CN112799432B

CN112799432B - Obstacle avoidance control method and device for unmanned aerial vehicle, storage medium and electronic equipment

Info

Publication number: CN112799432B
Application number: CN202110377887.6A
Authority: CN
Inventors: 毛一年; 安培; 张邦彦; 张继伟; 眭泽智; 黄金鑫
Original assignee: Beijing Sankuai Online Technology Co Ltd
Current assignee: Beijing Sankuai Online Technology Co Ltd
Priority date: 2021-04-08
Filing date: 2021-04-08
Publication date: 2021-07-02
Anticipated expiration: 2041-04-08
Also published as: CN112799432A

Abstract

The utility model relates to an unmanned aerial vehicle keeps away barrier control method, device, storage medium and electronic equipment, relates to unmanned aerial vehicle control technical field, and the method includes: the unmanned aerial vehicle control center receives the air route information of a plurality of unmanned aerial vehicles, and according to the air route information of each unmanned aerial vehicle and the preset obstacle avoidance distance, the conflict time information corresponding to the air route planned for each unmanned aerial vehicle is determined, then according to the conflict time information corresponding to the air route planned for each unmanned aerial vehicle and the preset target constraint condition, the flight parameters of each unmanned aerial vehicle are adjusted, and the flight parameters comprise: the departure time and/or the planned speed corresponding to the route section between the driving positions on the route planned for the unmanned aerial vehicle. To every unmanned aerial vehicle, the unmanned aerial vehicle control center sends the flight parameter of this unmanned aerial vehicle after the adjustment to this unmanned aerial vehicle, and unmanned aerial vehicle flies according to the flight parameter that corresponds after the adjustment. This openly can be simultaneously, control a large amount of unmanned aerial vehicle flight fast.

Description

Obstacle avoidance control method and device for unmanned aerial vehicle, storage medium and electronic equipment

Technical Field

The present disclosure relates to the field of unmanned aerial vehicle control technologies, and in particular, to an obstacle avoidance control method and apparatus for an unmanned aerial vehicle, a storage medium, and an electronic device.

Background

With the continuous development of the unmanned aerial vehicle technology, the unmanned aerial vehicle has been widely applied in the fields of aerial photography, agriculture, distribution and the like. In the delivery scene, because the quantity of order is great to the order requires highly to the real-time, consequently can appear having the condition that a large amount of unmanned aerial vehicles travel in the same region, consequently need the flight of reasonable control every unmanned aerial vehicle to guarantee can not bump between the unmanned aerial vehicle. Under the general condition, collision detection can be carried out according to the corresponding air route of each unmanned aerial vehicle and time and space, so that each unmanned aerial vehicle is controlled, the calculated amount and the time delay are large, and the method is difficult to be suitable for a real-time control scene.

Disclosure of Invention

The invention aims to provide an obstacle avoidance control method and device for an unmanned aerial vehicle, a storage medium and electronic equipment, which are used for solving the related problems in the prior art.

According to a first aspect of the embodiments of the present disclosure, there is provided an obstacle avoidance control method for an unmanned aerial vehicle, the method including:

the method comprises the steps that an unmanned aerial vehicle control center receives route information of a plurality of unmanned aerial vehicles, wherein the route information comprises a plurality of driving positions on a route planned for the unmanned aerial vehicle and planned speeds corresponding to route sections between the driving positions;

the unmanned aerial vehicle control center determines conflict time information corresponding to each unmanned aerial vehicle planned route according to the route information of each unmanned aerial vehicle and a preset obstacle avoidance distance, wherein the conflict time information comprises: a conflict time range corresponding to the planned route for the unmanned aerial vehicle and the planned routes for each unmanned aerial vehicle;

the unmanned aerial vehicle control center adjusts the flight parameters of each unmanned aerial vehicle according to the conflict time information corresponding to the planned air route of each unmanned aerial vehicle and the preset target constraint condition, wherein the flight parameters comprise: taking off time and/or a planned speed corresponding to a route segment between each driving position on a route planned for the unmanned aerial vehicle;

for each unmanned aerial vehicle, the unmanned aerial vehicle control center sends the adjusted flight parameters of the unmanned aerial vehicle to the unmanned aerial vehicle;

and the unmanned aerial vehicle flies according to the adjusted corresponding flight parameters.

Optionally, the adjusting, by the drone control center, the flight parameter of each drone according to the conflict time information corresponding to the planned route for each drone and a preset target constraint condition includes:

determining the target constraint condition according to the conflict time information corresponding to each planned air route of the unmanned aerial vehicle, wherein the target constraint condition comprises: a difference between a takeoff time of a first drone and a takeoff time of a second drone, belonging to a time range outside a conflict time range corresponding to the flight path planned for the first drone and the flight path planned for the second drone; the first unmanned aerial vehicle is any one of the unmanned aerial vehicles, and the second unmanned aerial vehicle is any one of the unmanned aerial vehicles except the first unmanned aerial vehicle;

and adjusting the takeoff time of each unmanned aerial vehicle according to the target constraint condition.

Optionally, the adjusting the takeoff time of each of the drones according to the target constraint condition includes:

under the condition that the target constraint condition is met, solving an objective function through a preset optimization algorithm to obtain the takeoff time of each unmanned aerial vehicle when the objective function is minimum, wherein variables in the objective function comprise the takeoff time of each unmanned aerial vehicle, and the objective function is positively correlated with the sum of the takeoff times of each unmanned aerial vehicle.

Optionally, the objective function is a sum of products of the takeoff time of each drone and a weight corresponding to the drone, and the weight corresponding to the drone is determined according to the takeoff priority of the drone and/or the priority of the airline planned for the drone.

Optionally, the determining, by the drone control center, collision time information corresponding to a planned route for each drone according to the route information of each drone and a preset obstacle avoidance distance includes:

determining that a first driving position on a first air route corresponds to a conflict position range on a second air route, wherein the distance between any driving position in the conflict position range and the first driving position is smaller than or equal to the obstacle avoidance distance; the first air route and the second air route are air routes planned for any unmanned aerial vehicle, and the first driving position is any driving position on the first air route;

determining a conflict time period of the first driving position corresponding to the second air route according to a conflict position range of the first driving position corresponding to the second air route, a driving time length corresponding to the first air route and a driving time length corresponding to the second air route;

and combining the conflict time periods of each driving position on the first air route corresponding to the second air route to obtain a conflict time range corresponding to the first air route and the second air route, wherein the conflict time range is used for representing the interval between the takeoff time of the unmanned aerial vehicle distributed on the first air route and the takeoff time of the unmanned aerial vehicle distributed on the second air route.

Optionally, the determining, according to the range of the conflict position of the first driving position on the second airline, the driving duration corresponding to the first airline, and the driving duration corresponding to the second airline, the conflict time period of the first driving position corresponding to the second airline includes:

determining two boundary driving positions on the boundary of the conflict position range of the first driving position corresponding to the second route;

determining a first relative time length according to the first driving position and the driving time length corresponding to the first route, wherein the first relative time length is the time length from the initial driving position of the first route to the first driving position;

determining a second relative time length corresponding to each boundary driving position according to each boundary driving position and the driving time length corresponding to the second air route, wherein the second relative time length is the time length from the initial driving position of the second air route to the boundary driving position;

and determining a conflict time period of the first driving position corresponding to the second air route according to the first relative time length and a second relative time length corresponding to each boundary driving position.

