CN112729309A

CN112729309A - Unmanned aerial vehicle logistics path planning method and device

Info

Publication number: CN112729309A
Application number: CN202011554678.6A
Authority: CN
Inventors: 楚西岳; 张宗来; 陈彬
Original assignee: Beijing Lingyu Aviation Technology Research Institute Co ltd
Current assignee: Beijing Lingyu Aviation Technology Research Institute Co ltd
Priority date: 2020-12-24
Filing date: 2020-12-24
Publication date: 2021-04-30

Abstract

The embodiment of the application provides an unmanned aerial vehicle logistics path planning method and equipment, wherein an unmanned aerial vehicle logistics transportation request from a user terminal is received; generating a corresponding initialization key point sequence according to the unmanned aerial vehicle logistics transportation request, and generating a corresponding initialization logistics pipeline based on the initialization key point sequence; determining a temporary logistics pipeline section which does not meet a first preset condition in the initialized logistics pipeline; searching a new logistics pipeline key point according to the temporary logistics pipeline section which does not meet the first preset condition until the new temporary logistics pipeline section generated according to the new logistics pipeline key point meets the preset target condition; taking a new logistics pipeline key point corresponding to a new temporary logistics pipeline section meeting a preset target condition as a target logistics pipeline key point; and updating the initialized logistics pipeline according to the key points of the target logistics pipeline to obtain the corresponding target logistics pipeline.

Description

Unmanned aerial vehicle logistics path planning method and device

Technical Field

The application relates to the technical field of unmanned aerial vehicles, in particular to a method and equipment for planning logistics paths of an unmanned aerial vehicle.

Background

Along with the rapid development of unmanned aerial vehicle technology in recent years, unmanned aerial vehicles are widely applied to various industries. And along with the development of the logistics transportation industry, the unmanned aerial vehicle plays an increasingly important role in the logistics transportation industry. The unmanned aerial vehicle can replace the traditional ground transportation in the middle and short distance logistics transportation, especially under the condition that the ground transportation environment is relatively complex, so that the logistics transportation efficiency is improved; in long-distance logistics transportation, unmanned aerial vehicle can replace the transportation that has the man-machine, reduces logistics transportation cost.

The existing unmanned aerial vehicle path planning technology usually adopts a visual sensor to perform real-time adjustment in the flight process of the unmanned aerial vehicle. For unmanned aerial vehicles used in the logistics industry, there are usually relatively well-defined starting and ending points before flight. And, along with the development of unmanned aerial vehicle technique and commodity circulation transportation trade, will have more and more unmanned aerial vehicle to drop into the commodity circulation trade, only rely on prior art to carry out real-time adjustment to flight logistics pipeline in the unmanned aerial vehicle use, no longer can satisfy unmanned aerial vehicle's demand, can cause unmanned aerial vehicle to bump in the use, installation hidden danger such as mutual interference between the unmanned aerial vehicle. Moreover, the cost of the unmanned aerial vehicle adopting the vision sensor is high, and the unmanned aerial vehicle is not suitable for being greatly invested in the logistics industry.

Based on this, how to provide a technical scheme that is high in safety and suitable for the flight path planning of the logistics unmanned aerial vehicle becomes a technical problem that needs to be solved urgently.

Disclosure of Invention

The embodiment of the application provides an unmanned aerial vehicle logistics path planning method, and solves the problems that the existing unmanned aerial vehicle path planning technology is not suitable for the unmanned aerial vehicle logistics transportation industry and is low in safety.

In one aspect, an embodiment of the present application provides an unmanned aerial vehicle logistics path planning method, which includes: receiving an unmanned aerial vehicle logistics transportation request from a user terminal; generating a corresponding initialization key point sequence according to the unmanned aerial vehicle logistics transportation request, and generating a corresponding initialization logistics pipeline based on the initialization key point sequence; the initialization key point sequence consists of key points of a logistics pipeline, and the key points of the logistics pipeline are used for representing passing points of the unmanned aerial vehicle flying; determining a temporary logistics pipeline section which does not meet a first preset condition in the initialized logistics pipeline; searching a new logistics pipeline key point according to the temporary logistics pipeline section which does not meet the first preset condition until the new temporary logistics pipeline section generated according to the new logistics pipeline key point meets the preset target condition; taking a new logistics pipeline key point corresponding to a new temporary logistics pipeline section meeting a preset target condition as a target logistics pipeline key point; and updating the initialized logistics pipeline according to the key points of the target logistics pipeline to obtain the corresponding target logistics pipeline.

Through the scheme, the server receives the unmanned aerial vehicle logistics transportation request from the user terminal, and generates the initialization key point sequence and the initialization logistics pipeline based on the unmanned aerial vehicle logistics transportation request. When the initialized logistics pipeline does not meet the preset conditions, the initialized logistics pipeline is adjusted until the adjusted logistics pipeline meets all the preset conditions, so that a path suitable for the logistics unmanned aerial vehicle is determined. By the method, a logistics transportation pipeline is provided for the unmanned aerial vehicle for logistics transportation operation, the safety of the unmanned aerial vehicle and goods in the flight process is guaranteed, the logistics transportation efficiency is greatly improved, and the logistics transportation time is shortened.

In one possible implementation mode, an initialization key point sequence is generated according to a cargo start-up point, a cargo delivery point and pre-acquired unmanned aerial vehicle flight guarantee information in the unmanned aerial vehicle logistics transportation request; the key points of the logistics pipeline comprise a cargo start-up point, a cargo delivery point and an unmanned aerial vehicle flight guarantee point; generating corresponding temporary logistics pipeline sections according to two adjacent logistics pipeline key points in the initialization key point sequence and the pre-acquired flight performance information of the unmanned aerial vehicle; and combining the temporary logistics pipeline sections according to corresponding preset rules to form an initialized logistics pipeline.

In one possible implementation, the preset target condition at least includes: a first preset condition, a second preset condition and a third preset condition; according to the temporary logistics pipeline section which does not satisfy the first preset condition, searching for a new logistics pipeline key point until the temporary logistics pipeline section which is generated according to the new logistics pipeline key point satisfies the preset target condition, and the method specifically comprises the following steps: searching a new logistics pipeline key point according to the temporary logistics pipeline section which does not meet the first preset condition until the temporary logistics pipeline section generated according to the new logistics pipeline key point meets the first preset condition to generate a first temporary logistics pipeline; according to the temporary logistics pipeline section which does not meet the second preset condition in the first temporary logistics pipeline, searching a new logistics pipeline key point again until the temporary logistics pipeline section generated according to the new logistics pipeline key point meets the first preset condition and the second preset condition so as to generate a second temporary logistics pipeline; and searching a new key point of the logistics pipeline according to the second temporary logistics pipeline which does not meet the third preset condition until the temporary logistics pipeline section generated according to the new key point of the logistics pipeline meets the preset target condition so as to generate a third temporary logistics pipeline.

According to the scheme provided by the embodiment of the application, the initialized logistics pipeline is updated to the first temporary logistics pipeline under the condition that the initialized logistics pipeline meets the first preset condition; updating the first material flow pipeline to be a second material flow pipeline under the condition that the first material flow pipeline meets a first preset condition and a second preset condition; under the condition that the second physical flow pipeline meets the first preset condition and the second preset condition, updating the second physical flow pipeline into a third physical flow pipeline; and under the condition that the third logistics pipeline simultaneously meets the first preset condition, the second preset condition and the third preset condition, updating the third logistics pipeline into a fourth logistics pipeline, wherein the fourth logistics pipeline is the target logistics pipeline. This application is optimized initialization logistics pipeline with three condition of predetermineeing to can generate the logistics pipeline that is more suitable for logistics unmanned aerial vehicle to use.

In one possible implementation manner, the first preset condition, the second preset condition, and the third preset condition are any one of the following items: target obstacles do not exist in the temporary logistics pipeline section; the airspace where the temporary logistics pipeline section is located is not a no-fly airspace; matching the temporary logistics pipeline section with unmanned aerial vehicle performance information corresponding to the unmanned aerial vehicle logistics transportation request; the first preset condition, the second preset condition and the third preset condition are different from each other.

The scheme that this application embodiment provided, with barrier, no-fly airspace and with the matching of unmanned aerial vehicle performance information as presetting the condition, combine commodity circulation unmanned aerial vehicle operational environment more to can provide the commodity circulation pipeline that more agrees with commodity circulation unmanned aerial vehicle's reality operational environment.

In a possible implementation manner, when the first preset condition is that the temporary logistics pipeline segment is matched with performance information in the unmanned aerial vehicle logistics transportation request, the temporary logistics pipeline segment which does not meet the first preset condition is determined, and the method specifically includes: determining the performance information of the unmanned aerial vehicle according to the unmanned aerial vehicle transportation request; wherein the performance information includes: the minimum turning radius of the unmanned aerial vehicle and the maximum climbing gradient of the unmanned aerial vehicle are determined; determining the turning radius and climbing gradient at the key point of the logistics pipeline according to the position information of the key point of the logistics pipeline; under the condition that at most one preset condition is met, the temporary material flow pipeline section corresponding to the material flow pipeline key point is a temporary material flow pipeline section which does not meet the first preset condition; the preset conditions are as follows: the first difference is greater than the corresponding preset threshold, and the second difference is less than the corresponding preset threshold. The first difference value is the difference value between the turning radius of the key point of the logistics pipeline and the minimum turning radius of the unmanned aerial vehicle; the second difference is the difference between the climbing gradient of the key point of the logistics pipeline and the maximum climbing gradient of the unmanned aerial vehicle.

