Unmanned aerial vehicle route conflict detection method and device and electronic equipment

Abstract

The invention relates to an unmanned aerial vehicle route conflict detection method and device and electronic equipment, relates to the field of unmanned aerial vehicles, and solves the technical problem of how to ensure safe flight of routes of multiple unmanned aerial vehicles. The unmanned aerial vehicle route conflict detection method comprises the following steps that at least two unmanned aerial vehicle route convex spaces are generated according to coordinate values of waypoints in at least two unmanned aerial vehicle routes, and the unmanned aerial vehicle route convex spaces comprise all the waypoints in the unmanned aerial vehicle routes; and judging whether the convex spaces of the unmanned aerial vehicle routes intersect or not, if so, determining that the unmanned aerial vehicle routes conflict with each other, and otherwise, determining that the unmanned aerial vehicle routes do not conflict with each other.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicles, and in particular to a method, a device and an electronic device for detecting conflict of unmanned aerial vehicle routes. Background Art

[0002] In recent years, with the widespread and in-depth application of drone systems in multiple fields such as industry, agriculture, and military, the number of drones required to complete a task is increasing. For example, in the spraying operation in the agricultural field, fire scene reconnaissance and auxiliary fire fighting in the fire emergency field, and cargo transportation in the logistics field, multiple drones are required to cooperate to complete the task. In the past, the mode of one ground station software controlling one drone has been increasingly unable to keep up with the needs of the rapid development of drone technology. One ground station controls multiple or even dozens of drones (that is, one station controls multiple drones) has become an important research direction in the current drone field. The benefits of one station controlling multiple drones are obvious in terms of improving work efficiency, optimizing resource allocation, enhancing combat capabilities, and reducing costs. However, while one station controls multiple drones, it also brings new challenges, such as how to ensure that there are no conflicts between the routes of multiple drones.

[0003] In addition, the drone may experience link interruption or other emergencies at any time during flight, at which time the drone flight control system will trigger the link-breaking homing operation. Compared with other homing modes, straight-line homing is the best choice. The benefits of straight-line homing are mainly reflected in improving the efficiency and safety of homing. In this mode, the drone will return directly along the shortest path, avoiding detours or getting lost in complex environments, thereby greatly shortening the return time. This mode is particularly suitable for emergency situations, such as low battery or emergency situations that require a quick return to the base, to ensure that the drone returns to the take-off point quickly and safely. However, for the existing one-stop multi-machine route detection technology, the conflict detection between routes only checks whether the two routes intersect in space, which cannot meet the conflict detection requirements of straight-line homing. In case of emergencies such as link breaking, the original route homing mode can generally only be selected.

[0004] Therefore, how to ensure the safe flight of multiple drone routes is a technical problem that needs to be solved urgently. Summary of the invention

[0005] In view of the above analysis, the embodiments of the present invention aim to provide a method, device and electronic device for detecting conflicts in UAV routes, so as to solve the technical problem of how to ensure the safe flight of routes of multiple UAVs.

[0006] In a first aspect, an embodiment of the present invention provides a method for detecting a conflict of a drone route, comprising the following steps:

[0007] Generate a convex space of the drone route according to the coordinate values ​​of the waypoints in the drone route, wherein the convex space of the drone route includes all the waypoints in the drone route; and

[0008] It is determined whether the convex spaces of the drone routes intersect each other. If so, there is a conflict between the drone routes. Otherwise, there is no conflict between the drone routes.

[0009] Based on the further improvement of the above method, judging whether the convex spaces of the UAV routes intersect includes:

[0010] Step S100: determining whether the height ranges between the convex spaces of the drone routes intersect, if not, there is no conflict between the drone routes; otherwise, proceeding to step S200;

[0011] Step S200: Determine whether the boundary lines between the convex spaces of the drone routes intersect, if so, there is a conflict between the drone routes; otherwise, proceed to step S300;

[0012] Step S300: Determine whether there is an inclusion relationship between the convex spaces of the drone routes. If so, there is a conflict between the drone routes; otherwise, there is no conflict between the drone routes.

[0013] Based on the further improvement of the above method, judging whether there is an inclusion relationship between the convex spaces of the UAV routes includes:

[0014] According to the positional relationship of the centers of gravity between the convex spaces of the drone routes, it is determined whether there is an inclusion relationship between the convex spaces of the drone routes.