Optionally, the determining the conflict time period of the second route corresponding to the first driving position according to the first relative duration and the second relative duration corresponding to each boundary driving position includes:

and determining the conflict time period of the first driving position corresponding to the second air route according to the preset redundant time length and the difference between the second relative time length corresponding to each boundary driving position and the first relative time length.

Optionally, the determining, according to a preset redundant time length and a difference between a second relative time length corresponding to each boundary driving position and the first relative time length, a collision time period of the second route corresponding to the first driving position includes:

determining a starting boundary driving position and an ending boundary driving position in the two boundary driving positions, wherein the difference between the first relative duration and a second relative duration corresponding to the starting boundary driving position is smaller than the difference between the first relative duration and the second relative duration corresponding to the ending boundary driving position;

subtracting the redundant time length from the difference between the first relative time length and a second relative time length corresponding to the starting boundary driving position to obtain the starting time of the conflict time period of the second air route corresponding to the first driving position;

and adding the redundant time length to the difference between the first relative time length and a second relative time length corresponding to the end boundary driving position to obtain the end time of the conflict time period of the second air route corresponding to the first driving position.

Optionally, the target constraint further includes: the difference between the takeoff time of the first unmanned aerial vehicle and the takeoff time of the third unmanned aerial vehicle belongs to a time range outside a conflict time range corresponding to the flight path planned for the first unmanned aerial vehicle and the flight path planned for the third unmanned aerial vehicle, and the third unmanned aerial vehicle is an unmanned aerial vehicle allocated with the takeoff time.

Optionally, the target constraint further includes: if the takeoff priority of the first unmanned aerial vehicle is higher than that of the second unmanned aerial vehicle, the takeoff time of the first unmanned aerial vehicle is before that of the second unmanned aerial vehicle; and/or the presence of a gas in the gas,

the takeoff time of the first unmanned machine is before the appointed time of the first unmanned machine, the appointed time of the first unmanned machine is determined according to flight constraint parameters of the first unmanned machine, and the flight constraint parameters comprise at least one of the following parameters: the residual electric quantity, the running time corresponding to the planned route and the forced takeoff time.

According to a second aspect of the embodiments of the present disclosure, there is provided an obstacle avoidance control device for an unmanned aerial vehicle, the device including:

the system comprises a receiving module, a control module and a control module, wherein the receiving module is used for receiving route information of a plurality of unmanned aerial vehicles through an unmanned aerial vehicle control center, and the route information comprises a plurality of driving positions on a route planned for the unmanned aerial vehicle and planning speeds corresponding to route sections between the driving positions;

the determining module is used for determining conflict time information corresponding to each unmanned aerial vehicle planned route through the unmanned aerial vehicle control center according to the route information of each unmanned aerial vehicle and a preset obstacle avoidance distance, wherein the conflict time information comprises: a conflict time range corresponding to the planned route for the unmanned aerial vehicle and the planned routes for each unmanned aerial vehicle;

an adjusting module, configured to adjust, by the drone control center, a flight parameter of each drone according to conflict time information corresponding to a planned route for each drone and a preset target constraint condition, where the flight parameter includes: taking off time and/or a planned speed corresponding to a route segment between each driving position on a route planned for the unmanned aerial vehicle;

the sending module is used for sending the adjusted flight parameters of the unmanned aerial vehicle to the unmanned aerial vehicle through the unmanned aerial vehicle control center aiming at each unmanned aerial vehicle;

and the control module is used for flying according to the adjusted corresponding flight parameters through the unmanned aerial vehicle.

Optionally, the adjusting module includes:

a first determining submodule, configured to determine the target constraint condition according to conflict time information corresponding to a planned route for each unmanned aerial vehicle, where the target constraint condition includes: a difference between a takeoff time of a first drone and a takeoff time of a second drone, belonging to a time range outside a conflict time range corresponding to the flight path planned for the first drone and the flight path planned for the second drone; the first unmanned aerial vehicle is any one of the unmanned aerial vehicles, and the second unmanned aerial vehicle is any one of the unmanned aerial vehicles except the first unmanned aerial vehicle;

and the adjusting submodule is used for adjusting the takeoff time of each unmanned aerial vehicle according to the target constraint condition.

Optionally, the adjusting submodule is configured to:

Optionally, the determining module includes:

the second determination submodule is used for determining that a first driving position on a first air route corresponds to a conflict position range on a second air route, and the distance between any driving position in the conflict position range and the first driving position is smaller than or equal to the obstacle avoidance distance; the first air route and the second air route are air routes planned for any unmanned aerial vehicle, and the first driving position is any driving position on the first air route;

the third determining submodule is used for determining a conflict time period of the first driving position corresponding to the second air route according to a conflict position range of the first driving position corresponding to the second air route, the driving time length corresponding to the first air route and the driving time length corresponding to the second air route;

and the merging submodule is used for merging the conflict time periods of each driving position on the first air route corresponding to the second air route so as to obtain a conflict time range corresponding to the first air route and the second air route, wherein the conflict time range is used for representing the interval between the takeoff time of the unmanned aerial vehicle distributed on the first air route and the takeoff time of the unmanned aerial vehicle distributed on the second air route.

Optionally, the third determining sub-module is configured to:

According to a third aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of the first aspect.

According to a fourth aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including:

a memory having a computer program stored thereon;

a processor for executing the computer program in the memory to implement the steps of the method of the first aspect.

Through the technical scheme, the unmanned aerial vehicle control center firstly receives the route information of a plurality of unmanned aerial vehicles in the disclosure, wherein the planned speed corresponding to a plurality of running positions on the route planned for the unmanned aerial vehicle and the route section between each running position is included, then, according to the route information of each unmanned aerial vehicle and the preset obstacle avoidance distance, the conflict time information corresponding to the route planned for each unmanned aerial vehicle is determined, wherein the conflict time range corresponding to the route planned for the unmanned aerial vehicle and the route planned for each unmanned aerial vehicle is included, then, according to the conflict time information corresponding to the route planned for each unmanned aerial vehicle and the preset target constraint condition, the takeoff time of each unmanned aerial vehicle is adjusted, and/or the planned speed corresponding to the route section between the running positions on the route planned for the unmanned aerial vehicle is adjusted. To every unmanned aerial vehicle, the unmanned aerial vehicle control center sends the flight parameter of this unmanned aerial vehicle after the adjustment to this unmanned aerial vehicle, and is corresponding, and unmanned aerial vehicle flies according to the flight parameter of the correspondence after the adjustment. The flight of a plurality of unmanned aerial vehicles is controlled through conflict time information and target constraint conditions, and a large number of unmanned aerial vehicles on a plurality of air routes can be controlled to fly simultaneously and rapidly on the premise of ensuring safe driving of the unmanned aerial vehicles.

Additional features and advantages of the disclosure will be set forth in the detailed description which follows.

