[0034] When the neighboring nodes are on the same layer as the target node, the estimated cost is calculated using the following formula:

[0035] When the neighboring nodes and the target node are in different layers, the estimated cost is calculated using the following formula:

[0036] 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.

[0037] Furthermore, in the planning node set, the planning path is found based on the parent-child relationship between nodes, including:

[0038] S241, taking the target node as the current node;

[0039] 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;

[0040] 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.

[0041] Compared with the existing technology, the present invention takes the dimensional information of the Z axis 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.

[0042] 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

[0043] 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.

[0044] Figure 1 A flow chart of a flight path planning method considering altitude information according to an embodiment of the present invention;

[0045] Figure 2 A schematic diagram of a low-level map in a multi-level map according to an embodiment of the present invention;

[0046] Figure 3 A schematic diagram of a high-level map in a multi-level map according to an embodiment of the present invention;

[0047] Figure 4 This is a schematic diagram of the path planning result of only a single-layer map in an embodiment of the present invention;

[0048] 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;

[0049] 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

[0050] 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.

[0051] A specific embodiment of the present invention discloses a flight path planning method taking altitude information into consideration, such as Figure 1 As shown, the following steps are included:

[0052] S1. Generate a multi-layer planning map based on geographical and meteorological information within the flight range; each layer of map information includes the traffic type and traffic cost multiplier for each traffic node in the layer; the traffic types include normal traffic type, slowed traffic type, and obstructed traffic type;

[0053] S2. Based on the locations of the flight starting point and target point, as well as the traffic type and traffic cost multiplier of each traffic node in each layer of the map, an improved path planning algorithm is used to calculate the optimal path from the starting point to the target point to obtain the planned flight path of the aircraft.

[0054] By taking the Z-axis dimensional information into consideration and dividing the traffic type into normal traffic type, slowed traffic type and obstructed traffic type, the flight path planning of the aircraft is no longer just a detour. It can also consider planning the path in the Z-axis space, so that it can flexibly avoid different types of obstacles and select better paths 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.

[0055] Specifically, in step S1, a multi-layer planning map is generated based on geographical and meteorological information within the flight range, including:

[0056] S11. Segment the three-dimensional space of the flight range vertically to form multiple segmentation layers;

[0057] 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.

[0058] For three-dimensional path planning tasks, it is necessary to first divide the space on the Z axis to obtain different layers, and each layer can be abstracted as a two-dimensional plane.

[0059] S12. Divide each segmentation layer into grids to form a multi-layer grid map, where one grid block is a pass node.

[0060] Each two-dimensional plane is divided according to a uniform segmentation scale, and each area block is regarded as a pass node.

[0061] For example, a three-dimensional space is a space from the ground to a height of 10,000 meters, with a length and width of 300 km. The height of each map layer is 100 meters, and the three-dimensional space is layered. Each layer is divided into areas of 100m×100m, that is, each layer is divided into grids, and each grid block is a pass node.

[0062] S13. Mark the traffic type and traffic cost multiplier of each traffic node according to the geographical and meteorological information corresponding to each traffic node to obtain a multi-layer planning map.

[0063] 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.

[0064] During implementation, the path planning is aviation path planning, which can obtain geographic information and meteorological information in the three-dimensional flight space.

[0065] 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.

[0066] Clouds are divided into three families and ten genera, as shown in Table 1.

[0067] Table 1 Cloud classification

[0068]

[0069] Specifically, step S13 marks the traffic type and traffic cost multiplier of each traffic node according to the geographical and meteorological information corresponding to each traffic node, and obtains a multi-layer planning map, including:

[0070] 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:

[0071] 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;

[0072] Otherwise, mark the current pass node as a normal pass type.

[0073] 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.

[0074] 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.

[0075] 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.

[0076] 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.

[0077] 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.

[0078] If there are no mountains, buildings or clouds at the current pass node, the current pass node will be marked as a normal pass type.

[0079] 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.

[0080] 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.

[0081]

[0082] 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 .

[0083] 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 3 This 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.

[0084] Multi-level path planning is inevitable to reduce the total cost and can flexibly avoid different types of obstacles.

[0085] After obtaining the multi-layer map information, in step S2, an improved path planning algorithm is used to calculate the optimal path from the starting point to the target point according to the traffic type and traffic cost multiplier of each traffic node in each layer of the map.

[0086] 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.

[0087] The specific planning process is:

[0088] S21, putting the starting point into the intention node set;

[0089] 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;

[0090] 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.

[0091] The path cost of the starting node is 0.

[0092] 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.

[0093] 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.

[0094] 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:

[0095] 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.

[0096] 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.

[0097] The intention node that is ranked first after sorting is taken as the current parent node.

[0098] 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;

[0099] 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;

[0100] 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.

[0101] 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).

[0102] 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.

[0103] For example, Figure 2 The middle node (7, 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 set of visited nodes, its total cost does not need to be calculated and it is not added to the intended node set.

[0104] 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.

[0105] First, the path cost is calculated based on the position relationship between the adjacent nodes and the parent node.