[0015] Based on a further improvement of the above method, judging whether there is an inclusion relationship between the convex spaces of the drone routes according to the positional relationship of the centers of gravity between the convex spaces of the drone routes includes:

[0016] Step S10: obtaining the center of gravity of the convex space of the drone route to be detected;

[0017] Step S20: Determine whether the center of gravity is inside the other UAV route convex space. If so, the UAV route convex space to be detected and the other UAV route convex space have an inclusion relationship; otherwise, proceed to step S30;

[0018] Step S30: Obtaining the center of gravity of another convex space of the UAV route;

[0019] Step S40: Determine whether the other center of gravity is inside the convex space of the drone route to be detected. If so, there is an inclusion relationship between the convex space of the drone route to be detected and the other convex space of the drone route; otherwise, there is no inclusion relationship.

[0020] Based on a further improvement of the above method, judging whether the center of gravity is inside another convex space of the UAV route or judging whether another center of gravity is inside the convex space of the UAV route to be detected includes:

[0021] The ray method in computer graphics is used to determine whether the center of gravity is inside the convex space of the UAV route.

[0022] Based on the further improvement of the above method, generating at least two UAV route convex spaces according to the coordinate values ​​of the waypoints in at least two UAV routes includes:

[0023] Step A100: according to the latitude and longitude coordinate values ​​of the waypoints in each UAV route, determine a first target point from the waypoints and set the first target point as the current target point;

[0024] Step A200: determining the next target point from the remaining waypoints according to the azimuths of the current target point and the remaining waypoints, wherein the starting direction of the azimuth of the current target point is the vector direction from the previous target point to the current target point, and the starting direction of the azimuth of the first target point is the vector direction from the first target point to the target direction;

[0025] Step A300: determining whether the next target point coincides with the first target point, if so, proceeding to step A400, otherwise, setting the next target point as the current target point and returning to step A200;

[0026] Step A400: sequentially connect all target points and generate a convex space according to the height values ​​of the waypoints in the UAV route.

[0027] Based on the further improvement of the above method, generating at least two UAV route convex spaces according to the coordinate values ​​of the waypoints in at least two UAV routes also includes the following steps:

[0028] The boundary of the buffer zone of the convex space is determined according to the positional relationship between the centroid of the convex hull formed by sequentially connecting all target points and the edge of the convex hull.

[0029] Based on a further improvement of the above method, determining the boundary of the buffer zone of the convex space according to the positional relationship between the centroid of the convex hull and the edge of the convex hull includes:

[0030] Determine whether the center of gravity of the convex hull is on the right side of the edge of the convex hull. If so, draw a parallel line to the left that is parallel to the edge of the convex hull; otherwise, draw a parallel line to the right that is parallel to the edge of the convex hull; wherein the distance between the parallel line and the edge of the convex hull is a preset safety threshold;

[0031] Fitting the gaps between adjacent parallel lines with a curve; and

[0032] The parallel lines and the curves are sequentially connected to obtain a boundary of a buffer zone of the convex space.

[0033] In a second aspect, an embodiment of the present invention provides a device for detecting a conflict of a drone route, comprising:

[0034] A convex space generation module is configured to generate at least two drone route convex spaces according to the coordinate values ​​of the waypoints in at least two drone routes, wherein the drone route convex spaces contain all the waypoints in the drone routes; and

[0035] The convex space intersection judgment module is configured to judge whether the convex spaces of the drone routes intersect. If so, there is a conflict between the drone routes; otherwise, there is no conflict between the drone routes.

[0036] In a third aspect, an embodiment of the present invention provides an electronic device, including:

[0037] at least one processor; and

[0038] A memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the UAV route conflict detection method described in any one of the first aspects of the present invention.

[0039] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0040] 1. The scheme of the present invention provides a reliable and efficient method for detecting conflicts between UAV routes, which can quickly detect whether multiple UAV routes intersect in space, provide a reliable reference basis for further optimizing UAV routes, and ensure the safe flight of multiple UAV routes.

[0041] 2. The solution of the present invention utilizes the characteristic that the line connecting any two points in the convex space must be contained in the convex space itself, which meets the conflict detection requirements of straight-line homing and theoretically solves the possibility of conflict between routes during straight-line homing operations.

[0042] 3. The solution of the present invention utilizes the characteristic that the convex space is the smallest convex polygon containing the route, which can ensure that the drone occupies as little airspace resources as possible when returning in a straight line, ensuring that the airspace resources occupied by each route are minimized.

[0043] In the present invention, the above-mentioned technical solutions can also be combined with each other to achieve more preferred combination solutions. Other features and advantages of the present invention will be described in the subsequent description, and some advantages can become obvious from the description, or can be understood by practicing the present invention. The purpose and other advantages of the present invention can be achieved and obtained through the contents particularly pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings are only used for the purpose of illustrating specific embodiments and are not to be considered as limiting the present invention. In the entire drawings, the same reference symbols represent the same components;

[0045] Figure 1 A schematic flow chart of a method for detecting conflicts in UAV routes according to an embodiment of the present invention is shown.