Drawings

The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure without limiting the disclosure. In the drawings:

fig. 1 is a flowchart illustrating an obstacle avoidance control method for a drone according to an exemplary embodiment;

fig. 2 is a flowchart illustrating another obstacle avoidance control method for a drone according to an exemplary embodiment;

fig. 3 is a flow chart illustrating another method of obstacle avoidance control for a drone in accordance with an exemplary embodiment;

FIG. 4 is a schematic diagram illustrating a first lane and a second lane, according to an exemplary embodiment;

fig. 5 is a block diagram illustrating an obstacle avoidance control apparatus of a drone according to an exemplary embodiment;

fig. 6 is a block diagram illustrating an obstacle avoidance control apparatus of another drone according to an exemplary embodiment;

fig. 7 is a block diagram illustrating an obstacle avoidance control apparatus of another drone according to an exemplary embodiment;

FIG. 8 is a block diagram illustrating an electronic device in accordance with an example embodiment.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

Before introducing the obstacle avoidance control method and apparatus for an unmanned aerial vehicle, a storage medium, and an electronic device provided by the present disclosure, an application scenario related to each embodiment in the present disclosure is first introduced. Embodiments provided by the present disclosure may be applied to various control scenarios of drones, such as drone logistics, drone takeaway distribution, and so on. The method comprises the steps that a plurality of air routes exist in an operating area, corresponding air routes can be planned for the unmanned aerial vehicles according to starting points and end points of tasks required to be executed by the unmanned aerial vehicles, namely zero, one or more unmanned aerial vehicles can be distributed on each air route, and the unmanned aerial vehicles distributed on the air routes run according to the air routes. When there are a plurality of unmanned aerial vehicles, need be under the prerequisite of guaranteeing that every unmanned aerial vehicle traveles safely (do not bump with other unmanned aerial vehicles promptly), control every unmanned aerial vehicle flight. In the operation area, including unmanned aerial vehicle control center and a plurality of unmanned aerial vehicle, unmanned aerial vehicle control center is used for managing a plurality of unmanned aerial vehicles, can be the server, include but not limited to: an entity server, a server cluster or a cloud server.

Fig. 1 is a flowchart illustrating an obstacle avoidance control method for a drone according to an exemplary embodiment, where as shown in fig. 1, the method includes the following steps:

step 101, an unmanned aerial vehicle control center receives route information of a plurality of unmanned aerial vehicles, wherein the route information comprises a plurality of driving positions on a route planned for the unmanned aerial vehicle and planning speeds corresponding to route segments between the driving positions.

For example, in a scene where multiple unmanned aerial vehicles need to be controlled to fly simultaneously, the unmanned aerial vehicle control center first receives route information sent by the multiple unmanned aerial vehicles, wherein the route information of each unmanned aerial vehicle includes planned speeds corresponding to multiple traveling positions on a route planned for the unmanned aerial vehicle and route segments between the traveling positions. Each route may include a plurality of driving positions, and the driving positions may be understood as points or line segments on the route, or the route may be understood as a connection of a plurality of driving positions, and the driving positions may be represented by coordinates corresponding to a three-dimensional coordinate system. The planned speed corresponding to the route segment between each driving position can be understood as the speed planned in advance by the unmanned aerial vehicle control center for the route segment between each two adjacent driving positions on the route, and when the unmanned aerial vehicle flies on the corresponding route, the unmanned aerial vehicle can fly according to the planned speed corresponding to the route segment between each driving position.

102, determining conflict time information corresponding to a planned route of each unmanned aerial vehicle by the unmanned aerial vehicle control center according to the route information of each unmanned aerial vehicle and a preset obstacle avoidance distance, wherein the conflict time information comprises: and the conflict time range corresponding to the planned route for the unmanned plane and the planned route for each unmanned plane.

For example, after acquiring the route information of each unmanned aerial vehicle, the unmanned aerial vehicle control center may determine, by combining a preset obstacle avoidance distance and a driving duration corresponding to each route, conflict time information corresponding to the route planned for each unmanned aerial vehicle. Wherein, the conflict time corresponding to any route may include: the conflict time range corresponding to the air route and each air route can be used for representing the takeoff time of the unmanned aerial vehicle distributed on the air route and the interval between the takeoff time of the unmanned aerial vehicle distributed on each air route. The conflict time range may also be understood as a time range in which the unmanned aerial vehicle allocated on each route takes off according to the respective preset time and flies at the planned speed corresponding to the route segment between the respective driving positions, and in the conflict time range, the distance between the unmanned aerial vehicle allocated on the route and the unmanned aerial vehicle allocated on each route is smaller than the obstacle avoidance distance, that is, there is a possibility of collision. The route conflict time table can be established according to the route information of each unmanned aerial vehicle, the driving time corresponding to each route and the preset obstacle avoidance distance, wherein the route conflict time table comprises the conflict time information corresponding to each route.

The driving time length corresponding to each route can be understood as the time length required for any unmanned aerial vehicle to drive on the route from the starting driving position (which can be understood as the starting point of the route) to the ending driving position (which can be understood as the ending point of the route) of the route. Therefore, the time length of the unmanned aerial vehicle running from the initial running position to any running position of the air route can be obtained according to the running time length corresponding to the air route (the difference between the time of the unmanned aerial vehicle running to the running position and the takeoff time of the unmanned aerial vehicle can also be understood).

Keep away barrier distance and can understand, on arbitrary air route, when unmanned aerial vehicle traveles certain position of traveling, will guarantee not to take place the conflict with other unmanned aerial vehicles, need with the distance that keeps between other unmanned aerial vehicles. The obstacle avoidance distance can be determined according to the size and the positioning precision of the unmanned aerial vehicle. For example, the sum of the radius and the positioning accuracy of the drone may be used as an obstacle avoidance distance, and the sum of the radius and the positioning accuracy of the drone and a preset redundant distance (which may be 1m, for example) may also be used as an obstacle avoidance distance. If the radiuses of the unmanned aerial vehicle in the three coordinate directions in the three-dimensional coordinate system are different from each other, the positioning accuracy in the three coordinate directions is different from each other, in one implementation mode, the obstacle avoidance distances in the three coordinate directions can be respectively set according to the radiuses and the positioning accuracy of the unmanned aerial vehicle in the three coordinate directions, the obstacle avoidance distances can also be understood as a vector, the three-dimensional obstacle avoidance distance comprises three dimensions, and the obstacle avoidance distance D = (D) is not only avoided_x，D_y，D_z) Wherein D is_xIndicating unmanned plane on X-axisDistance of obstacle avoidance, D_yIndicating the obstacle avoidance distance of the drone on the Y-axis, D_zAnd the obstacle avoidance distance of the unmanned aerial vehicle on the Z axis is represented. Like this, can be according to the obstacle-avoiding distance in the three coordinate direction, confirm one and keep away the obstacle space, when any unmanned aerial vehicle traveles certain position of traveling promptly, will guarantee not to take place the conflict with other unmanned aerial vehicles, need other unmanned aerial vehicles outside this unmanned aerial vehicle keeps away the obstacle space, do not in this unmanned aerial vehicle keeps away the obstacle space promptly. In another implementation, the obstacle avoidance distance may be determined by selecting the largest radius and the largest positioning accuracy in the three coordinate directions, that is, the obstacle avoidance distance D = max (R = max)_x，R_y，R_z）+ max（a_x，a_y，a_z) Wherein R is_xRepresenting the radius of the drone on the X-axis, R_yIndicating the radius of the drone on the Y-axis, R_zIndicating the radius of the drone in the Z axis, a_xIndicating the positioning accuracy of the drone on the X-axis, a_yIndicating the positioning accuracy of the drone on the Y-axis, a_zAnd the positioning precision of the unmanned aerial vehicle on the Z axis is shown.