In a possible implementation manner, when the first preset condition is that no target obstacle exists in the temporary logistics pipeline segment, according to the initialized temporary logistics pipeline segment that does not satisfy the first preset condition, a new logistics pipeline key point is searched until the temporary logistics pipeline segment generated according to the new logistics pipeline key point satisfies the first preset condition, so as to generate the first temporary logistics pipeline, specifically including: determining the lowest safe flying height of the unmanned aerial vehicle of the logistics pipeline section to be adjusted based on the height value of the highest point of the target obstacle in the logistics pipeline section to be adjusted; wherein, the temporary material flow pipeline section which does not meet the first preset condition is used as the material flow pipeline section to be adjusted; under the condition that the minimum safe flying height of the unmanned aerial vehicle is smaller than the maximum flying height of the unmanned aerial vehicle, calculating the difference value between the maximum flying height of the unmanned aerial vehicle and the minimum safe flying height of the unmanned aerial vehicle, and taking the difference value between the maximum flying height of the unmanned aerial vehicle and the minimum safe flying height of the unmanned aerial vehicle as a third difference value; determining a new logistics pipeline key point under the condition that the third difference value is larger than the corresponding set threshold value, and updating the logistics pipeline to be adjusted by taking the lowest safe flight height of the unmanned aerial vehicle as the bottom height of the logistics pipeline to be adjusted so as to generate a corresponding first temporary logistics pipeline; and under the condition that the third difference value is smaller than the corresponding preset threshold value, determining a space range with the vertex of the target obstacle as an origin, and determining a new key point of the logistics pipeline in the space range until the temporary logistics pipeline section generated according to the new key point of the logistics pipeline meets a first preset condition so as to generate a corresponding first temporary logistics pipeline.

In a possible implementation manner, when the first preset condition is that the airspace in which the temporary logistics pipeline section is located is not a no-fly airspace, determining the temporary logistics pipeline section which does not meet the first preset condition in the initialized logistics pipeline, specifically including: determining the flight time period of the unmanned aerial vehicle according to the unmanned aerial vehicle transportation request; acquiring airspace information in a flight time period, and determining whether the airspace in which each temporary logistics pipeline section is located is a no-flight airspace according to the airspace information; and determining the temporary logistics pipeline section of which the airspace is the no-fly airspace as the temporary logistics pipeline section which does not meet the second preset condition.

In one possible implementation, the method further includes: acquiring current position information of the unmanned aerial vehicle in real time; determining the distance between the current position of the unmanned aerial vehicle and the next target logistics pipeline section; wherein the target material flow pipeline consists of target material flow pipeline sections; when the distance between the current position of the unmanned aerial vehicle and the next target logistics pipeline section is smaller than the preset distance, determining the current airspace information of the airspace in which the next target logistics pipeline section is located; determining whether the next target logistics pipeline section is a temporary flight-forbidden airspace according to the current airspace information of the airspace in which the next target logistics pipeline section is located; and under the condition that the airspace where the next target logistics pipeline section is located is a temporary flight-forbidden airspace, searching for a new logistics pipeline key point so that the new target logistics pipeline section generated according to the new key point meets a preset target condition.

In one possible implementation, the method further includes: determining the first unmanned aerial vehicle number capable of being accommodated by the target logistics pipeline according to the fourth difference and the unmanned aerial vehicle flight performance information corresponding to the unmanned aerial vehicle logistics transportation request; wherein the fourth difference is the minimum vertical distance of the target material flow pipeline; determining the number of unmanned aerial vehicles with the same cargo departure point and the same cargo arrival point in the same time period as the number of second unmanned aerial vehicles according to the logistics transportation request of the unmanned aerial vehicles; and under the condition that the number of the second unmanned aerial vehicles is smaller than that of the first unmanned aerial vehicles, layering each target logistics pipeline segment along the flight direction of the unmanned aerial vehicles according to a preset rule to obtain corresponding sub-target logistics pipelines.

The scheme provided by the embodiment of the application not only considers the expectable optimization condition, but also optimizes the temporary condition, thereby providing a logistics pipeline with stronger practicability.

On the other hand, this application embodiment still provides an unmanned aerial vehicle path planning equipment, and this equipment includes: the system includes at least one processor, and a memory communicatively coupled to the at least one processor. Wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to: receiving an unmanned aerial vehicle logistics transportation request from a user terminal; generating a corresponding initialization key point sequence according to the unmanned aerial vehicle logistics transportation request, and generating a corresponding initialization logistics pipeline based on the initialization key point sequence; the initialization key point sequence consists of key points of a logistics pipeline, and the key points of the logistics pipeline are used for representing passing points of the unmanned aerial vehicle flying; determining a temporary logistics pipeline section which does not meet a first preset condition in the initialized logistics pipeline; searching a new logistics pipeline key point according to the temporary logistics pipeline section which does not meet the first preset condition until the new temporary logistics pipeline section generated according to the new logistics pipeline key point meets the preset target condition; taking a new logistics pipeline key point corresponding to a new temporary logistics pipeline section meeting a preset target condition as a target logistics pipeline key point; and updating the initialized logistics pipeline according to the key points of the target logistics pipeline to obtain the corresponding target logistics pipeline.

The embodiment of the application provides an unmanned aerial vehicle logistics path planning method and equipment. When the initialized logistics pipeline does not meet the preset conditions, the initialized logistics pipeline is adjusted until the adjusted logistics pipeline meets all the preset conditions, so that a path suitable for the logistics unmanned aerial vehicle is determined. By the method, a logistics transportation pipeline is provided for the unmanned aerial vehicle for logistics transportation operation, the safety of the unmanned aerial vehicle and goods in the flight process is guaranteed, the logistics transportation efficiency is greatly improved, and the logistics transportation time is shortened.

Drawings

The accompanying drawings, which are included to provide a further understanding of the specification and are incorporated in and constitute a part of this specification, illustrate embodiments of the specification and together with the description serve to explain the specification and not to limit the specification in a non-limiting sense. In the drawings:

fig. 1 is a schematic flow chart of an unmanned aerial vehicle logistics path planning method according to an embodiment of the present application;

fig. 2 is a schematic flow chart of an unmanned aerial vehicle logistics path planning method according to an embodiment of the present application;

fig. 3 is a schematic flow chart of a method for planning a logistics path of an unmanned aerial vehicle according to an embodiment of the present application;

fig. 4 is a schematic structural diagram of an intermediate section in the unmanned aerial vehicle logistics path planning method provided in the embodiment of the present application;

fig. 5 is a schematic flow chart of an unmanned aerial vehicle logistics path planning method according to an embodiment of the present application;

fig. 6 is a schematic flow chart of an unmanned aerial vehicle logistics path planning method according to an embodiment of the present application;

fig. 7 is a schematic flow chart of an unmanned aerial vehicle logistics path planning method according to an embodiment of the present application;

fig. 8 is a schematic flow chart of an unmanned aerial vehicle logistics path planning method according to an embodiment of the present application;

fig. 9 is a schematic flow chart of an unmanned aerial vehicle logistics path planning method according to an embodiment of the present application;

fig. 10 is a schematic flow chart of an unmanned aerial vehicle logistics path planning method according to an embodiment of the present application;

fig. 11 is a schematic flow chart of an unmanned aerial vehicle logistics path planning method according to an embodiment of the present application;

fig. 12 is a schematic structural diagram of an unmanned aerial vehicle logistics path planning apparatus according to an embodiment of the present application.

Detailed Description

For a better understanding of the above objects, aspects and advantages of the present application, reference will now be made to the following detailed description of embodiments of the present application, which is to be read in connection with the accompanying drawings. It is to be understood that the described embodiments are merely a few embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without any inventive step, are within the scope of the present invention.

The embodiment of the application provides a method for planning logistics paths of an unmanned aerial vehicle, and as shown in fig. 1, the method comprises the following steps:

s101, the server receives an unmanned aerial vehicle logistics transportation request from a user terminal.

The unmanned aerial vehicle logistics transportation request is used for indicating the server to carry out corresponding unmanned aerial vehicle logistics path planning. The unmanned aerial vehicle logistics transportation request at least comprises the following steps: a freight shipment starting point and a freight delivery point.

Besides the cargo departure point and the cargo delivery point, the unmanned aerial vehicle logistics transportation request can further include: unmanned aerial vehicle identification. That is, the user can specify the drone for this logistics transportation through the user terminal. At this moment, the server can determine the unmanned aerial vehicle corresponding to the unmanned aerial vehicle identity through the unmanned aerial vehicle identity in the unmanned aerial vehicle logistics transportation request, and the unmanned aerial vehicle is used as the unmanned aerial vehicle appointed by the user for the logistics transportation operation.