[0046] Figure 2 A conceptual schematic diagram of a drone route in an embodiment of the present invention is shown.

[0047] Figure 3 An example of a two-dimensional convex hull generated by a method according to an embodiment of the present invention is shown.

[0048] Figure 4 A schematic flow chart of a method for generating a convex space of a UAV route according to another embodiment of the present invention is shown.

[0049] Figure 5 An example of the buffer zone of the convex space formed according to steps A10 to A30 is shown.

[0050] Figure 6-1 to Figure 6-3 Three examples of intersecting convex spaces according to embodiments of the present invention are shown.

[0051] Figure 7 An exemplary block diagram of a conflict detection device for drone routes according to an embodiment of the present invention is shown.

[0052] Figure 8 A schematic block diagram of an example electronic device 800 that may be used to implement embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0053] The preferred embodiments of the present invention are 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, but are not used to limit the scope of the present invention.

[0054] Figure 1 FIG. 2 is a flow chart showing a method for detecting a conflict of a UAV route according to an embodiment of the present invention. Figure 1 As shown, the conflict detection method of the UAV route includes the following steps:

[0055] Step S101: generating at least two drone route convex spaces according to the coordinate values ​​of the waypoints in at least two drone routes, wherein the drone route convex spaces contain all the waypoints in the drone routes.

[0056] Convex hull is a concept in computational geometry. It refers to a minimum convex polygon that contains a given set of points and ensures that these points are either on the polygon or inside the polygon. In two-dimensional space, the convex hull can be imagined as a rubber band that just surrounds all points. In computational geometry, convex hull is an important concept that involves how to effectively process and analyze the boundaries of a point set. The application of convex hull is very wide, including graphics, computer vision, geographic information systems and other fields. The calculation of convex hull can be implemented through different algorithms, such as Graham scanning method. These algorithms can effectively find the minimum convex polygon that contains a given set of points, thus playing an important role in practical applications. For example, in image processing, convex hull can be used to identify the outline of an object; in geographic information systems, convex hull can help analyze the shape and boundaries of an area, etc.

[0057] UAV route planning refers to planning a safe and efficient movement path for a UAV from a starting point to a target point in a given environment. The concept of convex hull has great application potential in UAV route planning. For example, by judging whether there is a possibility of intersection between two convex hulls, it can be judged whether there is a risk of conflict between any UAV routes within the two convex hulls, thereby greatly reducing the possibility of conflict between UAV routes and ensuring the safety of routes. For another example, when a UAV triggers a link break and homing operation due to link interruption or other emergencies, by determining a convex hull with flight safety, any straight return route of the UAV within the convex hull will not fly out of the convex hull range, thereby ensuring that the UAV can return quickly and safely in the shortest straight line path in the event of a link interruption or other emergencies.

[0058] The method for generating the convex space of the UAV route in step S101 is described below. The method for generating the convex space of the UAV route includes the following steps:

[0059] Step A100: According to the latitude and longitude coordinate values ​​of the waypoints in each UAV route, a first target point is determined from the waypoints and the first target point is set as the current target point.

[0060] The drone route in this embodiment may be a manually drawn route. In this embodiment, the manually drawn route data may be obtained through an imported route file. The route data here includes the latitude and longitude data and altitude data of each waypoint in the route. Figure 2FIG. 1 is a conceptual diagram of a drone route in an embodiment of the present invention. Figure 2 As shown in the left figure, four waypoints can be marked on the two-dimensional map first ( Figure 2 The waypoints are marked as A, B, C, and D in the figure), and then each waypoint is connected in sequence along the direction of flight by manual connection to form a route. The figure on the right shows the route, which includes three segments, each of which is interconnected in sequence, and each segment includes two waypoints. For example, the first segment includes waypoint A and waypoint B. The altitude of each waypoint on the drone route is usually a fixed altitude value generated by the system by default (for example, 3000 meters). It should be noted that, unless otherwise specified, in this article, the terms "waypoint" and "endpoint of the segment" have the same meaning.

[0061] The UAV route in this embodiment can also be automatically planned by the automatic route planning algorithm built into the UAV ground station software. The UAV ground station software can automatically generate a UAV route according to the terrain characteristics using the automatic route planning algorithm. The automatically planned route includes the latitude and longitude data and altitude data of each waypoint in the route.