And generating conflict time information corresponding to each air route according to a plurality of driving positions included on each air route, the driving time corresponding to the air route and a preset obstacle avoidance distance. For example, the first route and the second route are both any routes (that is, the first route and the second route may be the same route or may be two different routes). An implementation mode, a conflict time range of a first air route and a second air route can be determined, when an unmanned aerial vehicle runs to each running position on the first air route, which running positions on the second air route can conflict with the unmanned aerial vehicle, then the running positions on the first air route are determined, and under the condition that the unmanned aerial vehicle simultaneously appears at the running positions on the second air route, the takeoff time of the corresponding unmanned aerial vehicle on the first air route is different from the takeoff time of the corresponding unmanned aerial vehicle on the second air route, so that the conflict time range of the first air route and the second air route is obtained. In another implementation manner, the conflict time range between the first air route and the second air route may be determined by first determining the time for a certain unmanned aerial vehicle to travel to each travel position on the first air route when the certain unmanned aerial vehicle takes off according to a first preset time, determining the time for another unmanned aerial vehicle to travel to each travel position on the second air route when the another unmanned aerial vehicle takes off according to a second preset time (which may be the same as or different from the first preset time), then determining at which moments the distance between the two unmanned aerial vehicles is less than the obstacle avoidance distance, and finally determining the conflict time range between the first air route and the second air route according to the moments.

For example, N (N ≧ 1) preplanned airlines exist in the operating area, an airline conflict schedule can be established, as shown in Table 1, where an airline ID can uniquely identify an airline, and ConflictTime _ i _ j _ list represents a conflict time range (i and j may be the same) corresponding to an airline with airline ID i and an airline ID j. The flight path conflict time table comprises N columns, each column is conflict time information corresponding to one flight path, and each conflict time information comprises N conflict time ranges (namely N rows in the column), namely the flight path conflict time table comprises N × N conflict time ranges in total. For example, the first column is the conflict time information corresponding to the flight line with the flight line ID of 1, which includes N conflict time ranges from ConflictTime _1_1_ list to ConflictTime _ N _1_ list. In this way, the conflict time information corresponding to the air route planned for each unmanned aerial vehicle can be determined in a table look-up manner. For example, the conflict time information corresponding to each airline may be obtained according to the airline ID corresponding to the airline, and taking the airline conflict time table shown in table 1 as an example, to search for the conflict time information corresponding to any airline, the column in which the airline ID corresponding to the airline is located may be used as the conflict time information corresponding to the airline, where the conflict time range corresponding to the airline and each airline is included.

TABLE 1

Route ID	1	…	N
				1	ConflictTime_1_1_list	…	ConflictTime_1_N_list
…	…	…	…
				N	ConflictTime_N_1_list	…	ConflictTime_N_N_list

If ConflictTime _ i _ j _ list is-120 s to-60 s, 180s to 300s, then the difference between the departure time T1 of the UAV a assigned on the route with route ID i and the departure time T2 of the UAV b assigned on the route with route ID j should be outside the conflict time range, i.e. T1-T2< -120s, or 180s > T1-T2> -60s, or T1-T2>300 s. If unmanned aerial vehicle a is at 10: 10 take-off, then drone b should 10: 12, or 10: 07 to 10: 11, or 10: 05 before take-off.

103, the unmanned aerial vehicle control center adjusts the flight parameters of each unmanned aerial vehicle according to the conflict time information corresponding to the planned air route of each unmanned aerial vehicle and the preset target constraint condition, wherein the flight parameters comprise: the departure time and/or the planned speed corresponding to the route section between the driving positions on the route planned for the unmanned aerial vehicle.

For example, the drone control center may adjust the takeoff time of the drone and/or the planned speed corresponding to the route segment between the travel positions on the route planned for the drone, i.e., the flight parameters of the drone, according to the conflict time information corresponding to the route planned for each drone and the preset target constraint condition. Specifically, the target constraint condition may include multiple constraints, and for example, may include: in the multiple unmanned aerial vehicles, the difference between the takeoff times of every two unmanned aerial vehicles belongs to a time range outside a corresponding conflict time range between routes planned for the two unmanned aerial vehicles. Specifically, for every two unmanned aerial vehicles, the unmanned aerial vehicle control center can adjust the takeoff time of the two unmanned aerial vehicles according to the target constraint condition, so that the two unmanned aerial vehicles do not collide when taking off according to the adjusted takeoff time. The planning speed corresponding to the route section of the unmanned aerial vehicle between the driving positions can be adjusted, so that the two unmanned aerial vehicles do not collide when flying on the corresponding routes according to the adjusted planning speed. The takeoff time of the unmanned aerial vehicle and the planning speed corresponding to the flight path section between the driving positions can be adjusted simultaneously, so that the two unmanned aerial vehicles take off according to the adjusted takeoff time and do not collide when flying on the corresponding flight paths according to the adjusted planning speed.

And step 104, aiming at each unmanned aerial vehicle, the unmanned aerial vehicle control center sends the adjusted flight parameters of the unmanned aerial vehicle to the unmanned aerial vehicle.

And 105, flying the unmanned aerial vehicle according to the adjusted corresponding flight parameters.

The example, unmanned aerial vehicle control center can send the flight parameter that corresponds after every unmanned aerial vehicle adjustment to this unmanned aerial vehicle for every unmanned aerial vehicle all can fly according to the flight parameter that corresponds after the adjustment, that is to say a plurality of unmanned aerial vehicles can fly separately, has realized simultaneously, the purpose of controlling a large amount of unmanned aerial vehicle flights on a plurality of air routes fast. In addition, the adjusted air routes are determined according to the corresponding conflict time information of each air route and the preset target constraint condition, so that collision among a plurality of unmanned aerial vehicles can be avoided, and the safety degree of the unmanned aerial vehicles in flight is effectively ensured.

In summary, in the present disclosure, the drone control center first receives the flight path information of multiple drones, where the planned speed corresponding to the flight path segment between the multiple driving positions and each driving position on the flight path planned for the drone is included, and then determines the conflict time information corresponding to the flight path planned for each drone according to the flight path information of each drone and the preset obstacle avoidance distance, where the conflict time range corresponding to the flight path planned for the drone and the flight path planned for each drone is included, and then adjusts the takeoff time of each drone according to the conflict time information corresponding to the flight path planned for each drone and the preset target constraint condition, and/or adjusts the planned speed corresponding to the flight path segment between the driving positions on the flight path planned for the drone. To every unmanned aerial vehicle, the unmanned aerial vehicle control center sends the flight parameter of this unmanned aerial vehicle after the adjustment to this unmanned aerial vehicle, and is corresponding, and unmanned aerial vehicle flies according to the flight parameter of the correspondence after the adjustment. The flight of a plurality of unmanned aerial vehicles is controlled through conflict time information and target constraint conditions, and a large number of unmanned aerial vehicles on a plurality of air routes can be controlled to fly simultaneously and rapidly on the premise of ensuring safe driving of the unmanned aerial vehicles.