It should be noted that, one drone logistics transportation request may include at least one drone identity, that is, the drone logistics transportation request may correspond to at least one drone.

In addition, in this application embodiment, the server can also confirm whether the unmanned aerial vehicle that above-mentioned unmanned aerial vehicle identification corresponds accords with relevant requirement. For example, the unmanned aerial vehicle identity in the unmanned aerial vehicle logistics transportation request corresponds to an unmanned aerial vehicle a, the server can determine whether the unmanned aerial vehicle a has logistics transportation qualification according to pre-stored related information of the unmanned aerial vehicle a, and under the condition that the unmanned aerial vehicle a has the logistics transportation qualification, the server determines that the unmanned aerial vehicle a executes the logistics transportation task; under the condition that the unmanned aerial vehicle A does not have logistics transportation qualification, the server determines that the unmanned aerial vehicle A cannot execute the logistics transportation operation, and the server can distribute the unmanned aerial vehicle with the logistics transportation qualification for the unmanned aerial vehicle according to the logistics transportation request of the unmanned aerial vehicle.

Furthermore, in the in-service use process, the user may not specify the unmanned aerial vehicle to carry out the logistics transportation operation, that is, there is no unmanned aerial vehicle identification in the unmanned aerial vehicle logistics transportation request. At this time, the server may allocate the drone for the logistics transportation operation according to the drone logistics transportation request, as shown in fig. 2, and may be implemented as follows:

s201, the server can acquire the current working state of each unmanned aerial vehicle in real time.

Wherein, unmanned aerial vehicle's current operating condition can include idle state, operating condition, reservation state. The operating state may mean that the drone is in flight, is working. The reservation status may mean that the drone has been reserved and is not yet in use. The idle state may mean that the drone is neither flying nor reserved, and may be available for use.

S202, the server takes the unmanned aerial vehicle with the current working state being the idle state as the unmanned aerial vehicle to be determined, and acquires the position information of each unmanned aerial vehicle to be determined.

S203, the server can calculate the distance value between each to-be-determined unmanned aerial vehicle and the cargo starting point according to the cargo starting point in the unmanned aerial vehicle logistics transportation request and the position information of each to-be-determined unmanned aerial vehicle.

And S204, the server determines the number of target unmanned aerial vehicles corresponding to the unmanned aerial vehicle logistics transportation request according to the cargo information in the unmanned aerial vehicle logistics transportation request.

Above-mentioned target unmanned aerial vehicle quantity can be the required unmanned aerial vehicle quantity of goods information in satisfying unmanned aerial vehicle logistics transportation request, is the required unmanned aerial vehicle's of this time logistics transportation operation quantity promptly.

In this application embodiment, the unmanned aerial vehicle logistics transportation request may further include cargo information. The cargo information is used for representing the relevant information of the cargo transported by the logistics, and may at least comprise one of the following items: cargo weight, cargo volume, and cargo quantity.

For example, if the cargo transported by logistics is rice, the weight of the rice is 21kg, and the weight of the cargo transported by each unmanned aerial vehicle is 3kg, then 7 unmanned aerial vehicles are required for the logistics transportation. If the logistics transportation is express delivery parcel, totally 5, every unmanned aerial vehicle can transport a parcel, then this logistics transportation needs 5 unmanned aerial vehicles. For another example, the cargo information of a certain logistics transportation operation is 20 pieces of clothes, each piece of clothes needs one unmanned aerial vehicle for transportation, and the number of the unmanned aerial vehicles in the logistics transportation operation is 20.

It should be noted that the above only exists as an example, and as the performance of the drones may be different (for example, the weight of the cargo carried by the drone a is 3kg, and the weight of the cargo carried by the drone B is 4kg), the number of the drones required may be calculated according to the performance of the drone and the cargo information, and may be adjusted according to the actual situation, which is not described herein again.

In addition, because unmanned aerial vehicle needs corresponding power source, consequently, in order to realize the unmanned aerial vehicle distribution better, combine above-mentioned scheme, the server can also be according to the transportation distance of this commodity circulation transportation operation, unmanned aerial vehicle flight performance information and goods information distribution unmanned aerial vehicle again, as the unmanned aerial vehicle of this commodity circulation transportation.

The flight performance information mentioned here may include the current flyable range, maximum load of the drone.

For example, above-mentioned logistics transportation operation that needs 3 unmanned aerial vehicle transportation 6 kilograms of rice, the distance between goods departure point and the goods arrival point is 28 kilometers. The existing four unmanned aerial vehicles a, b, c and d have the current flight range of 30 kilometers, the maximum load of 3kg and the current working state of being reserved; the current flight range of the unmanned aerial vehicle b is 20 kilometers, the maximum load is 2kg, and the current state is idle; the current flight distance of the unmanned aerial vehicle c is 22 kilometers, the maximum load is 3kg, and the current working state is in work; the current flight distance of the unmanned aerial vehicle d is 30 kilometers, the maximum load is 3kg, and the current working state is idle. The server can confirm according to unmanned aerial vehicle a, b, c, d's state information, unmanned aerial vehicle b and d that are in idle state all can be used to this commodity circulation transportation operation, on this basis, the server confirms unmanned aerial vehicle b and unmanned aerial vehicle d apart from the distance of goods starting point, for example, unmanned aerial vehicle b apart from the goods starting point 2.5 kilometers, unmanned aerial vehicle d apart from the goods starting point 5 kilometers, this moment, the server confirms that unmanned aerial vehicle b is used for this commodity circulation transportation operation.

The user terminal may be a mobile terminal such as a mobile phone or a tablet computer, or may be other terminal equipment.

In some embodiments of the Application, the user terminal may install corresponding Application software (APP), and perform data transmission with the server through the installed APP, so as to send the unmanned aerial vehicle logistics transportation request to the server. The mode that the user passes through user terminal's APP input unmanned aerial vehicle logistics transportation request can be for speech input, picture discernment input.

It should be noted that, the steps S204 and S201 may be executed simultaneously, or the step S201 may be executed first, and then the step S204 is executed; or, step S204 is executed first, and then step S201 is executed, and the specific execution sequence is not limited in the embodiment of the present application.

S205, the server determines corresponding target unmanned aerial vehicles according to the number of the target unmanned aerial vehicles and the position information of the unmanned aerial vehicles to be determined.

The target unmanned aerial vehicle is the unmanned aerial vehicle for executing work in the logistics transportation operation.

Corresponding unmanned aerial vehicles can be allocated to the unmanned aerial vehicle logistics transportation request through the steps S201-S205.

And S102, the server generates a corresponding initialization key point sequence according to the unmanned aerial vehicle logistics transportation request.

The initialization key point sequence is composed of logistics pipeline key points, and the logistics pipeline key points are used for representing passing points of unmanned aerial vehicle flying.

The stream pipeline key points can comprise: unmanned aerial vehicle departure point, unmanned aerial vehicle landing point, flight guarantee point.

As can be seen from the above, the unmanned aerial vehicle logistics transportation request includes: a goods starting point and a goods delivery point. In this application embodiment, unmanned aerial vehicle departure point can be confirmed according to goods departure point, and unmanned aerial vehicle landing point can be confirmed according to goods arrival point. It should be noted that, in an actual application scenario, the cargo departure point, the unmanned aerial vehicle departure point, the cargo delivery point, and the unmanned aerial vehicle landing point may be the same location or different locations.

Specifically, as shown in fig. 3, determining a departure point of the unmanned aerial vehicle according to the cargo departure point and determining a landing point of the unmanned aerial vehicle according to the cargo delivery point can be implemented by the following method:

s301, the server matches the cargo start-up point and the cargo delivery point with a pre-stored unmanned aerial vehicle take-off and landing field set.

The unmanned aerial vehicle take-off and landing field set refers to a set formed by position information of all unmanned aerial vehicle take-off and landing fields in a preset range. For example, the preset range has unmanned aerial vehicle take-off and landing fields 1, 2, 3, 4, and then the position information combination of the unmanned aerial vehicle take-off and landing fields is composed of the position information of the unmanned aerial vehicle take-off and landing fields 1, 2, 3, 4.

Specifically, the position information of the cargo departure point and the position information of the cargo delivery point may be acquired in advance. And determining whether the unmanned aerial vehicle take-off and landing field set has a matched unmanned aerial vehicle take-off and landing field or not according to the position information of the cargo start-up and transportation point, if so, indicating that the cargo start-up and transportation point is matched with the unmanned aerial vehicle take-off and landing field set, and otherwise, indicating that the cargo start-up and transportation point is not matched. And determining whether the unmanned aerial vehicle taking-off and landing field set has a matched unmanned aerial vehicle taking-off and landing field or not according to the position information of the goods arrival point, if so, indicating that the goods arrival point is matched with the unmanned aerial vehicle taking-off and landing field set, and otherwise, indicating that the goods arrival point is not matched.