[0062] In this embodiment, a two-dimensional convex hull can be generated based on the latitude and longitude data of each waypoint in the drone route. Specifically, in step A100, the first target point can be selected from all the waypoints of the drone route as the starting point of the two-dimensional convex hull based on the latitude and longitude data of each waypoint in the drone route. In some embodiments, the waypoint with the largest latitude value can be found from all the waypoints of the drone route as the first target point; if there are multiple waypoints with the largest latitude values, the waypoint with the largest longitude value can be selected from them as the first target point. The first target point here is the first target point in this embodiment. After obtaining the first target point, it can be set as the current target point and participate in the calculation of the following steps.

[0063] In some embodiments, the waypoint with the largest longitude value can be found from all the waypoints on the drone route as the first target point; if there are multiple waypoints with the largest longitude values, the waypoint with the largest latitude value can be selected as the first target point. The first target point here is the first target point in this embodiment. After the first target point is obtained, it can be set as the current target point and participate in the calculation of the following steps.

[0064] Step A200: Determine the next target point from the remaining waypoints based on the azimuths of the current target point and the remaining waypoints, wherein the starting direction of the azimuth of the current target point is the vector direction from the previous target point to the current target point, and the starting direction of the azimuth of the first target point is the vector direction from the first target point to the target direction.

[0065] In this embodiment, the azimuth between the current target point and all other waypoints can be calculated respectively, and then the waypoint with the smallest azimuth angle can be selected as the next target point. For example, if the current target point is the first target point (i.e., the starting point of the convex hull), the azimuth between the first target point and all other waypoints can be calculated respectively, and then the waypoint with the smallest azimuth angle can be selected as the second target point, and the second target point is the next target point in this embodiment. The starting direction of the azimuth angle of the first target point can be the vector direction pointing from the first target point to the target direction. The target direction here is a preset hyperparameter. For example, in order to make the search process of the target point proceed in a counterclockwise direction, it can be determined according to the characteristics of the position information of the first target point. For example, if the first target point is the waypoint with the largest latitude value, the target direction is due north; if the first target point is the waypoint with the largest longitude value, the target direction is due east. For another example, if the current target point is the second target point (i.e., the second point of the convex hull), the azimuth between the second target point and all other waypoints (including the first target point) can be calculated respectively, and then the waypoint with the smallest azimuth is selected as the third target point. The third target point is the next target point in this embodiment, and the starting direction of the azimuth of the second target point is the vector direction from the first target point to the second target point. For another example, if the current target point is the third target point (i.e., the third point of the convex hull), the azimuth between the third target point and all other waypoints (including the first target point and the second target point) can be calculated respectively, and then the waypoint with the smallest azimuth is selected as the fourth target point. The fourth target point is the next target point in this embodiment, and the starting direction of the azimuth of the third target point is the vector direction from the second target point to the third target point, and so on.

[0066] Step A300: Determine whether the next target point coincides with the first target point. If so, proceed to step A400; otherwise, set the next target point as the current target point and return to step A200.

[0067] In this embodiment, it can be determined whether the next target point returns to the first target point. If so, enter step A400. Otherwise, after setting the next target point as the current target point, return to step A200 to continue calculation until the next target point in step A300 coincides with the first target point.

[0068] Step A400: sequentially connect all target points and generate a convex space according to the height values ​​of the waypoints in the UAV route.

[0069] In this embodiment, the two-dimensional convex hull can be obtained by sequentially connecting all target points. Figure 3 An example of a two-dimensional convex hull generated by a method according to an embodiment of the present invention is shown. Figure 3Steps A100 to A400 are described below. Figure 3 As shown, the drone route has a total of 7 waypoints, which are recorded as waypoint 1, waypoint 2, waypoint 3, waypoint 4, waypoint 5, waypoint 6, and waypoint 7. The algorithm for generating the two-dimensional convex hull includes:

[0070] 1. According to the longitude and latitude coordinates of all waypoints, find the waypoint with the largest latitude value, which is waypoint 2, and record it as point A. Point A is the starting point of the convex hull, and point A is retained.

[0071] 2. Calculate the azimuth between point A and all other waypoints. The result is that the azimuth between waypoint 7 and waypoint 2 is the smallest. Record waypoint 7 as point B and keep point B. The starting direction of the azimuth of point A is that point A points to the due north.

[0072] 3. Next, calculate the azimuth between point B and all other waypoints. The starting direction of the azimuth is the vector direction from point A to point B. The result is that the azimuth between waypoint 5 and waypoint 7 is the smallest. Record waypoint 5 as point C and retain point C.

[0073] 3. Perform similar processing starting from waypoint 5. The original waypoint number corresponding to the obtained convex hull polygon (ABCDEA) is (2,7,5,4,1,2).