Fig. 2 is a flowchart illustrating another obstacle avoidance control method for a drone according to an exemplary embodiment, and as shown in fig. 2, step 103 may include:

step 1031, determining target constraint conditions according to the conflict time information corresponding to the air route planned for each unmanned aerial vehicle, wherein the target constraint conditions comprise: the difference between the takeoff time of the first drone and the takeoff time of the second drone belongs to a time range outside the conflict time range corresponding to the flight path planned for the first drone and the flight path planned for the second drone. The first unmanned aerial vehicle is any unmanned aerial vehicle, and the second unmanned aerial vehicle is any unmanned aerial vehicle except the first unmanned aerial vehicle.

And step 1032, adjusting the takeoff time of each unmanned aerial vehicle according to the target constraint condition.

With any two unmanned aerial vehicles: a first drone and a second drone. A route A is planned for the first unmanned aerial vehicle, and a route B is planned for the second unmanned aerial vehicle (the route A and the route B can be the same route or two different routes). The target constraint condition may include a difference between the takeoff time of the first drone and the takeoff time of the second drone, and belongs to a time range outside a conflict time range corresponding to the a route and the B route, that is, the difference between the takeoff time of the first drone and the takeoff time of the second drone is not within the conflict time range corresponding to the a route and the B route, and the constraint may be represented as constraint _ 1. If the corresponding conflict time range of the A route and the B route is as follows: -50s to-10 s, 70s to 150s, the takeoff time of the first drone being denoted T3 and the takeoff time of the second drone being denoted T4, then constraint _1 may be: T3-T4< -50s, or 70s > T3-T4> -10s, or T3-T4>150 s. It should be noted that the conflict time ranges are relative, and the conflict time range corresponding to the a route and the B route and the conflict time range corresponding to the B route and the a route should be symmetric, that is, the conflict time range corresponding to the B route and the a route is: -150s to-70 s, 10s to 50s, so the target constraint may also include: the difference between the takeoff time of the second drone and the takeoff time of the first drone belongs to a time range outside a conflict time range corresponding to the route B and the route a, the constraint may be represented as constraint _2, and constraint _2 may be: T4-T3< -150s, or 10s > T4-T3> -70s, or T4-T3>50 s.

Further, the takeoff time in the flight parameters of each drone may be adjusted according to target constraints.

Under the condition that the target constraint condition is met, solving the objective function through a preset optimization algorithm to obtain the takeoff time of each unmanned aerial vehicle when the objective function is minimum, wherein variables in the objective function comprise the takeoff time of each unmanned aerial vehicle, and the objective function is positively correlated with the sum of the takeoff time of each unmanned aerial vehicle.

For example, the takeoff time of each drone may be used as a variable to generate an objective function. The target function is positively correlated with the sum of the takeoff times of the multiple unmanned aerial vehicles, that is, the target function can reflect the multiple unmanned aerial vehiclesThe magnitude of the sum of the takeoff times of (c). For example, the sum of the takeoff times of the multiple unmanned aerial vehicles may be directly used as an objective function, and the takeoff times of the multiple unmanned aerial vehicles may be subjected to weighted summation to be used as the objective function, and the objective function may also be in other forms that satisfy positive correlation with the sum of the takeoff times of the multiple unmanned aerial vehicles, which is not specifically limited by the present disclosure. In an implementation, the take-off time of each unmanned aerial vehicle and the product of the weights corresponding to the unmanned aerial vehicle can be summed to obtain an objective function, wherein the weights corresponding to the unmanned aerial vehicle are determined according to the take-off priority of the unmanned aerial vehicle and/or the priority of the planned route for the unmanned aerial vehicle, the take-off priority of the unmanned aerial vehicle can be determined according to the emergency degree of the task executed by the unmanned aerial vehicle, and can also be determined according to the remaining capacity of the unmanned aerial vehicle, and the priority of the planned route for the unmanned aerial vehicle can be set according to specific requirements. The objective function can be expressed as

Wherein, Takeoff _ time _ m represents the Takeoff time of the mth unmanned plane, w_mAnd representing the weight corresponding to the mth unmanned aerial vehicle, wherein M is the number of the unmanned aerial vehicles.

After the objective function is determined, the objective function can be solved according to a preset optimization algorithm, so that a solution when the objective function is minimum, namely the takeoff time of each unmanned aerial vehicle when the objective function is minimum, is obtained. The optimization algorithm includes, but is not limited to, an analysis-based optimization algorithm (e.g., a sequential quadratic optimization algorithm, an interior point method, a mixed integer linear optimization algorithm, a mixed integer nonlinear optimization algorithm, etc.), a meta-heuristic algorithm (e.g., a genetic algorithm, an ant colony algorithm, etc.), a machine learning algorithm, etc., which is not specifically limited in this disclosure. Because the objective function is positively correlated with the sum of the takeoff times of the unmanned aerial vehicles, the takeoff time of each unmanned aerial vehicle obtained by solving the objective function through an optimization algorithm is the optimal solution for parallel scheduling of the unmanned aerial vehicles in an operating area, the limitation of a conflict time range can be met, the unmanned aerial vehicles are guaranteed to take off according to respective takeoff times, conflicts can not occur, the unmanned aerial vehicles can take off as soon as possible (namely the sum of the takeoff times of the unmanned aerial vehicles is the minimum), and the scheduling efficiency and the concurrency capability of the unmanned aerial vehicle control center are effectively improved.

Fig. 3 is a flowchart illustrating another obstacle avoidance control method for a drone according to an exemplary embodiment, and as shown in fig. 3, step 102 may include the following steps:

and 1021, determining that the first driving position on the first air route corresponds to a conflict position range on the second air route, and the distance between any driving position in the conflict position range and the first driving position is smaller than or equal to the obstacle avoidance distance. The first air route and the second air route are air routes planned for any unmanned aerial vehicle, and the first driving position is any driving position on the first air route.

And step 1022, determining a conflict time period of the first driving position corresponding to the second air route according to the conflict position range of the first driving position corresponding to the second air route, the driving time length corresponding to the first air route and the driving time length corresponding to the second air route.

And 1023, combining conflict time periods of the second air route corresponding to each driving position on the first air route to obtain a conflict time range corresponding to the first air route and the second air route, wherein the conflict time range is used for representing the interval between the takeoff time of the unmanned aerial vehicle distributed on the first air route and the takeoff time of the unmanned aerial vehicle distributed on the second air route.

For example, for a first driving position on a first route, it may be determined that the first driving position corresponds to a collision position range on a second route, the collision position range including at least one driving position, wherein a distance between each driving position and the first driving position is less than or equal to an obstacle avoidance distance. That is, when the drone travels to a first travel location on a first route, a conflict may occur with a drone located at any travel location within a range of conflict locations. As shown in fig. 4, a1 is a first driving position on the first route, a circle (a circle shown by a dotted line in fig. 4) is drawn with a center of a1 and an obstacle avoidance distance as a radius, and a portion of the second route located inside the circle is a collision position range of a1 corresponding to the second route: A2-S2, wherein the distances among A2, S2 and A1 are obstacle avoidance distances.