It should be noted that, the position information of the unmanned aerial vehicle take-off and landing site in the unmanned aerial vehicle take-off and landing site set is matched with the position information of the cargo start-up point, that is, the cargo start-up point is the unmanned aerial vehicle take-off and landing site. Similarly, the goods delivery point is the same as the goods departure point.

S302, under the condition that the position information of the goods departure point and the goods arrival point is matched with the position information set of the unmanned aerial vehicle departure and landing field, the unmanned aerial vehicle departure and landing field corresponding to the goods departure point is used as an unmanned aerial vehicle departure and landing point, and the unmanned aerial vehicle departure and landing field corresponding to the goods arrival point is used as an unmanned aerial vehicle landing point.

And S303, under the condition that the position information of the cargo start-up point and the cargo delivery point is not matched with the unmanned aerial vehicle take-off and landing field set, selecting the corresponding unmanned aerial vehicle take-off and landing field according to a preset rule.

For example, when purchasing on the internet, the user is usually used to fill in the receiving address as the detailed home address of the user, but in the process of logistics transportation, the goods are usually sent to the transfer points such as the goods warehouse or the vegetable and bird post station in the city where the home address of the user is located, and at this time, the delivery point of the goods and the landing point of the unmanned aerial vehicle are different points. That is, the location information of the cargo delivery point does not match the set of unmanned aerial vehicle take-off and landing sites.

In this application specification, after the server received the unmanned aerial vehicle logistics transportation request that user terminal sent, at first do the matching with the unmanned aerial vehicle set of taking off and landing place that prestores in the server with the positional information of goods departure point, when the positional information of goods departure point matches with the unmanned aerial vehicle set of taking off and landing place that prestores in the server, the server judges that goods departure point is the same with the unmanned aerial vehicle set of taking off and landing place in the unmanned aerial vehicle set of taking off and landing place, otherwise, the server judges that goods departure point is different with the unmanned aerial vehicle set of taking off and landing place in the unmanned aerial vehicle set of taking off and landing place. For the cargo delivery point and the unmanned aerial vehicle landing point, the server judges whether the cargo delivery point and the unmanned aerial vehicle landing point are the same point, and the judgment method of the cargo start-up point and the unmanned aerial vehicle departure point can be referred to, and is not repeated herein.

When the server judges that the goods departure point and the unmanned aerial vehicle take-off and landing field are integrated, when the unmanned aerial vehicle take-off and landing field is matched, the unmanned aerial vehicle take-off and landing field is used as the starting point of the take-off and landing point of the unmanned aerial vehicle and the starting point of the initialized logistics pipeline, and when the server judges that the goods delivery point and the unmanned aerial vehicle take-off and landing field are matched, the unmanned aerial vehicle take-off and landing field is used as the landing point of the unmanned aerial vehicle and the ending point.

When the departure point of goods is different from the unmanned aerial vehicle take-off and landing field, the server acquires the load value of each unmanned aerial vehicle take-off and landing field in the unmanned aerial vehicle take-off and landing field set at a plurality of unmanned aerial vehicle take-off and landing fields in the unmanned aerial vehicle take-off and landing field set. And when the load state meets the preset condition, selecting the unmanned aerial vehicle taking-off and landing field as the flying point of the unmanned aerial vehicle to be determined. And the server calculates the distance between the take-off point of each undetermined unmanned aerial vehicle and the start point of the goods, and takes the take-off point of the undetermined unmanned aerial vehicle with the minimum distance as the take-off point of the unmanned aerial vehicle for the logistics transportation operation.

It should be noted that, when the goods arrival point and the unmanned aerial vehicle take-off and landing site are not matched, the corresponding unmanned aerial vehicle take-off and landing site can be allocated as the unmanned aerial vehicle landing point of the logistics transportation operation in the above manner, which is not described herein again.

Because the unmanned aerial vehicle does not have the pilot to carry out real-time adjustment to the aircraft situation at the flight in-process, so need some flight guarantee information to ensure unmanned aerial vehicle's flight safety at unmanned aerial vehicle flight in-process. In this application embodiment, unmanned aerial vehicle flight guarantee information is used for expressing the flight guarantee requirement of unmanned aerial vehicle flight in-process. Flight assurance requirements may include at least one of: the unmanned aerial vehicle is ensured to communicate with at least one ground station and/or navigation station in the flight process; at least one reserve landing place is guaranteed in the flight process of the unmanned aerial vehicle. Thus, the flight assurance point may be at least any one of: navigation stations, ground stations and landing yards.

At unmanned aerial vehicle carry out the in-process of commodity circulation transportation operation, in order to guarantee the real-time management and control to unmanned aerial vehicle, unmanned aerial vehicle need communicate with corresponding navigation platform and/or ground station at the flight in-process. Simultaneously, because numerous unexpected circumstances may appear in the flight, need select suitable take-off and landing place for unmanned aerial vehicle, take-off and landing place is used for when unmanned aerial vehicle need emergency forced landing because of weather or other special circumstances, provides at least one interim landing point for unmanned aerial vehicle.

It should be noted that the navigation station, the ground station, and the landing place of the drone may be designated by the user terminal, or may be selected by the server. Moreover, the number of the navigation stations, the ground station and the standby landing field can be adjusted according to the actual situation, and the number can be increased properly under the condition of longer flight distance.

In the embodiment of the application, the flight guarantee point can be determined according to the prestored electronic map, the unmanned aerial vehicle takeoff point and the unmanned aerial vehicle landing point. For example, the server determines a straight line determined by the unmanned aerial vehicle departure point and the unmanned aerial vehicle landing point, and based on the straight line determined by the unmanned aerial vehicle departure point and the unmanned aerial vehicle landing point, the server searches for a navigation station, a ground station, and a landing place which are the shortest distance from the straight line, and selects an appropriate number of navigation station ground stations and landing places according to the communication range between the navigation station and the ground station and the distance between the unmanned aerial vehicle departure point and the unmanned aerial vehicle landing point.

In this application embodiment, unmanned aerial vehicle departure point, unmanned aerial vehicle landing point, flight guarantee point can be according to the order in unmanned aerial vehicle flight in-process route and sort, constitute above-mentioned initialization key point sequence.

In the embodiment of the application, the unmanned aerial vehicle departure point, the unmanned aerial vehicle landing point, and the flight assurance point may be represented by coordinates, for example, the longitude of the unmanned aerial vehicle departure and landing field corresponding to the cargo departure and transportation point on the electronic map is 116.54 °, the latitude is 39.93 °, and then the key point coordinates of the unmanned aerial vehicle departure and landing point corresponding to the cargo departure and transportation point are (116.54, 39.93).

S103, the server generates a corresponding initialized logistics pipeline based on the initialized key point sequence.

The initialization logistics pipeline is composed of at least one temporary logistics pipeline section. And each temporary logistics pipeline segment is generated by the server according to two adjacent logistics pipeline key points in the initialization key point sequence and the flight performance information of the unmanned aerial vehicle. And when the number of the temporary logistics pipeline sections is more than 1, all the temporary logistics pipeline sections are sequentially connected end to form the initialized logistics pipeline.

Wherein, unmanned aerial vehicle flight performance information can include maximum flying height, minimum flying height and side direction safety width.

The temporary flow conduit may include a beginning section, at least one intermediate section, and an ending section. The starting section is a temporary logistics pipeline section from the takeoff stage to the stable flight stage of the unmanned aerial vehicle; the ending section is a temporary logistics pipeline section for the unmanned aerial vehicle to land after finishing the stable flight phase until landing; at least one intermediate section between the starting section and the ending section is a temporary logistics pipeline section in a stable flight stage.

In this application specification, along the unmanned aerial vehicle's of each interim commodity circulation pipeline section flight direction, the section of corresponding interim commodity circulation pipeline is the rectangle. Fig. 4 is a schematic diagram that interim commodity circulation pipeline section is the interlude, and as shown in fig. 4, this interlude is the rectangle along its unmanned aerial vehicle flight direction's section. For convenience of expression, 401 in the figure may be referred to as the top height of the middle section, 402 as the bottom height of the middle section, and 403 as the width of the middle section.

Under the condition that interim commodity circulation pipeline section is the interlude, the top height of interlude is confirmed according to unmanned aerial vehicle maximum flight height, and the end height of interim commodity circulation pipeline section is confirmed according to unmanned aerial vehicle minimum flight height, and the width boundary of interim commodity circulation pipeline section is confirmed according to unmanned aerial vehicle's safe flight width.

For the initial section and the final section, because the aircraft at the initial section is in the climbing stage and the final section is in the landing stage, the temporary logistics pipeline sections respectively corresponding to the initial section and the final section are determined by depending on the performance information of the unmanned aerial vehicle, and the intermediate section is specifically referred to and is not repeated again.

And S104, the server determines a temporary logistics pipeline section which does not meet the first preset condition in the initialized logistics pipeline.