[0074] After obtaining the two-dimensional convex hull, the two-dimensional convex hull can be converted into a convex space according to the height data of each waypoint in the UAV route. Figure 3 In the example, we can compare the altitude values ​​of waypoints 1 to 7, and then take the minimum and maximum altitude values. The resulting altitude interval is the altitude range of the convex space.

[0075] Figure 4 FIG. 2 is a flow chart showing a method for generating a convex space of a drone route according to another embodiment of the present invention. Figure 4 As shown, the method for generating the convex space of the UAV route includes the following steps:

[0076] Step A101: According to the latitude and longitude coordinate values ​​of waypoints in the UAV route, a first target point is determined from the waypoints and the first target point is set as the current target point.

[0077] Step A102: Determine the next target point from the remaining waypoints based on the azimuths of the current target point and the remaining waypoints, wherein the starting direction of the azimuth of the current target point is the vector direction from the previous target point to the current target point, and the starting direction of the azimuth of the first target point is the vector direction from the first target point to the target direction.

[0078] Step A103: Determine whether the next target point coincides with the first target point. If so, proceed to step A104. Otherwise, set the next target point as the current target point and return to step A102.

[0079] Step A104: Sequentially connect all target points and generate a convex space based on the height values ​​of the waypoints in the UAV route.

[0080] Step A105: Determine the boundary of the buffer zone of the convex space according to the positional relationship between the centroid of the convex hull formed by sequentially connecting all target points and the edge of the convex hull.

[0081] Steps A101 to A104 are basically the same as steps A100 to A400, and are not described in detail here. The following description focuses on step A105.

[0082] In this embodiment, the boundary of the buffer zone of the convex space can be determined according to the positional relationship between the centroid of the convex hull and the edge of the convex hull formed in steps A101 to A104. Specifically, the following steps can be included:

[0083] Step A10: If the center of gravity of the convex hull is on one side of the edge of the convex hull, draw a parallel line to the opposite side that is parallel to the edge of the convex hull; wherein the distance between the parallel line and the edge of the convex hull is a preset safety threshold.

[0084] Step A20: Fitting the gaps between adjacent parallel lines with a curve.

[0085] Step A30: sequentially connect parallel lines and curves to obtain the boundary of the buffer zone of the convex space.

[0086] Figure 5 An example of a buffer zone of a convex space formed according to steps A10 to A30 is shown below. Figure 5 Step A10 to Step A30 are described.

[0087] like Figure 5 As shown, first calculate the centroid of the convex hull polygon, denoted as point O, which can be obtained by calculating the weighted average of the coordinates of all vertices of the convex hull polygon.

[0088] Next, take any side AB of the convex hull polygon and determine the positional relationship between point O and AB. If point O is on one side of AB, draw parallel lines to the opposite side of AB. The distance between the parallel lines is the preset safety threshold. After that, traverse all the sides of the convex hull polygon and repeat the above steps until all the sides of the convex hull polygon are drawn parallel to the opposite side. The distance between the parallel lines and the sides of the convex hull polygon is the preset safety threshold.

[0089] In some embodiments, one side AB of the convex hull polygon can be randomly selected to determine the positional relationship between point O and AB. If point O is on the right side of AB, parallel lines are drawn uniformly along all sides of the convex hull polygon to the left, and the distance between the parallel lines is the preset safety threshold; otherwise, parallel lines are drawn uniformly to the right, and the distance between the parallel lines is also the preset safety threshold. In this embodiment, only one side needs to be determined to determine the positional relationship between point O and all other sides of the convex hull polygon, thereby improving the efficiency of the algorithm.

[0090] Afterwards, the gaps between adjacent parallel lines are fitted with arcs, and the arc radius is also the preset safety threshold.

[0091] Finally, parallel lines and arcs are sequentially connected at intervals to form a closed polygon, that is, the buffer zone of the convex space is obtained.

[0092] exist Figure 5 In the figure, the center of gravity O of the convex hull polygon (ABCDEA) is on the right side of the boundary lines AB, BC, CD, DE, and EA. Draw parallel lines on the left side of each boundary line, namely A 1 B 1 , B 2 C 1 , C 2 D 1 , D 2 E 1 、E 2 A 2 , parallel line A 1 B 1 , B 2 C 1 , C 2 D 1 , D 2 E 1 、E 2 A 2 The distances from the boundary lines AB, BC, CD, DE, and EA are all preset safety thresholds; then, the adjacent parallel lines A 1 B 1 and B 2 C 1 , adjacent parallel lines B 2 C 1 and C 2 D 1 , adjacent parallel lines C 2 D 1 and D 2 E 1 , adjacent parallel lines D 2 E 1 and E 2 A 2The gap part is fitted with an arc, and the arc radius is also the preset safety threshold; the convex hull buffer zone formed at last is: A 1 B 1 B 2 C 1 C 2 D 1 D 2 E 1 E 2 A 2 A 1 , where B 1 B 2 , C 1 C 2 , D 1 D 2 、E 1 E 2 , A 2 A 1 They are all arc segments.