And then, determining a conflict time period of the first driving position corresponding to the second air route according to the conflict position range of the first driving position corresponding to the second air route, the driving time length corresponding to the first air route and the driving time length corresponding to the second air route. The first driving position corresponds to a conflict time period of the second air route, and it can be understood that if the unmanned aerial vehicle UVA1 takes off from the initial driving position of the first air route at the time t1 and drives to the time t2 when the first driving position is the time t2, if another unmanned aerial vehicle UVA2 simultaneously appears in the conflict position range at the time t2, it can be deduced that the UVA2 takes off from the initial driving position of the second air route between the time t3 and the time t4, and then the difference between the time t3 and the time t4 and the time t2 can be used as the conflict time period of the first driving position corresponding to the second air route.

After obtaining the conflict time period corresponding to each driving position on the first airline corresponding to the second airline, the plurality of conflict time periods may be combined, thereby obtaining the conflict time range corresponding to the first airline and the second airline. For example, if any two collision time periods are adjacent or intersect, the two collision time periods may be combined into one collision time period. For example, obtaining a total of 4 collision periods includes: 225s to 137s, -178s to 23s, 34s to 99s, 67s to 102s, then 225s to 137s and 178s to 23s may be combined into-225 s to-23 s, and 34s to 99s and 67s to 102s may be combined into 34s to 102s, thereby taking-225 s to-23 s, 34s to 102s as the collision time range.

Correspondingly, the implementation manner of adjusting the flight parameters of each unmanned aerial vehicle in step 103, the unmanned aerial vehicle control center can adjust the takeoff time of any two unmanned aerial vehicles according to the target constraint condition, so that the difference value of the takeoff time of the two unmanned aerial vehicles belongs to the time range outside the corresponding conflict time range between the air routes planned for the two unmanned aerial vehicles, and collision is avoided. The unmanned aerial vehicle control center also can adjust the planning speed that the airline section of this unmanned aerial vehicle between each driving position corresponds in conflict position within range according to the target constraint condition for this two unmanned aerial vehicles can not appear in conflict position within range simultaneously, and conflict position scope is staggered to two unmanned aerial vehicles promptly, thereby avoids the collision. The unmanned aerial vehicle control center can also adjust the takeoff time of the unmanned aerial vehicle and the planning speed corresponding to the route section between the driving positions according to the target constraint condition, so that the takeoff time difference of the two unmanned aerial vehicles belongs to the time range outside the corresponding conflict time range between the routes planned for the two unmanned aerial vehicles, and the two unmanned aerial vehicles cannot appear in the conflict position range at the same time, thereby avoiding collision.

In one application scenario, step 1022 may be implemented by:

step 1) two boundary driving positions located on the boundary of the collision position range of the first driving position corresponding to the second route are determined.

And 2) determining a first relative time length according to the first driving position and the driving time length corresponding to the first air route, wherein the first relative time length is the time length from the initial driving position of the first air route to the first driving position.

And 3) determining a second relative time length corresponding to the boundary driving position according to each boundary driving position and the driving time length corresponding to the second air route, wherein the second relative time length is the time length from the initial driving position of the second air route to the boundary driving position.

And 4) determining a conflict time period of the first driving position corresponding to the second air route according to the first relative time length and the second relative time length corresponding to each boundary driving position.

Specifically, the first travel position shown in fig. 4 is a1, and the collision position range is a2 to S2. First, two boundary driving positions, a2 and S2, located at a2 through S2 are determined. Then, according to the position of the a1 and the driving time length corresponding to the first route, a first relative time length for the unmanned aerial vehicle to drive from the starting driving position Start1 of the first route to a1, that is, the flight time (which may be represented as time _ a 1) required for the unmanned aerial vehicle to drive to a1 is determined. For example, the driving time corresponding to the first route is 25min, the position of a1 is 10% of the first route, and then time _ a1=2.5 min. And determining a second relative time length from the starting driving position Start2 to a2 of the unmanned aerial vehicle on the second airline, namely the flight time (denoted as time _ a 2) required by the unmanned aerial vehicle to drive to a2, and a second relative time length from the starting driving position Start2 to S2 of the unmanned aerial vehicle on the second airline, namely the flight time (denoted as time _ S2) required by the unmanned aerial vehicle to drive to S2 according to the positions of a2 and S2 and the driving time length corresponding to the second airline. For example, if the second route corresponds to a travel time of 30min, the position of a2 is located at 90% of the second route, and the position of S2 is located at 85% of the second route, then time _ a2=27min, and time _ S2=25.5 min.

Finally, the conflict time period of the first driving position corresponding to the second air route can be determined according to the first relative duration and the second relative duration corresponding to each boundary driving position. For example, time _ a1=2.5min, time _ a2=27min, time _ S2=25.5min, it is determined that a1 corresponds to the conflict time period for the second lane. Then, the difference between time _ a1 and time _ a2, i.e., 2.5min-27min = -24.5min, may be used as one boundary of the collision time period for a1 corresponding to the second lane, and the difference between time _ a1 and time _ S2, i.e., 2.5min-25.5min = -23min, may be used as the other boundary of the collision time period for a1 corresponding to the second lane, and then the collision time period for a1 corresponding to the second lane may be found to be-24.5 min to-23 min.

In one implementation, the implementation manner of the step 4) may be:

For example, the start time of the conflict period for the second lane at the first travel position may be min (time _ A1-time _ A2, time _ A1-time _ S2), and the end time may be max (time _ A1-time _ A2, time _ A1-time _ S2). In another implementation, the starting time of the conflict time period for the second route for the first travel position may be min (time _ a1-time _ a2, time _ a1-time _ S2) -duration, and the ending time may be max (time _ a1-time _ a2, time _ a1-time _ S2) } + duration, where the duration may be a preset redundant duration, such as 1 min.

In another implementation manner, the implementation manner of the step 4) may include:

first, a starting boundary travel position and an ending boundary travel position are determined among the two boundary travel positions, and a difference between a first relative duration and a second relative duration corresponding to the starting boundary travel position is smaller than a difference between the first relative duration and the second relative duration corresponding to the ending boundary travel position.

And then, subtracting the redundant time length from the difference between the first relative time length and the second relative time length corresponding to the initial boundary driving position to obtain the initial time of the conflict time period of the second air route corresponding to the first driving position.

And finally, adding the redundant time length to the difference between the first relative time length and the second relative time length corresponding to the end boundary driving position to obtain the end time of the conflict time period of the second air route corresponding to the first driving position.

In an example, of the two boundary driving positions, the starting boundary driving position is close to the starting driving position of the second route, and the ending boundary driving position is far away from the starting driving position of the second route, that is, the unmanned aerial vehicle drives according to the second route, and passes through the starting boundary driving position first and then passes through the ending boundary driving position. Taking the first travel position shown in fig. 4 as a1 and the range of collision positions as a2 to S2 for example, then the starting boundary travel position is S2 and the ending boundary travel position is a2, then time _ a1-time _ S2-duration may be taken as the starting time of the collision session for the second airline for the first travel position and time _ a1-time _ a2+ duration as the ending time of the collision session for the second airline for the first travel position.

In another application scenario, the target constraints further include: the difference between the takeoff time of the first unmanned aerial vehicle and the takeoff time of the third unmanned aerial vehicle belongs to a time range outside a conflict time range corresponding to the flight path planned for the first unmanned aerial vehicle and the flight path planned for the third unmanned aerial vehicle, and the third unmanned aerial vehicle is an unmanned aerial vehicle allocated with the takeoff time.