The initialized logistics pipeline is an idealized logistics pipeline which is initially established only after considering the takeoff and landing point and some necessary flight guarantee information of the unmanned aerial vehicle, however, in the actual flight work, the idealized initialized logistics pipeline is not suitable for some special situations, and needs to be adjusted according to some specific situations of the flight, and the details are as follows:

in the present specification, corresponding preset target conditions are preset, and the preset target conditions may include a first preset condition, a second preset condition, and a third preset condition.

Specifically, the first preset condition, the second preset condition, and the third preset condition may be any one of the following:

the temporary logistics pipeline section does not have a target obstacle, the airspace where the temporary logistics pipeline section is located is not a no-fly airspace, and the flight performance of the temporary logistics pipeline section is matched with that of the unmanned aerial vehicle. The first preset condition, the second preset condition and the third preset condition are different from each other.

It should be noted that, if each temporary material flow pipeline section in the initialized material flow pipeline obtained in step S103 meets the preset target condition, that is, meets the first preset condition, the second preset condition, and the third preset condition at the same time, the initialized material flow pipeline is used as the target material flow pipeline. In an embodiment of the present application, when the first preset condition is that the temporary logistics pipeline section does not have the target obstacle, as shown in fig. 5, step S104 may be implemented by the following steps:

s501, the server traverses all initialized logistics pipeline segments in the initialized logistics pipeline.

S502, the server determines the barrier with the height exceeding the preset height in the vertical downward projection range of each temporary logistics pipeline section based on a preset electronic map.

S503, the server determines the obstacle exceeding the preset height, and determines the lowest safe flying height of the unmanned aerial vehicle corresponding to the obstacle according to the preset rule.

S504, the server calculates the difference value between the minimum flying height of the unmanned aerial vehicle and the minimum safe flying height of the unmanned aerial vehicle.

And S505, when the difference value between the minimum flying height of the unmanned aerial vehicle and the minimum safe flying height of the unmanned aerial vehicle is negative, determining that the temporary logistics pipeline section does not meet the first preset condition.

In the practical application process, the server circularly acquires the existence condition of the obstacles from the first temporary logistics pipeline section to the last temporary logistics pipeline section. The embodiment of the present application specifically describes, as an example, that the server determines whether or not the tenth temporary distribution pipeline section satisfies the first preset condition.

An A model unmanned aerial vehicle, maximum flying height is 3000 meters, and minimum flying height is 2000 meters. Safe lateral width is 20 meters, according to A model unmanned aerial vehicle flight performance information, can confirm that the tenth interim logistics pipeline section is shown in fig. 3, and the top height of tenth interim logistics pipeline is 3000 meters promptly, and the end height is 2000 meters, and the width boundary is 20 meters.

And the server determines the geographic information in the vertical downward projection range of the tenth temporary logistics pipeline section according to a preset electronic map.

The minimum flying height of the A-type unmanned aerial vehicle is 2000 m, so that the flying safety of the unmanned aerial vehicle is guaranteed to the maximum extent, and the server determines the barrier with the height exceeding 1500 m in the projection range as the barrier to be determined based on a preset electronic map.

For example, there is an obstacle C having a height of 1700 meters, and the server regards the obstacle C as an obstacle to be determined. And according to the height value 1700 of the obstacle C to be determined, the server determines that the minimum safe flying height of the unmanned aerial vehicle corresponding to the obstacle C to be determined is 2100 meters.

The server makes a difference between the minimum flying height of the unmanned aerial vehicle model A and the minimum safe flying height corresponding to the target obstacle C to be determined, namely 2000 plus 2100, the obtained result is-100, and the server can determine the tenth temporary logistics pipeline section as the temporary logistics pipeline section which does not meet the first preset condition according to the negative value.

For another example, if the height of the obstacle D is 1500 meters, the obstacle D can be determined as the obstacle to be determined. And according to the height value 1500 of the obstacle D to be determined, the server determines that the minimum safe flying height of the unmanned aerial vehicle corresponding to the obstacle D to be determined is 1900 meters.

The server makes a difference between the minimum flying height of the unmanned aerial vehicle model A and the minimum safe flying height corresponding to the obstacle D to be determined, namely 2000 plus 1900, the obtained result is 100, and the result is a positive value, so that the server can determine that the tenth logistics pipeline section is a temporary logistics pipeline section meeting the first preset condition.

In some embodiments of the present application, when the first preset condition is that the airspace in which the temporary logistics pipeline section is located is not a no-fly airspace, as shown in fig. 6, step S104 may be implemented by:

s601, the server determines the flight time period of the unmanned aerial vehicle according to the logistics transportation request of the unmanned aerial vehicle.

Can include the time information of this time logistics transport operation in unmanned aerial vehicle logistics transport request, through this time information, unmanned aerial vehicle's flight time section in the time of can confirming this time logistics transport operation.

Specifically, the server determines the flight time period of the unmanned aerial vehicle according to the length of the initialized logistics pipeline and the flight performance information of the designated unmanned aerial vehicle model.

S602, the server acquires the airspace information in the flight time period of the unmanned aerial vehicle, and determines whether the airspace in which the temporary logistics pipeline section is located is a no-fly airspace according to the airspace information.

The server determines the temporary logistics pipeline section in the no-fly airspace in the flight time period of the unmanned aerial vehicle as the temporary logistics pipeline section which does not meet the first preset condition according to a preset electronic map.

In some embodiments of the present application, when the first preset condition is that the temporary logistics pipeline segment matches with the unmanned aerial vehicle performance information corresponding to the unmanned aerial vehicle logistics transportation request, as shown in fig. 7, step S104 may be implemented by:

s701, determining the performance information of the unmanned aerial vehicle according to the logistics transportation request of the unmanned aerial vehicle.

Wherein, unmanned aerial vehicle's performance information includes unmanned aerial vehicle minimum turning radius and the biggest slope that climbs of unmanned aerial vehicle.

Specifically, according to the unmanned aerial vehicle logistics transportation request, the unmanned aerial vehicle corresponding to the unmanned aerial vehicle logistics transportation request is determined, namely the unmanned aerial vehicle executing the logistics transportation operation at this time is executed, and therefore the performance information of the unmanned aerial vehicle executing the logistics transportation operation at this time is obtained.

S702, according to the position information of the key point of the logistics pipeline, the turning radius and the climbing gradient of the key point of the logistics pipeline are determined.

And S703, under the condition that at most one preset condition is met, the temporary logistics pipeline section corresponding to the logistics pipeline key point is the temporary logistics pipeline section which does not meet the first preset condition.

Wherein, the preset conditions include: the first difference is greater than the corresponding preset threshold, and the second difference is less than the corresponding preset threshold.

Specifically, the first difference is the difference between the turning radius of the key point of the logistics pipeline and the minimum turning radius of the unmanned aerial vehicle. The second difference is the difference between the climbing gradient of the key point of the logistics pipeline and the maximum climbing gradient of the unmanned aerial vehicle. In practical application, the logistics pipeline inevitably needs to turn to and lift the height in good time to, require unmanned aerial vehicle corresponding turn to and climb in order to adapt to the pipeline section. However, because the turning radius and climbing slope of the drone are limited due to the performance limitation of the drone, the performance limitation of the drone is fully considered when planning the logistics pipeline.

Specifically, the server judges whether there is the unmatched interim commodity circulation pipeline section with unmanned aerial vehicle minimum turning radius, can adopt following technical scheme:

and the server traverses each logistics pipeline key point, and takes three adjacent logistics pipeline key points as a detection unit. And determining two pipeline sections at every three logistics pipeline key points, calculating the turning radius of the pipeline sections of two adjacent temporary logistics pipeline sections by the server, and assigning the turning radius of the pipeline section to the middle logistics pipeline key point in the three logistics pipeline key points. The server makes a difference between the turning radius of the pipeline section of each logistics pipeline key point and the minimum turning radius of the unmanned aerial vehicle in sequence from the first logistics pipeline key point, and the difference is recorded as a first difference value; if the first difference value is larger than the corresponding preset threshold value, continuously calculating the key point of the next logistics pipeline; if the first difference value is smaller than the preset threshold value, the fact that the turning radius of the pipeline section of the middle logistics pipeline key point and the two pipeline sections determined by the front logistics pipeline key point and the rear logistics pipeline key point is smaller than the minimum turning radius of the unmanned aerial vehicle is represented, and the first difference value is not matched with the performance information of the unmanned aerial vehicle.

Specifically, the server judges whether the temporary logistics pipeline section which is not matched with the maximum climbing gradient of the unmanned aerial vehicle exists or not, and the following technical scheme can be adopted:

and the server traverses each logistics pipeline key point of the temporary third logistics pipeline and takes the adjacent three logistics pipeline key points as a detection unit. And determining two pipeline sections at every three logistics pipeline key points, calculating the climbing gradient of the pipeline sections of the two adjacent temporary logistics pipeline sections by the server, and assigning the climbing gradient value of the pipeline section to the middle logistics pipeline key point in the middle of the three logistics pipeline key points. The server makes a difference between the climbing gradient of the pipeline section of each logistics pipeline key point and the maximum climbing gradient of the unmanned aerial vehicle in sequence from the first logistics pipeline key point, and records the difference as a second difference; if the second difference is smaller than the preset threshold value, continuously calculating the key point of the next logistics pipeline; if the second difference value is larger than the preset threshold value, the pipeline climbing gradient of the middle logistics pipeline key point and the pipeline climbing gradient of the two pipeline sections determined by the front logistics pipeline key point and the rear logistics pipeline key point is larger than the unmanned maximum climbing gradient, and the unmanned aerial vehicle performance information is not matched.