[0106] Specifically, if the neighboring node is on the same layer as the parent node, the path cost is calculated using the following formula:

[0107]

[0108] 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.

[0109] 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.

[0110] If the neighboring node and the parent node are in different layers, the path cost is calculated using the following formula

[0111] 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.

[0112] Specifically, according to the formula Calculate the cost from the parent node to the neighboring node

[0113] Among them, l represents the cost multiplier of the adjacent node, λ represents the cost value of crossing a 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.

[0114] Then, the estimated cost is calculated based on the positional relationship between the neighboring nodes and the target point

[0115] Specifically, if the neighboring nodes are on the same layer as the target node, the estimated cost is calculated using the following formula:

[0116] If the neighboring nodes and the target node are in different layers, the estimated cost is calculated using the following formula:

[0117] 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

[0118] 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.

[0119] The total cost of neighboring nodes That is, the total cost is the sum of the path cost and the estimated cost.

[0120] 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.

[0121] 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.

[0122] 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:

[0123] 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):

[0124] If 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;

[0125] 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.

[0126] 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.

[0127] 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 When the path cost of (x,y) is less than the intended path, the node p recorded in the node set is i (x,y) path cost, 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.

[0128] 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;

[0129] 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.

[0130] Specifically, the planned path is found based on the parent-child relationship between nodes, including:

[0131] S241, taking the target node as the current node;

[0132] 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;

[0133] 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.

[0134] 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.

[0135] S25. Otherwise, return to step S22.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] First, the starting point p 1 (1,1) is put into the intention node set.

[0140] 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.

[0141] 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),

[0142] According to the formula:

[0143]

[0144] or or

[0145] D m =|x c -x e |+|y c -y e |

[0146] Calculate the path cost, estimated cost, and total cost for each neighboring point:

[0147]

[0148]

[0149]

[0150]

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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)

[0156] 、、、、、、、p 2 (2,3)p 2 (3,3)p 2 (3,2)p 2 (3,1)Add the intention node set. 、、、

[0158] 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).

[0159] 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.

[0160] Initially, the path node set is empty.

[0161] Point p 1 (20,20) is the current node.

[0162] 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.

[0163] 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)

[0164] 、、、、、、、、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)

[0165] 、、、、、、、p 1 (19,12)p 1 (20,13)p 1 (20,14)p 1 (20,15)p 1 (20,16)p 1 (20,17)

[0166] 、、、、、、p 1 (20,18)p 1 (19,19)p 1 (20,20)), such as Figure 4 It should be noted that due to 、、

[0168] There is only one map layer, so the neighboring nodes of the current parent node in step S23 only include nodes in the same layer that are adjacent to the parent node.

[0169] 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)

[0170] 、、、、、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)

[0171] 、、、、、、、p 2 (12,13)p 1 (13,12)p 1 (13,13)p 2 (14,14)p 1 (15,15)p 1 (16,15)

[0172] 、、、、、、p 1 (17,16),p 1 (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 multi-layer maps can obtain shorter path planning results.

[0173] 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.

[0174] 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 method considering altitude information, characterized in that: The following steps are involved: Generate a multi-layer planning map based on geographical and meteorological information within the flight range; each layer of planning map information 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; Based on the locations of the flight starting point and destination, as well as the traffic type and traffic cost multiplier of each traffic node in each layer of the planning map, an improved path planning algorithm is used to calculate the optimal path from the starting point to the destination, and the planned flight path of the aircraft is obtained; Generate multi-layer planning maps based on geographical and meteorological information within the flyable area, including: The three-dimensional space of the flight range is divided vertically to form multiple division layers; In each segmentation layer, grid division is performed to form a multi-layer grid map, and one grid block is a pass node; Mark the traffic type and traffic cost multiplier of each traffic node according to the geographical and meteorological information corresponding to each traffic node, and obtain a multi-layer planning map; Based on the locations of the flight start and destination points, as well as the traffic type and traffic cost multiplier of each traffic node in each layer of the planning map, an improved path planning algorithm is used to calculate the optimal path from the start point to the destination point, and the planned flight path of the aircraft is obtained, including: 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 the 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 planned path is obtained by searching based on the parent-child relationship between the nodes; S25. Otherwise, return to step S22.

2. The flight path planning method considering altitude information according to claim 1, characterized in that: Mark the traffic type and traffic cost multiplier of each traffic node according to the geographical and meteorological information corresponding to each traffic node, and obtain a multi-layer planning map, 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.

3. The flight path planning method considering altitude information according to claim 1, characterized in that: Select the node with the smallest total value in the set of intention nodes as the current parent node, including: 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.

4. The flight path planning method considering altitude information according to claim 1, characterized in that: 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.

5. The flight path planning method considering altitude information according to claim 4, characterized in that: 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.

6. The flight path planning method considering altitude information according to claim 4, characterized in that: cost Among them, l represents the cost multiplier of the adjacent node, λ represents the cost value of crossing a 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.

7. The flight path planning method considering altitude information according to claim 1, characterized in that: 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.

8. The flight path planning method considering altitude information according to claim 1, characterized in that: 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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