[0093] The convex space buffer in the embodiment of the present invention can solve the safety risks that may be caused by multiple routes being too close to each other. By expanding an area of ​​a threshold value for each convex hull polygon, as long as the convex spaces corresponding to the routes do not intersect, the distance between the two drones must be within a safety threshold.

[0094] Step S102: Determine whether the convex spaces of the drone routes intersect. If so, there is a conflict between the drone routes. Otherwise, there is no conflict between the drone routes.

[0095] In this embodiment, the convex space of drone routes can be used to determine whether there is a possibility of intersection between drone routes. If the convex spaces of two drone routes do not intersect, the two drone routes must not intersect. If the convex spaces of two drone routes intersect, although the drone routes may not intersect in a small number of cases, this embodiment of the present invention ignores such a small number of cases. In this embodiment, judging whether the convex spaces of two drone routes intersect is equivalent to whether the drone routes intersect, thereby ensuring the absolute safety between the drone routes.

[0096] In some embodiments, step S102 includes the following steps:

[0097] Step S100: Determine whether the height ranges between the convex spaces of the drone routes intersect. If not, there is no conflict between the drone routes; otherwise, proceed to step S200.

[0098] Step S200: Determine whether the boundary lines between the convex spaces of the drone routes intersect. If so, there is a conflict between the drone routes; otherwise, proceed to step S300.

[0099] Step S300: Determine whether there is an inclusion relationship between the convex spaces of the drone routes. If so, there is a conflict between the drone routes; otherwise, there is no conflict between the drone routes.

[0100] Exemplarily, assume that there are two convex spaces, denoted as convex space A and convex space B, and convex space B is the convex space to be detected. In step S100, the height ranges of convex space A and convex space B can be compared. If the height ranges of the two do not intersect, the judgment is terminated directly and the result that convex space B does not intersect with convex space A is output, that is, there is no risk of conflict between the two drone routes corresponding to convex space A and convex space B; if the height ranges of the two intersect, then go to step S200 for further judgment. In step S200, the boundary lines L of convex space A and convex space B can be taken respectively. A and L B , then the boundary line L A and L B If there is an intersection, it means that the two convex spaces intersect, and the corresponding two UAV routes have a risk of conflict. At this time, the judgment ends and the result of the conflict between the UAV routes is output; if there is no intersection, continue to take other boundary lines L of convex space A and convex space B ’ A and L ’ B , then the boundary line L ’ A and L ’ B Intersection judgment is performed between them, and the judgment process is the same as L A and L B If all boundary lines of convex space B and convex space A are traversed and all boundary lines of convex space A and convex space B do not intersect, then proceed to step S300 for further judgment, otherwise output the result that the two UAV routes conflict.

[0101] In step S300, it can be further determined whether there is an inclusion relationship between convex space A and convex space B. The inclusion relationship here includes that convex space A contains convex space B and convex space B contains convex space A. If convex space A contains convex space B or convex space B contains convex space A, then there is an inclusion relationship between convex space A and convex space B. At this time, convex space B intersects with convex space A, and the result that the two drone routes conflict is output. If convex space B does not have an inclusion relationship with convex space A, the result that the two drone routes do not conflict is output.

[0102] In some embodiments, step S300 includes: determining whether there is an inclusion relationship between the drone route convex spaces according to the positional relationship of the centers of gravity between the drone route convex spaces.

[0103] In some embodiments, judging whether there is a containment relationship between the convex spaces of the drone routes according to the positional relationship of the centers of gravity between the convex spaces of the drone routes comprises the following steps:

[0104] Step S10: obtaining the center of gravity of the convex space of the drone route to be detected;

[0105] Step S20: Determine whether the center of gravity is inside the other UAV route convex space. If so, the UAV route convex space to be detected and the other UAV route convex space have an inclusion relationship; otherwise, proceed to step S30;

[0106] Step S30: Obtaining the center of gravity of another convex space of the UAV route;

[0107] Step S40: Determine whether the other center of gravity is inside the convex space of the drone route to be detected. If so, there is an inclusion relationship between the convex space of the drone route to be detected and the other convex space of the drone route; otherwise, there is no inclusion relationship.

