Dense high-rise urban area unmanned aerial vehicle distribution path planning method

Abstract

The invention discloses a dense high-rise urban area unmanned aerial vehicle distribution path planning method, and relates to the technical field of unmanned aerial vehicle path planning, and the method comprises the steps: determining an initial flight height according to a target stable difference value W which represents the discrete condition of the vertical distance of all distribution points in a distribution initial sequence, and obtaining a flight height range through combining with a preset minimum height; selecting a route for ensuring the shortest flight path in the flight height range; in the process, the intensive height needing to be bypassed is considered, meanwhile, energy consumption caused by height rising is considered, it is synchronously considered that the route of bypassing the high-rise building or the route of jumping the high-rise building is shorter, and therefore a more reasonable flight route can be planned.

Description

Technical Field

[0001] The present invention belongs to the technical field of drone path planning, and specifically is a method for drone delivery path planning in a densely populated high-rise urban area. Background Art

[0002] The patent with publication number CN117311384A discloses a method, device, electronic device and readable storage medium for generating a UAV flight path, which is applied to the field of UAV technology. The method includes determining the flight parameters of the UAV according to the task to be performed, and constructing an A-star grid based on the flight parameters; calling the A-star optimization algorithm to perform global obstacle avoidance based on the A-star grid to generate an initial flight path; removing collinear path points by performing collinear optimization processing on the initial flight path to obtain an initial optimized flight path; performing redundant inflection point optimization processing on the initial optimized flight path to obtain the target flight path of the UAV. This application can solve the problem of poor practicality of related technologies and can generate the optimal flight path of the UAV using limited computing resources.

[0003] However, with regard to drone path generation, especially when it comes to drone delivery in densely populated high-rise areas, especially when the delivery destination is not on the ground, or at a certain height, that is, the location where the items are delivered is at a certain height or is in a certain building, there are several obstacles involved that need to be bypassed. However, bypassing will lead to the problem of longer paths and increased energy consumption. How to reasonably choose a suitable path to bypass some high-rise buildings in densely populated areas is a problem. Based on this, a solution is provided. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a method for planning a delivery path for drones in densely populated high-rise urban areas.

[0005] A method for planning a delivery path for drones in densely populated high-rise urban areas, the method specifically comprising the following steps:

[0006] Get the starting point and all the delivery points, and sort the delivery points from near to far from the starting point. If the straight-line distance between any two adjacent delivery points does not exceed X1, they will be sorted from small to large according to the difference between the vertical distance representing the height of the delivery point and the average of the vertical distances of all the delivery points. Determine the order of all the delivery points and get the initial delivery order.

[0007] The initial flight altitude is determined according to the standard stable difference value W representing the discrete situation of the vertical distance of all delivery points in the initial delivery sequence. At the same time, the flight altitude range is obtained in combination with the preset minimum altitude. The route that ensures the shortest flight path is selected within the flight altitude range to obtain a one-way flight path.

[0008] Furthermore, the target stability difference is obtained by:

[0009] First, the vertical distances of all delivery points are obtained and marked as Ci, i=1, ..., n, and the average vertical distance is obtained simultaneously and marked as P;

[0010] Use the formula to calculate the stable difference value W of Ci. The specific calculation formula is:

[0011]

[0012] Furthermore, the specific method of determining the initial flight altitude according to the target stable difference value W is:

[0013] When the W value does not exceed the preset value X1, the maximum altitude in Ci is compared with the flight ceiling altitude of the current area, and the smaller value of the two is set as the initial altitude;

[0014] At the same time, the set minimum flight altitude of the drone is obtained, and the minimum altitude to the initial altitude is marked as the flight altitude range.

[0015] Furthermore, the specific method of selecting a route that ensures the shortest flight path within the flight altitude range is:

[0016] The initial altitude is set as the upper limit of the UAV's flight altitude, and then the shortest flight path from the starting point to the delivery points in the initial delivery sequence is automatically obtained. The shortest flight path ensures that the UAV's flight altitude does not exceed the flight altitude range; thus, a one-way flight path is obtained.