And S105, the server searches a new logistics pipeline key point according to the temporary logistics pipeline section which does not meet the first preset condition until the new temporary logistics pipeline section generated according to the searched new logistics pipeline key point meets the preset target condition.

Specifically, as shown in fig. 8, the step S105 can be implemented by the following steps:

s801, adjusting the temporary material flow pipeline section in the temporary material flow pipeline which does not meet the first preset condition to obtain a first temporary material flow pipeline.

Specifically, according to the temporary logistics pipeline section which does not meet the first preset condition, a new logistics pipeline key point is searched until the temporary logistics pipeline section generated according to the new logistics pipeline key point meets the first preset condition.

And taking the new key point of the logistics pipeline corresponding to the temporary logistics pipeline section meeting the first preset condition as the key point of the first temporary logistics pipeline.

Generating a first temporary logistics pipeline according to the key point of the first temporary logistics pipeline;

s802, adjusting the temporary logistics pipeline section in the first temporary logistics pipeline which does not meet the second preset condition to obtain a second temporary logistics pipeline.

Specifically, according to a first temporary logistics pipeline section which does not meet a second preset condition in the first temporary logistics pipeline, a new logistics pipeline key point is searched again until a temporary logistics pipeline section generated according to the new logistics pipeline key point meets the first preset condition and the second preset condition,

and taking the new key point of the logistics pipeline corresponding to the temporary logistics pipeline section meeting the first preset condition and the second preset condition as the key point of the second temporary logistics pipeline.

And generating a second temporary logistics pipeline according to the second temporary logistics pipeline key point.

And S803, adjusting the temporary material flow pipeline section in the second temporary material flow pipeline which does not meet the third preset condition to obtain a third temporary material flow pipeline.

Specifically, according to a second temporary logistics pipeline which does not meet a third preset condition, a new logistics pipeline key point is searched until a temporary logistics pipeline section generated according to the new logistics pipeline key point meets a preset target condition. And taking the new key point of the logistics pipeline corresponding to the temporary logistics pipeline section meeting the preset target condition as a third key point of the temporary logistics pipeline.

And generating a third temporary logistics pipeline according to the key point of the third temporary logistics pipeline, wherein the third temporary logistics pipeline is a target logistics pipeline.

Determining that a temporary logistics pipeline section which does not meet a first preset condition exists in the temporary logistics pipeline according to the step S104, namely determining that a relatively ideal initialized logistics pipeline section which is determined according to the unmanned aerial vehicle flying point, the unmanned aerial vehicle landing point and the unmanned aerial vehicle flight guarantee point is not suitable for the actual flight process of the unmanned aerial vehicle, and further adjusting according to the preset condition. And, according to the step S104, it is determined that all the material flow pipeline sections that do not satisfy the first preset condition in the initialized material flow pipeline, it is only necessary to perform adjustment based on the material flow pipeline sections that do not satisfy the first preset condition found in the step S104.

In the embodiment of the application, for convenience of description, a case that no target obstacle exists in the temporary logistics pipeline segment is used as a first target condition, the temporary logistics pipeline segment is matched with unmanned aerial vehicle performance information corresponding to an unmanned aerial vehicle logistics transportation request to be used as a second target condition, and an airspace in which the temporary logistics pipeline segment is located is not a no-fly airspace is used as a third preset condition is described.

When the first preset condition is that the temporary material flow pipeline section does not have the target obstacle, as shown in fig. 9, the step S105 may be implemented by the following steps:

s901, the server determines the lowest safe flying height of the unmanned aerial vehicle of the logistics pipeline section to be adjusted based on the height value of the highest point of the target obstacle in the logistics pipeline section to be adjusted.

The material flow pipeline section to be adjusted is a temporary material flow pipeline section which does not meet a first preset condition.

S902, calculating the difference value between the maximum flying height of the unmanned aerial vehicle and the minimum safe flying height of the unmanned aerial vehicle under the condition that the minimum safe flying height of the unmanned aerial vehicle is smaller than the maximum flying height of the unmanned aerial vehicle.

And taking the difference value of the maximum flying height of the unmanned aerial vehicle and the minimum safe flying height of the unmanned aerial vehicle as a third difference value.

And S903, determining a new key point of the logistics pipeline under the condition that the third difference value is larger than the corresponding preset threshold value, taking the lowest safe flight height of the unmanned aerial vehicle as the bottom height of the temporary logistics pipeline, and updating the logistics pipeline to be adjusted to generate a corresponding first temporary logistics pipeline.

And S904, under the condition that the third difference value is smaller than the corresponding preset threshold value, determining a space range with the vertex of the target obstacle as the origin, and determining a new key point of the logistics pipeline in the space range until the logistics pipeline section generated according to the new key point of the logistics pipeline meets a first preset condition so as to generate a corresponding first temporary logistics pipeline.

As an example, the embodiment of the present application continues to use the performance parameters of the model a drone.

In one embodiment of the present application, the height of an obstacle C to be determined is 1700 meters, and the minimum safe flying height corresponding to the obstacle C to be determined is 2100 meters. The server makes a difference between the maximum flying height of the unmanned aerial vehicle type A and the minimum safe flying height corresponding to the obstacle C to be determined, namely 3000 plus 2100, the obtained result is 900, and if the result is positive, the difference 900 between the maximum flying height of the unmanned aerial vehicle type A and the minimum safe flying height corresponding to the obstacle C to be determined is determined as a third difference.

The server adjusts the bottom height of the initialized logistics pipeline to be the minimum safe flying height of the unmanned aerial vehicle corresponding to the barrier C, namely 2100 meters, and a first temporary logistics pipeline is obtained.

In an embodiment of the application, the height of an obstacle E to be determined is 2300 meters, the server determines that the minimum safe flying height of an unmanned aerial vehicle of type a corresponding to the obstacle E to be determined is 2700 meters according to the height of the obstacle E to be determined, the maximum flying height of the unmanned aerial vehicle of type a is 3000 meters, and the server obtains that the maximum flying height of the unmanned aerial vehicle is greater than the minimum safe flying height of the unmanned aerial vehicle corresponding to the obstacle E to be determined. And the server takes the difference value between the maximum flying height of the unmanned aerial vehicle and the minimum safe flying height of the unmanned aerial vehicle corresponding to the obstacle E to be determined as a third difference value, namely 300.

When the total weight of the cargos at the same cargo departure point and the same cargo arrival point is 1000kg and the maximum transportation load of each unmanned aerial vehicle is 100kg, 10 unmanned aerial vehicles are required to work together. And, the safe vertical interval of each unmanned aerial vehicle is 50 meters, and the preset threshold value is 10x50 and is 500.

And the server compares the third difference value with a preset threshold value, namely the third difference value is 300 and the preset threshold value is 500, and the server obtains that the third difference value is smaller than the preset threshold value.

And under the condition that the third difference value is smaller than the preset threshold value, the server searches for a new logistics pipeline key point in a space range with the top point of the obstacle E to be determined as the circle center and the radius of 100 meters, returns the new logistics pipeline key point to the step S104 for verification until the new logistics pipeline key point meets the condition that the third difference value is larger than the preset threshold value, and obtains a first temporary logistics pipeline according to the new logistics pipeline key point.

Under the condition that the first temporary logistics pipeline meets the first preset condition, the server judges whether the first temporary logistics pipeline meets the second preset condition, and under the condition that the first logistics pipeline does not meet the second preset condition, new logistics pipeline key points are searched for, so that a third temporary logistics pipeline generated according to the new logistics pipeline key points meets the first preset condition and the second preset condition.

Specifically, when the second preset condition is that the temporary logistics pipeline segment matches with the unmanned aerial vehicle performance information corresponding to the unmanned aerial vehicle logistics transportation request, the above S802 includes the following steps:

the first preset condition is a method for determining the temporary logistics pipeline section which does not meet the first preset condition when the temporary logistics pipeline section is matched with unmanned aerial vehicle performance information corresponding to the unmanned aerial vehicle logistics transportation request, and the temporary logistics pipeline section in the first temporary logistics pipeline which does not meet the second preset condition is determined.

After the temporary logistics pipeline section in the first temporary logistics pipeline which does not meet the second preset condition is determined, the server searches for a suitable next logistics pipeline key point based on the intermediate logistics pipeline key point until a first difference value at the intermediate logistics pipeline key point is larger than a preset threshold value, and after all the logistics pipeline key points are traversed, the temporary second temporary logistics pipeline is determined according to the logistics pipeline key point matched with the minimum turning radius of the unmanned aerial vehicle.