[0108] For example, it is assumed that there are two convex spaces, which are respectively denoted as convex space A and convex space B, and convex space B is the convex space to be detected. In this embodiment, the centroid O of convex space B can be first obtained. 1 , then judge O 1 Is it inside the convex space A? If O 1 If O falls inside convex space A, it means that convex space A contains convex space B. At this time, convex space B intersects with convex space A, and the output is that there is a conflict between the two drone routes. 1 If it falls outside the convex space A, the center of gravity O of the convex space A can be obtained. 2 , then judge O 2 Is it inside the convex space B? If O 2 If O falls inside convex space B, it means that convex space B contains convex space A. At this time, convex space B intersects with convex space A, and the output is that there is a conflict between the two drone routes. 2 If it falls outside the convex space B, it means that the convex space B does not intersect with the convex space A. At this time, the output result is that there is no conflict between the two drone routes.

[0109] Figure 6-1 to Figure 6-3 Three examples of intersecting convex spaces according to embodiments of the present invention are shown. Figure 6-1 to Figure 6-3 In the example, the boundary line of the convex space A is: A 1 B 1 B 2 C 1 C 2 D 1 D 2 E1 E 2 A 2 A 1 , the boundary line of convex space B is: A 1 1 B 1 1 B 2 1 C 1 1 C 2 1 D 1 1 D 2 1 A 2 1 A 1 1 .exist Figure 6-1 In the convex space A, the boundary line A 1 B 1 and the boundary line D of the convex space B 2 1 A 2 1 intersect, so convex space A and convex space B intersect. Figure 6-2 In the example, the center of gravity of the convex space B is O 1 falls inside convex space A, so convex space A contains convex space B, and convex space A and convex space B intersect. Figure 6-3 In the example, the center of gravity O of the convex space A is 2 It falls inside the convex space B, so the convex space B contains the convex space A, and the convex space A and the convex space B intersect.

[0110] Figure 7 FIG. 2 shows an exemplary block diagram of a device for detecting a conflict of a drone route according to an embodiment of the present invention. Figure 7 As shown, the conflict detection device 700 for the drone route includes: a convex space generation module 701, which is configured to generate at least two drone route convex spaces according to the coordinate values ​​of the waypoints in at least two drone routes, wherein the drone route convex space includes all the waypoints in the drone route; and a convex space intersection judgment module 702, which is configured to judge whether the drone route convex spaces intersect, if so, there is a conflict between the drone routes, otherwise there is no conflict between the drone routes.

[0111] It should be understood that Figure 7 The various modules of the apparatus 700 shown in FIG. Figure 1 The steps in the described method correspond to each other. Therefore, the operations, features and advantages described above for the method are also applicable to the device 700 and the modules included therein. For the sake of brevity, some operations, features and advantages are not repeated here.

[0112] Figure 8 8 is a schematic block diagram of an example electronic device 800 that can be used to implement embodiments of the present disclosure. Figure 8 , a block diagram of an electronic device 800 that can serve as a server or client of the present disclosure will now be described, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein. Figure 8 As shown, the electronic device 800 includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. In RAM803, various programs and data required for the operation of the device 800 can also be stored. The computing unit 801, ROM802 and RAM803 are connected to each other through a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804. Multiple components in the device 800 are connected to the I / O interface 805, including: an input unit 806, such as a keyboard, a mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a disk, an optical disk, etc.; and a communication unit 809, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0113] The computing unit 801 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 801 performs the various methods and processes described above, such as the conflict detection method for the drone route. For example, in some embodiments, the conflict detection method for the drone route may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 808. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the gift package recommendation method described above may be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to perform the conflict detection method for the drone route in any other appropriate manner (e.g., by means of firmware).

[0114] Compared with the prior art, the embodiments of the present invention can achieve at least one of the following beneficial effects:

[0115] 1. The scheme of the present invention provides a reliable and efficient method for detecting conflicts between UAV routes, which can quickly detect whether multiple UAV routes intersect in space, provide a reliable reference basis for further optimizing UAV routes, and ensure the safe flight of multiple UAV routes.

[0116] 2. The solution of the present invention utilizes the characteristic that the line connecting any two points in the convex space must be contained in the convex space itself, which meets the conflict detection requirements of straight-line homing and theoretically solves the possibility of conflict between routes during straight-line homing operations.

[0117] 3. The solution of the present invention utilizes the characteristic that the convex space is the smallest convex polygon containing the route, which can ensure that the drone occupies as little airspace resources as possible when returning in a straight line, ensuring that the airspace resources occupied by each route are minimized.