For example, the drone control center may have allocated departure times for other drones before allocating departure times for multiple drones, i.e., there are one or more drones that have allocated departure times. Therefore, when the takeoff time is allocated to a plurality of drones, it is necessary to further consider the drone to which the takeoff time has been allocated. Taking any third drone assigned a departure time as an example, the target constraints may further include: the difference between the departure time of the first drone and the departure time of the third drone belongs to a time range outside the conflict time range corresponding to the flight path planned for the first drone and the flight path planned for the third drone, this constraint may be denoted as constraint — 3. Taking the Takeoff time of the first unmanned aerial vehicle as Takeoff _ time _1, the Takeoff time of the third unmanned aerial vehicle as Fi _ Takeoff _ time _3 as an example, the route ID of the route planned for the first unmanned aerial vehicle is i, and the route ID of the route planned for the third unmanned aerial vehicle is j, then constraint _3 may be: takeoff _ time _ 1-Fi _ Takeoff _ time _3 belongs to a time range outside ConflictTime _ i _ j _ list.

In yet another application scenario, the target constraint further comprises: and if the takeoff priority of the first unmanned aerial vehicle is higher than that of the second unmanned aerial vehicle, the takeoff time of the first unmanned aerial vehicle is before that of the second unmanned aerial vehicle. And/or the presence of a gas in the gas,

For example, corresponding takeoff priorities may be set for a plurality of drones in advance, and accordingly, the following limits may be added to the target constraints: if the takeoff priority of the first drone is higher than the takeoff priority of the second drone, the takeoff time of the first drone is before the takeoff time of the second drone, the constraint may be denoted as constraint _ 4. Taking the Takeoff time of the first drone as Takeoff _ time _1 and the Takeoff time of the second drone as Takeoff _ time _2 as examples, then constraint _4 may be: takeoff _ time _1< Takeoff _ time _ 2. Specifically, the takeoff priority may be determined according to the urgency of the task executed by the corresponding unmanned aerial vehicle, may also be determined according to the remaining power of the corresponding unmanned aerial vehicle, and may also be determined according to the priority of the planned route for the corresponding unmanned aerial vehicle, which is not specifically limited by the present disclosure.

Further, a specified time may be set for each drone to limit the takeoff time of the drone to be before the corresponding specified time, and the constraint may be denoted as constraint _ 5. With the Takeoff time of the first drone being denoted as Takeoff _ time _1 and the specified time of the first drone being denoted as Max _ Takeoff _ time, then constraint _5 may be: takeoff _ time _1 is less than or equal to Max _ Takeoff _ time. Specifically, the designated time can be manually designated according to specific requirements, for example, a forced takeoff time can be set for the unmanned aerial vehicle as the designated time. The designated time may also be determined from flight constraint parameters of the drone, the flight constraint parameters being capable of characterizing the flight capabilities of the drone, the flight constraint parameters may include, for example, at least one of: the residual electric quantity, the running time corresponding to the planned route and the forced takeoff time. For example, the remaining duration that the remaining capacity can support the unmanned aerial vehicle to travel can be determined according to the remaining capacity of the unmanned aerial vehicle, then the duration that the unmanned aerial vehicle can wait can be determined according to the travel duration corresponding to the planned air route for the unmanned aerial vehicle, and finally the specified time can be determined according to the duration that the unmanned aerial vehicle can wait. For example, the remaining time length that the remaining electric quantity of the unmanned aerial vehicle can support the unmanned aerial vehicle to travel is 50min, the travel time length corresponding to the planned route of the unmanned aerial vehicle is 30min, that is, the unmanned aerial vehicle needs to finish traveling on the corresponding route, and the remaining electric quantity of 3/5 needs to be used, so the time length that the remaining electric quantity of 2/5 can maintain the standby state of the unmanned aerial vehicle can be determined according to the power consumption of the standby state of the unmanned aerial vehicle, for example, the time length that the standby state of the unmanned aerial vehicle can be maintained is 30min, so the current time can be delayed backwards for 30min to obtain the specified time. That is, the drone needs to take off before consuming the remaining 2/5 of power to ensure that the drone can finish traveling on the respective flight line.

Fig. 5 is a block diagram illustrating an obstacle avoidance control apparatus of a drone according to an exemplary embodiment, and as shown in fig. 5, the apparatus 200 may include:

the receiving module 201 is configured to receive route information of a plurality of unmanned aerial vehicles through an unmanned aerial vehicle control center, where the route information includes a plurality of driving positions on a route planned for the unmanned aerial vehicle and a planning speed corresponding to a route segment between the driving positions.

The determining module 202 is configured to determine, by the unmanned aerial vehicle control center, collision time information corresponding to a planned route of each unmanned aerial vehicle according to the route information of each unmanned aerial vehicle and a preset obstacle avoidance distance, where the collision time information includes: and the conflict time range corresponding to the planned route for the unmanned plane and the planned route for each unmanned plane.

An adjusting module 203 for adjusting the flight parameters of each unmanned aerial vehicle through the unmanned aerial vehicle control center according to the conflict time information corresponding to the planned air route for each unmanned aerial vehicle and the preset target constraint condition, wherein the flight parameters include: the departure time and/or the planned speed corresponding to the route section between the driving positions on the route planned for the unmanned aerial vehicle.

And the sending module 204 is used for sending the adjusted flight parameters of the unmanned aerial vehicle to each unmanned aerial vehicle through the unmanned aerial vehicle control center.

And the control module 205 is configured to fly by the unmanned aerial vehicle according to the adjusted corresponding flight parameters.

Fig. 6 is a block diagram illustrating another obstacle avoidance control apparatus for a drone according to an exemplary embodiment, and as shown in fig. 6, the adjusting module 203 may include:

the first determining submodule 2031 is configured to determine, according to the conflict time information corresponding to the planned route for each drone, a target constraint condition, where the target constraint condition includes: the difference between the takeoff time of the first drone and the takeoff time of the second drone belongs to a time range outside the conflict time range corresponding to the flight path planned for the first drone and the flight path planned for the second drone. The first unmanned aerial vehicle is any unmanned aerial vehicle, and the second unmanned aerial vehicle is any unmanned aerial vehicle except the first unmanned aerial vehicle.

And an adjusting submodule 2032, configured to adjust a takeoff time of each drone according to the target constraint condition.

In an application scenario, the adjusting sub-module 2032 may be configured to:

Specifically, the objective function is the product of the takeoff time of each drone and the weight corresponding to the drone, and the weight corresponding to the drone is determined according to the takeoff priority of the drone and/or the priority of the planned route for the drone.

Fig. 7 is a block diagram illustrating another obstacle avoidance control apparatus for a drone according to an exemplary embodiment, where as shown in fig. 7, the determining module 202 may include:

the second determining submodule 2021 is configured to determine that the first driving position on the first route corresponds to a collision position range on the second route, and a distance between any driving position in the collision position range and the first driving position is smaller than or equal to the obstacle avoidance distance. The first air route and the second air route are air routes planned for any unmanned aerial vehicle, and the first driving position is any driving position on the first air route.

The third determining submodule 2022 is configured to determine, according to the collision position range of the first driving position corresponding to the second airline, the driving duration corresponding to the first airline, and the driving duration corresponding to the second airline, a collision time period of the first driving position corresponding to the second airline.