Specifically, the server determines a new temporary pipeline segment based on the pipeline segment that does not satisfy the second preset condition, and may adopt the following technical scheme:

after determining the key points of the logistics pipeline which at most meets one preset condition, the server searches for the appropriate key points of the next logistics pipeline based on the key points of the intermediate logistics pipeline until the first difference value of the key points of the intermediate logistics pipeline is larger than a preset threshold value and the second difference value is smaller than the preset threshold value. And after traversing all the key points of the logistics pipeline, determining a second temporary logistics pipeline according to the key points of the logistics pipeline, which meet the condition that the first difference is greater than a preset threshold and the second difference is smaller than the preset threshold.

In the embodiment of the application, besides the consideration of terrain factors and unmanned aerial vehicle performance factors, the planning of the logistics pipeline of the unmanned aerial vehicle is also greatly influenced by the restricted flight airspace.

When the third preset condition is that the airspace where the logistics pipeline section is located is not a no-fly airspace, the server judges whether the pipeline section which does not meet the third preset condition exists or not and adopts the following technical scheme:

and under the condition that the airspace in which the temporary logistics pipeline section is located is a no-fly airspace, determining a new logistics pipeline key point until the temporary logistics pipeline section generated according to the new logistics pipeline key point meets a preset target condition.

For example, when the server determines that the airspace in which the tenth logistics pipe section is located is a no-fly airspace. Because every interim commodity circulation pipeline section is confirmed by two commodity circulation pipeline key points, the commodity circulation pipeline key point that unmanned aerial vehicle passed through first is as the commodity circulation pipeline key point before, and latter commodity circulation pipeline key point is as the commodity circulation pipeline key point after. If the key point of the front logistics pipeline is not in the flight-forbidden airspace and the key point of the rear logistics pipeline is in the flight-forbidden airspace, a suitable key point of the new rear logistics pipeline is searched based on the key point of the front logistics pipeline, so that a pipeline section formed by the key point of the front logistics pipeline and the key point of the new rear logistics pipeline is not in the flight-forbidden airspace.

After the tenth logistics pipeline section is adjusted, the server sequentially detects backwards until all the logistics pipeline sections are located in airspaces which are not forbidden to fly, and the first preset condition and the second preset condition are met. And the server determines a third temporary logistics pipeline according to the condition that the airspace where all the logistics pipeline sections are located is not a no-fly airspace and meets the first preset condition and the second preset condition.

That is, the third temporary material flow pipeline section is the target material flow pipeline section.

In an actual application scenario, since an airspace may prompt adjustment due to some special situations, in order to further ensure safety and legality in the logistics transportation operation of the unmanned aerial vehicle, as shown in fig. 10, the method provided in the embodiment of the present application may further include the following technical solutions:

s1001, the current position information of the unmanned aerial vehicle is obtained in real time.

S1002, determining the distance between the current position of the unmanned aerial vehicle and the next target logistics pipeline section.

S1003, when the distance between the current position of the unmanned aerial vehicle and the next target logistics pipeline section is smaller than a preset distance, determining the current airspace information of the airspace where the next target logistics pipeline section is located.

And S1004, determining whether the next target logistics pipeline section is a temporary flight-forbidden airspace according to the current airspace information of the airspace in which the next target logistics pipeline section is located.

S1005, under the condition that the airspace where the next target logistics pipeline section is located is the temporary flight-forbidden airspace, searching a new logistics pipeline key point so that the new target logistics pipeline section generated according to the new logistics pipeline key point meets the preset target condition.

Through the steps S1001-S1005, the real-time adjustment can be performed on the target logistics pipeline, so that the safety and the legality of the unmanned aerial vehicle flight under the emergency situation can be ensured.

Specifically, based on the third temporary logistics pipeline (i.e., the target logistics pipeline segment), the server acquires the current position information of the unmanned aerial vehicle in real time through the ground station and the navigation station, and determines the distance from the unmanned aerial vehicle to the next logistics pipeline segment according to the distance between the current position of the unmanned aerial vehicle and the key point of the next logistics pipeline. And when the distance between the unmanned aerial vehicle and the next logistics pipeline section is less than the preset distance, the server determines the airspace information of the airspace in which the next logistics pipeline section is located based on the preset electronic map.

The preset distance needs to be determined specifically according to specific pipeline conditions, airspace information, unmanned aerial vehicle performance information and the like, and the purpose is to provide enough response time for the unmanned aerial vehicle. The preset distance is not specifically limited in the embodiment of the present application.

And the server determines whether the airspace in which the next pipeline section is located has a temporary no-fly airspace according to the acquired airspace information of the next logistics pipeline section. At the moment, the distance between the unmanned aerial vehicle and the airspace where the next logistics pipeline section is located is short, and corresponding announcements are made even if a temporary flight forbidding airspace exists.

When the airspace where the next logistics pipeline section is located is a temporary flight-forbidding airspace, the server searches for a new logistics pipeline key point based on a post logistics pipeline key point of the logistics pipeline section where the unmanned aerial vehicle is currently located, so that the new logistics pipeline section formed by the post logistics pipeline key point and the new logistics pipeline key point avoids the temporary flight-forbidding airspace, and the server determines a fourth temporary logistics pipeline according to the pipeline section avoiding the temporary flight-forbidding airspace and the temporary logistics pipeline section meeting the first preset condition, the second preset condition and the third preset condition.

When the weight of the goods between the same goods departure point and the goods arrival point in the single logistics transportation operation exceeds the maximum load of a single unmanned aerial vehicle in the unmanned aerial vehicle logistics transportation request, the server distributes a plurality of unmanned aerial vehicles according to the total weight of the goods and the load condition of each unmanned aerial vehicle. Based on this, as shown in fig. 11, the embodiment of the present application further provides the following technical solutions:

s1101, determining the number of first unmanned aerial vehicles capable of being accommodated by the target logistics pipeline according to the fourth difference value and the flight performance information of the unmanned aerial vehicles.

Wherein the fourth difference is the minimum vertical distance of the target stream conduit.

S1102, determining the number of unmanned aerial vehicles with the same cargo departure point and the same cargo delivery point in the same time period as the number of second unmanned aerial vehicles according to the unmanned aerial vehicle logistics transportation request.

And S1103, layering the target logistics pipeline sections in the vertical direction according to a preset rule under the condition that the number of the second unmanned aerial vehicles is smaller than that of the first unmanned aerial vehicles, so as to obtain corresponding sub-target logistics pipelines.

The server determines the number of the second unmanned aerial vehicles according to the weight of the same goods in the single logistics transportation operation, the goods in the goods departure point and the goods in the goods arrival point and the load condition of the single unmanned aerial vehicle.

For example, the total weight of the cargos at the same cargo departure point and the same cargo arrival point in a single logistics transportation operation is 1000kg, the maximum load of a single unmanned aerial vehicle is 100kg, the server can obtain the maximum load, and the number of the second unmanned aerial vehicles is 10.

And under the condition that the number of the second unmanned aerial vehicles is smaller than that of the first unmanned aerial vehicles, layering the target logistics pipelines along the flight direction of the unmanned aerial vehicles so as to obtain a plurality of sub-target logistics pipelines.

The unmanned aerial vehicle path planning method provided by the embodiment of the application solves the problems that the path planning in the prior art is not suitable for the unmanned aerial vehicle logistics transportation industry and has low safety. According to the technical scheme, the unmanned aerial vehicle logistics transportation request from the user terminal is received, and the initialization key point sequence and the initialization logistics pipeline are generated based on the unmanned aerial vehicle logistics transportation request. When the initialized logistics pipeline does not meet the preset conditions, the initialized logistics pipeline is adjusted until the adjusted logistics pipeline meets all the preset conditions, so that a path suitable for the logistics unmanned aerial vehicle is determined. By the method, a logistics transportation pipeline is provided for the unmanned aerial vehicle for logistics transportation operation, the safety of the unmanned aerial vehicle and goods in the flight process is guaranteed, the logistics transportation efficiency is greatly improved, and the logistics transportation time is shortened.

Based on the same idea, some embodiments of the present application further provide a device corresponding to the above method.

Fig. 12 is a schematic structural diagram of an unmanned aerial vehicle logistics path planning apparatus provided in an embodiment of the present application, and as shown in fig. 12, the apparatus includes:

at least one processor, and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to: receiving an unmanned aerial vehicle logistics transportation request from a user terminal;

generating a corresponding initialization key point sequence according to the unmanned aerial vehicle logistics transportation request, and generating a corresponding initialization logistics pipeline based on the initialization key point sequence; the initialization key point sequence consists of key points of a logistics pipeline, and the key points of the logistics pipeline are used for representing passing points of the unmanned aerial vehicle flying; determining a temporary logistics pipeline section which does not meet a first preset condition in the initialized logistics pipeline; searching a new logistics pipeline key point according to the temporary logistics pipeline section which does not meet the first preset condition until the new temporary logistics pipeline section generated according to the new logistics pipeline key point meets the preset target condition; taking a new logistics pipeline key point corresponding to a new temporary logistics pipeline section meeting a preset target condition as a target logistics pipeline key point; and updating the initialized logistics pipeline according to the key points of the target logistics pipeline to obtain the corresponding target logistics pipeline.