[0118] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for detecting conflict of unmanned aerial vehicle routes, characterized in that: The following steps are involved: Generate at least two UAV route convex spaces according to the coordinate values ​​of the waypoints in at least two UAV routes, wherein the UAV route convex spaces contain all the waypoints in the UAV routes; as well as It is determined whether the convex spaces of the drone routes intersect each other. If so, there is a conflict between the drone routes. Otherwise, there is no conflict between the drone routes.

2. The conflict detection method according to claim 1, characterized in that: Determining whether the convex spaces of the drone routes intersect includes: Step S100: determining whether the height ranges between the convex spaces of the drone routes intersect, if not, there is no conflict between the drone routes; otherwise, proceeding to step S200; Step S200: Determine whether the boundary lines between the convex spaces of the drone routes intersect, if so, there is a conflict between the drone routes; otherwise, proceed to step S300; Step S300: Determine whether there is an inclusion relationship between the convex spaces of the drone routes. If so, there is a conflict between the drone routes; otherwise, there is no conflict between the drone routes.

3. The conflict detection method according to claim 2, characterized in that: Determining whether there is an inclusion relationship between the convex spaces of the drone routes includes: According to the positional relationship of the centers of gravity between the convex spaces of the drone routes, it is determined whether there is an inclusion relationship between the convex spaces of the drone routes.

4. The conflict detection method according to claim 3, characterized in that: According to the positional relationship of the centers of gravity between the convex spaces of the drone routes, determining whether there is an inclusion relationship between the convex spaces of the drone routes includes: Step S10: obtaining the center of gravity of the convex space of the drone route to be detected; Step S20: Determine whether the center of gravity is inside the other UAV route convex space. If so, the UAV route convex space to be detected and the other UAV route convex space have an inclusion relationship; otherwise, proceed to step S30; Step S30: Obtaining the center of gravity of another convex space of the UAV route; Step S40: Determine whether the other center of gravity is inside the convex space of the drone route to be detected. If so, there is an inclusion relationship between the convex space of the drone route to be detected and the other convex space of the drone route; otherwise, there is no inclusion relationship.

5. The conflict detection method according to claim 4, characterized in that: Determining whether the center of gravity is inside the convex space of another drone route or determining whether another center of gravity is inside the convex space of the drone route to be detected includes: The ray method in computer graphics is used to determine whether the center of gravity is inside the convex space of the UAV route.

6. The conflict detection method according to claim 1, characterized in that: Generating at least two UAV route convex spaces according to the coordinate values ​​of the waypoints in at least two UAV routes includes: Step A100: according to the latitude and longitude coordinate values ​​of the waypoints in each UAV route, determine a first target point from the waypoints and set the first target point as the current target point; Step A200: determining the next target point from the remaining waypoints according to the azimuths of the current target point and the remaining waypoints, wherein the starting direction of the azimuth of the current target point is the vector direction from the previous target point to the current target point, and the starting direction of the azimuth of the first target point is the vector direction from the first target point to the target direction; Step A300: determining whether the next target point coincides with the first target point, if so, proceeding to step A400, otherwise, setting the next target point as the current target point and returning to step A200; Step A400: sequentially connect all target points and generate a convex space according to the height values ​​of the waypoints in the UAV route.

7. The conflict detection method according to claim 6, characterized in that: Generating at least two UAV route convex spaces according to the coordinate values ​​of the waypoints in the at least two UAV routes also includes the following steps: The boundary of the buffer zone of the convex space is determined according to the positional relationship between the centroid of the convex hull formed by sequentially connecting all target points and the edge of the convex hull.

8. The conflict detection method according to claim 7, characterized in that: Determining the boundary of the buffer zone of the convex space according to the positional relationship between the centroid of the convex hull and the edge of the convex hull includes: Determine whether the center of gravity of the convex hull is on the right side of the edge of the convex hull. If so, draw a parallel line to the left that is parallel to the edge of the convex hull; otherwise, draw a parallel line to the right that is parallel to the edge of the convex hull; wherein the distance between the parallel line and the edge of the convex hull is a preset safety threshold; Fitting the gaps between adjacent parallel lines with a curve; and The parallel lines and the curves are sequentially connected to obtain a boundary of a buffer zone of the convex space.

9. A device for detecting conflict of unmanned aerial vehicle routes, characterized in that: include: A convex space generation module is configured to generate at least two drone route convex spaces according to the coordinate values ​​of the waypoints in at least two drone routes, wherein the drone route convex spaces contain all the waypoints in the drone routes; as well as The convex space intersection judgment module is configured to judge whether the convex spaces of the drone routes intersect. If so, there is a conflict between the drone routes; otherwise, there is no conflict between the drone routes.

10. An electronic device comprising: at least one processor; A memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the conflict detection method for the drone route according to any one of claims 1-8.

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