[0017] Furthermore, when the W value exceeds the preset value X1, the height of all obstacles that the drone needs to bypass under the setting of the shortest path and without considering the flight altitude of the drone will be obtained first, and those exceeding the flight upper limit will be removed. The remaining obstacles will be sorted from high to low, and several upper limit altitudes will be selected. According to the shortest flight path that reaches the delivery points in the initial delivery sequence in sequence, the shortest flight path ensures that the flight altitude of the drone does not exceed the flight altitude range, and several flight sub-paths corresponding to the upper limit altitudes are obtained;

[0018] The flight energy consumption and path length of each flight sub-path are dimensionally removed and weighted, and then the sum of the weighted flight energy consumption and path length is calculated. The obtained sum is marked as an optional value, and the flight sub-path with the smallest optional value is marked as a one-way flight path.

[0019] Furthermore, the weights in the weighted calculation of flight energy consumption and path length are preset by the administrator.

[0020] Furthermore, the weights in the weighted calculation of flight energy consumption and path length are determined in the following manner:

[0021] Obtain the difference that satisfies Ci-P greater than zero, add all the difference values, and the resulting mark is the upper difference sum value;

[0022] Obtain the difference that satisfies Ci-P less than zero, take its absolute value and then sum it up, and the result is marked as the lower difference sum;

[0023] When the upper difference sum exceeds the lower difference sum, the weight of flight energy consumption is set to 0.3 and the weight of path length is set to 0.7; otherwise, the weights of the two are swapped.

[0024] Furthermore, after the one-way flight path is determined, the flight of the UAV is driven according to the one-way flight path.

[0025] Furthermore, the drone monitors its endurance in real time during the one-way flight path. When the endurance falls short of the set threshold at any time, it automatically plans the nearest charging point and charges until it can deliver the goods to the last delivery point and the endurance is sufficient to reach the nearest charging point for charging.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] The present application determines the initial flight altitude based on the target stable difference value W representing the discrete situation of the vertical distance of all delivery points in the initial delivery sequence, and at the same time obtains the flight altitude range in combination with the preset minimum altitude, and selects the route that ensures the shortest flight path within the flight altitude range;

[0028] During this process, the height of the densely populated buildings that need to be avoided will be taken into account, as will the energy consumption caused by the increased altitude. At the same time, it will be considered whether the path is shorter by bypassing the high-rise buildings or flying over them. This way, a more reasonable flight path can be planned. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a flowchart of the present invention. DETAILED DESCRIPTION

[0030] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] See also Figure 1 ,This application provides a method for planning the delivery path of drones in densely populated high-rise urban areas;

[0032] As an embodiment 1 of the present application, the method specifically includes the following steps:

[0033] Step 1: Get the starting point and several delivery points, mark each delivery point as a delivery target, there must be at least one delivery target, and the specific number depends on the actual situation;

[0034] Step 2: Get the starting point, and then get several delivery points along the way. Sort all the delivery points in ascending order of their straight-line distance from the starting point.

[0035] If the straight-line distance between any two adjacent delivery points does not exceed X1, a sequence analysis is performed. The specific method of sequence analysis is as follows:

[0036] Any combination of two adjacent delivery points whose straight-line distance does not exceed X1 is marked as a close-distance group;

[0037] Get the vertical distance of each distribution point. The vertical distance is the height of each distribution point. Automatically get the average value of all vertical distances and mark it as the average vertical distance.

[0038] Then, a group of close-distance groups is obtained at random, and the vertical distance of the two delivery points in the close-distance group is subtracted from the average vertical distance to obtain the absolute value, and the obtained value is marked as the vertical average difference, and the two delivery points in the close-distance group are sorted in the order of the vertical average difference from small to large;

[0039] Then the same process is performed on the remaining close-range groups to obtain the order of all close-range groups;

[0040] Preliminarily determine the order of all delivery points and mark them as the initial delivery order;

[0041] Step 3: After obtaining all the initial delivery sequences, perform height analysis according to the initial delivery sequences. The specific method of height analysis is as follows:

[0042] First, all vertical distances are obtained and marked as Ci, i=1, ..., n, and the average vertical distance is obtained synchronously and marked as P;

[0043] Use the formula to calculate the stable difference value W of Ci. The specific calculation formula is:

[0044]

[0045] When the W value does not exceed X1, the maximum altitude in Ci and the flight ceiling altitude of the current area will be automatically obtained. The flight ceiling altitude is set by the administrator according to local regulations and environment. If the maximum altitude in Ci is lower than the flight ceiling altitude, the maximum altitude will be automatically marked as the initial altitude, otherwise the flight ceiling altitude will be marked as the initial altitude;

[0046] At the same time, the set minimum flight altitude of the drone is obtained, and the minimum altitude to the initial altitude is marked as the flight altitude range; X1 is the preset value;

[0047] Step 4: After obtaining the initial delivery sequence and initial height, the route is planned based on the initial height and the initial delivery sequence. The specific planning method is as follows:

[0048] The initial altitude is set as the upper limit of the drone's flight altitude, and then the drone automatically obtains the shortest distance from the starting point to the second delivery point. During this process, the drone's flight altitude must not exceed the flight altitude range. This means that if the upper limit of the flight altitude can be reached, the drone can fly over some high-rise building clusters.

[0049] After arriving at the first delivery point, the shortest distance to the second delivery point is automatically obtained. During this process, the flight altitude is kept within the upper flight altitude limit, and the delivery route planning for all delivery points is completed in sequence;

[0050] Get the flight path corresponding to the initial delivery sequence and mark it as a one-way flight path;

[0051] Step 5: Drive the drone to fly along a one-way flight path;

[0052] As the second embodiment of the present application, this embodiment is implemented on the basis of the first embodiment, and the difference from the first embodiment is that this embodiment is used to describe the case where the W value exceeds X1;

[0053] At this time, a road analysis will be conducted, and the specific analysis method is as follows:

[0054] Automatically obtain the path from the starting point to each delivery point in the initial delivery sequence. The path is obtained by flying from the starting point to each delivery point in the initial delivery sequence along the shortest path. During this process, it will be evaluated whether to fly directly over the dense high-rise cluster or fly around it when arriving at any delivery point, and fly to the delivery point according to the shortest distance.

[0055] Then, all the heights that need to be flown over the high-rise clusters are obtained, and the heights of all the high-rise buildings are marked as obstacle heights;

[0056] Delete the obstacle heights that exceed the flight limit, mark the remaining obstacle heights as Zj, j = 1, ..., m, and arrange Zj in descending order according to height;

[0057] Get the values ​​of Zj corresponding to the top five in Zj and mark them as the predetermined height;

[0058] Select the predetermined altitudes in order, mark each selected predetermined altitude as the upper limit altitude, and then obtain the flight path in accordance with step 4 of embodiment 1;

[0059] Mark each flight path of a predetermined altitude as a flight sub-path, obtain the power required for the flight sub-path, mark it as flight energy consumption, and simultaneously obtain the path length of the flight sub-path;

[0060] Remove the dimensions of flight energy consumption and path length, and then calculate the optional value of the flight sub-path. The specific calculation formula is:

[0061] Optional value = K1×flight energy consumption+K2×path length;

[0062] K1 and K2 are weights, determined as follows:

[0063] Obtain the difference that satisfies Ci-P greater than zero, add all the difference values, and the resulting mark is the upper difference sum value;

[0064] Obtain the difference that satisfies Ci-P less than zero, take its absolute value and then sum it up, and the result is marked as the lower difference sum;

[0065] When the upper difference value exceeds the lower difference value, K1 is set to 0.3 and K2 is set to 0.7; otherwise, K1 is set to 0.7 and K2 is set to 0.3;

[0066] Mark the flight subpath with the smallest optional value as a one-way flight path;

[0067] Of course, the K1 and K2 values ​​here can also be preset by the administrator;

[0068] As the third embodiment of the present application, this embodiment is implemented on the basis of the second embodiment. The difference is that this embodiment also needs to monitor the battery life of the UAV in real time during the one-way flight path. When the battery life is less than the set threshold at any time, the nearest charging point is automatically planned and charged until the goods can be delivered to the last delivery point and the battery life can meet the requirements of reaching the nearest charging point for charging.