The embodiments in the present application are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The devices and the methods provided by the embodiment of the application are in one-to-one correspondence, so the devices also have beneficial technical effects similar to the corresponding methods.

Those skilled in the art will recognize that in one or more of the examples described above, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.

The above-mentioned embodiments, objects, technical solutions and advantages of the present invention are further described in detail, it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made on the basis of the technical solutions of the present invention should be included in the scope of the present invention.

Claims

1. An unmanned aerial vehicle logistics path planning method is characterized by comprising the following steps:

receiving an unmanned aerial vehicle logistics transportation request from a user terminal;

generating a corresponding initialization key point sequence according to the unmanned aerial vehicle logistics transportation request, and generating an initialization logistics pipeline according to the initialization key point sequence;

the initialization key point sequence consists of key points of a logistics pipeline, and the key points of the logistics pipeline are used for representing passing points of the unmanned aerial vehicle flying;

determining a temporary logistics pipeline section which does not meet a first preset condition in the initialized logistics pipeline;

searching a new logistics pipeline key point according to the temporary logistics pipeline section which does not meet the first preset condition until a new temporary logistics pipeline section generated according to the new logistics pipeline key point meets a preset target condition; taking a new logistics pipeline key point corresponding to a new temporary logistics pipeline section meeting a preset target condition as a target logistics pipeline key point;

and updating the initialized logistics pipeline according to the key point of the target logistics pipeline to obtain the corresponding target logistics pipeline.

2. The method according to claim 1, wherein generating the corresponding initialized logistics pipeline based on the initialization key point specifically comprises:

generating the initialization key point sequence according to a cargo start-up point, a cargo delivery point and pre-acquired unmanned aerial vehicle flight guarantee information in the unmanned aerial vehicle logistics transportation request;

the initialization key point sequence comprises an unmanned aerial vehicle flying point, an unmanned aerial vehicle landing point and a flight guarantee point;

generating corresponding temporary logistics pipeline sections according to two adjacent logistics pipeline key points in the initialization key point sequence and the pre-acquired flight performance information of the unmanned aerial vehicle;

and combining the temporary logistics pipeline sections according to corresponding preset rules to form the initialized logistics pipeline.

3. The method according to claim 1, characterized in that said preset target conditions comprise at least: a first preset condition, a second preset condition and a third preset condition;

the method includes the steps of searching a new key point of the logistics pipeline according to a temporary logistics pipeline section which does not meet the first preset condition until a temporary logistics pipeline section which is generated according to the new key point of the logistics pipeline meets a preset target condition, and specifically includes the following steps:

searching a new key point of the logistics pipeline according to the temporary logistics pipeline section which does not meet the first preset condition until the temporary logistics pipeline section generated according to the new key point of the logistics pipeline meets the first preset condition so as to generate a first temporary logistics pipeline;

according to the temporary logistics pipeline section which does not meet the second preset condition in the first temporary logistics pipeline, searching a new logistics pipeline key point again until the temporary logistics pipeline section generated according to the new logistics pipeline key point meets the first preset condition and the second preset condition so as to generate a second temporary logistics pipeline;

and searching a new key point of the logistics pipeline according to the second temporary logistics pipeline which does not meet the third preset condition until the temporary logistics pipeline section generated according to the new key point of the logistics pipeline meets the preset target condition so as to generate a third temporary logistics pipeline.

4. The method according to claim 3, wherein the first preset condition, the second preset condition and the third preset condition are any one of the following conditions:

no target obstacle exists in the temporary logistics pipeline section; and is

The airspace in which the temporary logistics pipeline section is positioned is not a no-fly airspace; and

the temporary logistics pipeline section is matched with unmanned aerial vehicle performance information corresponding to the unmanned aerial vehicle logistics transportation request;

the first preset condition, the second preset condition and the third preset condition are different from each other.

5. The method according to claim 4, wherein when the first preset condition is that the temporary logistics pipeline segment matches performance information in the unmanned aerial vehicle logistics transportation request, determining the temporary logistics pipeline segment that does not meet the first preset condition specifically includes:

determining performance information of the unmanned aerial vehicle according to the unmanned aerial vehicle transportation request; wherein the performance information includes: the minimum turning radius of the unmanned aerial vehicle and the maximum climbing gradient of the unmanned aerial vehicle are determined;

determining the turning radius and climbing gradient of the key point of the logistics pipeline according to the position information of the key point of the logistics pipeline;

under the condition that at most one preset condition is met, the temporary logistics pipeline section corresponding to the logistics pipeline key point is a temporary logistics pipeline section which does not meet the first preset condition;

the preset conditions are as follows: the first difference is larger than a corresponding preset threshold value, and the second difference is smaller than a corresponding preset threshold value;

wherein the first difference value is the difference value between the turning radius of the key point of the logistics pipeline and the minimum turning radius of the unmanned aerial vehicle; the second difference is the difference between the climbing gradient of the key point of the logistics pipeline and the maximum climbing gradient of the unmanned aerial vehicle.

6. The method according to claim 4, wherein when the airspace in which the temporary logistics pipeline section is located is not a no-fly airspace, the determining the temporary logistics pipeline section which does not meet the first preset condition in the initialized logistics pipeline specifically includes:

determining a flight time period of the unmanned aerial vehicle according to the unmanned aerial vehicle transportation request;

acquiring airspace information in the flight time period, and determining whether the airspace in which each temporary logistics pipeline section is located is a no-flight airspace according to the airspace information;

and determining the temporary logistics pipeline section of which the airspace is the no-fly airspace as the temporary logistics pipeline section which does not meet the second preset condition.

7. The method according to claim 4, wherein, in the case that the first preset condition is that no target obstacle exists in the temporary logistics pipeline section, the generating a first temporary logistics pipeline specifically comprises:

determining the lowest safe flying height of the unmanned aerial vehicle of the logistics pipeline section to be adjusted based on the height value of the highest point of the target obstacle in the logistics pipeline section to be adjusted; wherein, the temporary material flow pipeline section which does not meet the first preset condition is used as the material flow pipeline section to be adjusted;

under the condition that the minimum safe flying height of the unmanned aerial vehicle is smaller than the maximum flying height of the unmanned aerial vehicle, calculating a difference value between the maximum flying height of the unmanned aerial vehicle and the minimum safe flying height of the unmanned aerial vehicle, and taking the difference value between the maximum flying height of the unmanned aerial vehicle and the minimum safe flying height of the unmanned aerial vehicle as a third difference value;

determining a new logistics pipeline key point under the condition that the third difference value is larger than a corresponding preset threshold value, taking the lowest safe flight height of the unmanned aerial vehicle as the bottom height of the logistics pipeline to be adjusted, and updating the logistics pipeline to be adjusted to generate a corresponding first temporary logistics pipeline;

and under the condition that the third difference value is smaller than the corresponding preset threshold value, determining a space range with the vertex of the target obstacle as an origin, and determining a new key point of the logistics pipeline in the space range until the temporary logistics pipeline section generated according to the new key point of the logistics pipeline meets a first preset condition so as to generate a corresponding first temporary logistics pipeline.

8. The method of claim 1, further comprising:

acquiring current position information of the unmanned aerial vehicle in real time;

determining the distance between the current position of the unmanned aerial vehicle and the next target logistics pipeline section; wherein the target stream pipeline is comprised of target stream pipeline segments;

when the distance between the current position of the unmanned aerial vehicle and the next target logistics pipeline section is smaller than the preset distance, determining the current airspace information of the airspace in which the next target logistics pipeline section is located;

determining whether the next target logistics pipeline section is a temporary flight-forbidden airspace according to the current airspace information of the airspace in which the next target logistics pipeline section is located;

and under the condition that the airspace where the next target logistics pipeline section is located is a temporary flight-forbidden airspace, searching for a new logistics pipeline key point so that the new target logistics pipeline section generated according to the new key point meets the preset target condition.

9. The method of claim 1, further comprising:

determining the first unmanned aerial vehicle number which can be accommodated by the target logistics pipeline according to the fourth difference and the unmanned aerial vehicle flight performance information corresponding to the unmanned aerial vehicle logistics transportation request; wherein the fourth difference is a minimum vertical distance of the target stream conduit;

determining the number of unmanned aerial vehicles with the same cargo departure point and the same cargo arrival point in the same time period as the number of second unmanned aerial vehicles according to the unmanned aerial vehicle logistics transportation request;

and under the condition that the number of the second unmanned aerial vehicles is smaller than that of the first unmanned aerial vehicles, layering each target logistics pipeline segment along the flight direction of the unmanned aerial vehicles according to a preset rule to obtain corresponding sub-target logistics pipelines.

10. An unmanned aerial vehicle logistics path planning equipment which is characterized by comprising:

at least one processor; and the number of the first and second groups,

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to:

generating a corresponding initialization key point sequence according to the unmanned aerial vehicle logistics transportation request, and generating a corresponding initialization logistics pipeline based on the initialization key point sequence;