The merging submodule 2023 is configured to merge the conflict time periods of the second airline corresponding to each driving position on the first airline to obtain a conflict time range corresponding to the first airline and the second airline, where the conflict time range is used to represent an interval between the takeoff time of the unmanned aerial vehicle allocated on the first airline and the takeoff time of the unmanned aerial vehicle allocated on the second airline.

In an application scenario, the third determining submodule 2022 may be configured to perform the following steps:

In another application scenario, the third determining sub-module 2022 may be configured to:

In yet another application scenario, the third determining sub-module 2022 may be configured to perform the following steps:

In one application scenario, the target constraints further include: the difference between the takeoff time of the first unmanned aerial vehicle and the takeoff time of the third unmanned aerial vehicle belongs to a time range outside a conflict time range corresponding to the flight path planned for the first unmanned aerial vehicle and the flight path planned for the third unmanned aerial vehicle, and the third unmanned aerial vehicle is an unmanned aerial vehicle allocated with the takeoff time.

In another application scenario, the target constraints further include: and if the takeoff priority of the first unmanned aerial vehicle is higher than that of the second unmanned aerial vehicle, the takeoff time of the first unmanned aerial vehicle is before that of the second unmanned aerial vehicle. And/or the presence of a gas in the gas,

With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.

Fig. 8 is a block diagram illustrating an electronic device 300 in accordance with an example embodiment. For example, the electronic device 300 may be provided as a server. Referring to fig. 8, the electronic device 300 comprises a processor 322, which may be one or more in number, and a memory 332 for storing computer programs executable by the processor 322. The computer program stored in memory 332 may include one or more modules that each correspond to a set of instructions. Further, the processor 322 may be configured to execute the computer program to execute the above-described obstacle avoidance control method for the drone.

Additionally, electronic device 300 may also include a power component 326 and a communication component 350, the power component 326 may be configured to executeFor power management of electronic device 300, the communication component 350 may be configured to enable communication, e.g., wired or wireless communication, of the electronic device 300. In addition, the electronic device 300 may also include input/output (I/O) interfaces 358. The electronic device 300 may operate based on an operating system, such as Windows Server, stored in the memory 332^TM，Mac OS X^TM，Unix^TM，Linux^TMAnd so on.

In another exemplary embodiment, a computer readable storage medium including program instructions is further provided, which when executed by a processor, implement the steps of the above-mentioned obstacle avoidance control method for a drone. For example, the computer readable storage medium may be the memory 332 including program instructions, which are executable by the processor 322 of the electronic device 300 to implement the obstacle avoidance control method of the drone described above.

In another exemplary embodiment, a computer program product is also provided, which contains a computer program executable by a programmable apparatus, the computer program having code portions for performing the above-mentioned obstacle avoidance control method of a drone when executed by the programmable apparatus.

Preferred embodiments of the present disclosure are described in detail above with reference to the accompanying drawings, however, the present disclosure is not limited to the specific details of the above embodiments, and other embodiments of the present disclosure may be easily conceived by those skilled in the art within the technical spirit of the present disclosure after considering the description and practicing the present disclosure, and all fall within the protection scope of the present disclosure.

It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. Meanwhile, any combination can be made between various different embodiments of the disclosure, and the disclosure should be regarded as the disclosure of the disclosure as long as the combination does not depart from the idea of the disclosure. The present disclosure is not limited to the precise structures that have been described above, and the scope of the present disclosure is limited only by the appended claims.

Claims

1. An obstacle avoidance control method for an unmanned aerial vehicle, the method comprising:

the unmanned aerial vehicle control center determines conflict time information corresponding to each unmanned aerial vehicle planned route according to the route information of each unmanned aerial vehicle and a preset obstacle avoidance distance, wherein the conflict time information comprises: a conflict time range corresponding to the planned route for the unmanned aerial vehicle and the planned route for each unmanned aerial vehicle, wherein the conflict time range is used for representing the interval between the takeoff time of the unmanned aerial vehicle and the takeoff time of each unmanned aerial vehicle;

the unmanned aerial vehicle flies according to the adjusted corresponding flight parameters;

the unmanned aerial vehicle control center adjusts each flight parameter of the unmanned aerial vehicle according to the conflict time information corresponding to the planned air route of each unmanned aerial vehicle and the preset target constraint condition, and the method comprises the following steps:

2. The method of claim 1, wherein the objective function is a summation of a product of a takeoff time of each drone and a weight corresponding to the drone, the weight corresponding to the drone being determined according to a takeoff priority of the drone and/or a priority of the route planned for the drone.

3. The method of claim 1, wherein the determining, by the drone control center, collision time information corresponding to a planned route for each drone according to the route information of each drone and a preset obstacle avoidance distance comprises:

4. The method of claim 3, wherein determining the conflict time period for the first travel location corresponding to the second airline based on the range of conflict locations for the first travel location corresponding to the second airline, the travel duration corresponding to the first airline, and the travel duration corresponding to the second airline comprises:

5. The method of claim 4, wherein determining the time period of conflict for the first travel location with respect to the second route based on the first relative time period and the second relative time period for each of the boundary travel locations comprises:

6. The method of claim 5, wherein determining the conflict time period for the second route for the first travel position based on a preset redundant time period, a difference between a second relative time period corresponding to each of the boundary travel positions and the first relative time period comprises:

7. The method of claim 1, wherein the target constraints further comprise: the difference between the takeoff time of the first unmanned aerial vehicle and the takeoff time of the third unmanned aerial vehicle belongs to a time range outside a conflict time range corresponding to the flight path planned for the first unmanned aerial vehicle and the flight path planned for the third unmanned aerial vehicle, and the third unmanned aerial vehicle is an unmanned aerial vehicle allocated with the takeoff time.

8. The method of claim 1, wherein the target constraints further comprise: if the takeoff priority of the first unmanned aerial vehicle is higher than that of the second unmanned aerial vehicle, the takeoff time of the first unmanned aerial vehicle is before that of the second unmanned aerial vehicle; and/or the presence of a gas in the gas,

9. The utility model provides an unmanned aerial vehicle keeps away barrier controlling means which characterized in that, the device includes:

the determining module is used for determining conflict time information corresponding to each unmanned aerial vehicle planned route through the unmanned aerial vehicle control center according to the route information of each unmanned aerial vehicle and a preset obstacle avoidance distance, wherein the conflict time information comprises: a conflict time range corresponding to the planned route for the unmanned aerial vehicle and the planned route for each unmanned aerial vehicle, wherein the conflict time range is used for representing the interval between the takeoff time of the unmanned aerial vehicle and the takeoff time of each unmanned aerial vehicle;

the control module is used for flying by the unmanned aerial vehicle according to the adjusted corresponding flight parameters;

the adjustment module includes:

and the adjusting submodule is used for solving an objective function through a preset optimization algorithm under the condition that the target constraint condition is met so as to obtain the takeoff time of each unmanned aerial vehicle when the objective function is minimum, the variable in the objective function comprises the takeoff time of each unmanned aerial vehicle, and the objective function is positively correlated with the sum of the takeoff time of each unmanned aerial vehicle.

10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 8.

11. An electronic device, comprising:

a memory having a computer program stored thereon;

a processor for executing the computer program in the memory to carry out the steps of the method of any one of claims 1 to 8.