[0069] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for planning the delivery path of drones in densely populated high-rise urban areas, characterized in that: The method specifically comprises the following steps: Get the starting point and all the delivery points, and sort the delivery points from near to far from the starting point. If the straight-line distance between any two adjacent delivery points does not exceed X1, they will be sorted from small to large according to the difference between the vertical distance representing the height of the delivery point and the average of the vertical distances of all the delivery points. Determine the order of all the delivery points and get the initial delivery order. The initial flight altitude is determined according to the standard stable difference value W representing the discrete situation of the vertical distance of all delivery points in the initial delivery sequence. At the same time, the flight altitude range is obtained in combination with the preset minimum altitude. The route that ensures the shortest flight path is selected within the flight altitude range to obtain a one-way flight path.

2. The method for planning a delivery path for drones in densely populated high-rise urban areas according to claim 1 is characterized in that: The target stability difference is obtained by the following method: First, the vertical distances of all delivery points are obtained and marked as Ci, i=1, ..., n, and the average vertical distance is obtained simultaneously and marked as P; Use the formula to calculate the stable difference value W of Ci. The specific calculation formula is:

3. The method for planning a delivery path for drones in densely populated high-rise urban areas according to claim 1 is characterized in that: The specific method of determining the initial flight altitude based on the target stable difference value W is: When the W value does not exceed the preset value X1, the maximum altitude in Ci is compared with the flight ceiling altitude of the current area, and the smaller value of the two is set as the initial altitude; At the same time, the set minimum flight altitude of the drone is obtained, and the minimum altitude to the initial altitude is marked as the flight altitude range.

4. The method for planning a delivery path for drones in densely populated high-rise urban areas according to claim 3 is characterized in that: The specific method of selecting the route that ensures the shortest flight path within the flight altitude range is as follows: The initial altitude is set as the upper limit of the UAV's flight altitude, and then the shortest flight path from the starting point to the delivery points in the initial delivery sequence is automatically obtained. The shortest flight path ensures that the UAV's flight altitude does not exceed the flight altitude range; thus, a one-way flight path is obtained.

5. The method for planning a delivery path for drones in densely populated high-rise urban areas according to claim 2 is characterized in that: When the W value exceeds the preset value X1, the first step is to obtain all the obstacles that the drone needs to bypass under the setting of the shortest path and without considering the flight altitude of the drone. Those that exceed the flight upper limit are removed, and the remaining obstacles are sorted from high to low to select several upper limit heights. According to the shortest flight path that reaches the delivery points in the initial delivery sequence in sequence, the shortest flight path ensures that the flight altitude of the drone does not exceed the flight altitude range, and obtains several flight sub-paths corresponding to the upper limit heights; The flight energy consumption and path length of each flight sub-path are dimensionally removed and weighted, and then the sum of the weighted flight energy consumption and path length is calculated. The obtained sum is marked as an optional value, and the flight sub-path with the smallest optional value is marked as a one-way flight path.

6. The method for planning a delivery path for drones in densely populated high-rise urban areas according to claim 5 is characterized in that: The weights in the weighted calculation of flight energy consumption and path length are preset by the administrator.

7. The method for planning a delivery path for drones in densely populated high-rise urban areas according to claim 5 is characterized in that: The weights in the weighted calculation of flight energy consumption and path length are determined as follows: Obtain the difference that satisfies Ci-P greater than zero, add all the difference values, and the resulting mark is the upper difference sum value; Obtain the difference that satisfies Ci-P less than zero, take its absolute value and then sum it up, and the result is marked as the lower difference sum; When the upper difference sum exceeds the lower difference sum, the weight of flight energy consumption is set to 0.3 and the weight of path length is set to 0.7; otherwise, the weights of the two are swapped.

8. The method for planning a delivery path for drones in densely populated high-rise urban areas according to claim 1 is characterized in that: After determining the one-way flight path, drive the drone to fly according to the one-way flight path.

9. The method for planning a delivery path for drones in densely populated high-rise urban areas according to claim 8 is characterized in that: The drone monitors its endurance in real time during its one-way flight path. If the endurance falls below the set threshold at any time, it will automatically plan the nearest charging point and charge until it can deliver the goods to the last delivery point and the endurance is sufficient to reach the nearest charging point for charging.

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