CN115061489A

CN115061489A - Unmanned aerial vehicle distribution planning method, device and system

Info

Publication number: CN115061489A
Application number: CN202110975855.6A
Authority: CN
Inventors: 苏志智
Original assignee: Individual
Current assignee: Individual
Priority date: 2021-08-24
Filing date: 2021-08-24
Publication date: 2022-09-16

Abstract

The invention discloses a method, a device and a system for unmanned aerial vehicle distribution planning, wherein the method comprises the following steps: acquiring unmanned aerial vehicle monitoring information corresponding to a plurality of transportation tracks; the transportation track is arranged above the target transportation area so as to enable the transportation unmanned aerial vehicle to carry out flying distribution; determining unmanned aerial vehicle bearing information corresponding to the transportation track according to the unmanned aerial vehicle monitoring information corresponding to the transportation track; determining an unmanned aerial vehicle scheduling strategy according to the track route information corresponding to all the transportation tracks and the unmanned aerial vehicle bearing information; the unmanned aerial vehicle scheduling strategy is used for scheduling at least one target transport unmanned aerial vehicle to enter a corresponding transport track to fly, so that the distribution efficiency of the target transport area is improved. Therefore, the invention can realize more efficient and more reasonable dispatching of the unmanned aerial vehicle so as to improve the distribution efficiency of the distribution area and bring better distribution service experience for users.

Description

Unmanned aerial vehicle distribution planning method, device and system

Technical Field

The invention relates to the technical field of unmanned aerial vehicles, in particular to a method, a device and a system for planning distribution of an unmanned aerial vehicle.

Background

Unmanned aerial vehicle is called unmanned aerial vehicle for short, as emerging scientific and technological product, has obtained rapid development in recent years, and unmanned aerial vehicle not only obtains large-scale application in fields such as fire control, patrolling and examining, agriculture, commodity circulation, etc. also is accepted gradually by common people, has gradually promoted numerous consumption level products at present. Following this, some fast food distribution businesses are also considering the incorporation of unmanned aerial vehicles into the confines of distribution tools to provide customers with the distribution of fast food or semi-finished delicatessens.

However, with the development of unmanned aerial vehicle distribution service, more and more unmanned aerial vehicles fly at low altitude, the unmanned aerial vehicles at low altitude are more and more dense, and the collision risk of the unmanned aerial vehicles becomes greater and greater. The unmanned aerial vehicle can fly orderly, which is an effective way for solving the problem, and the distribution planning for the unmanned aerial vehicle is an implementation scheme for achieving the goal of orderly flying with the most cost performance under the prior art condition. How to plan the flight path of the unmanned aerial vehicle becomes an increasingly urgent problem to be solved.

Disclosure of Invention

The invention aims to solve the technical problem of providing an unmanned aerial vehicle distribution planning method, device and system, which can determine the bearing condition of a transportation track based on monitoring information acquired by a plurality of unmanned aerial vehicle transportation tracks and further determine an unmanned aerial vehicle dispatching strategy, thereby realizing more efficient and more reasonable dispatching of the unmanned aerial vehicle so as to improve the distribution efficiency of a distribution area and bring better distribution service experience for users.

In order to solve the technical problem, a first aspect of the present invention discloses an unmanned aerial vehicle distribution planning method, including:

acquiring unmanned aerial vehicle monitoring information corresponding to a plurality of transportation tracks; the transportation track is arranged above the target transportation area so as to enable the transportation unmanned aerial vehicle to carry out flying distribution;

determining unmanned aerial vehicle bearing information corresponding to the transportation track according to the unmanned aerial vehicle monitoring information corresponding to the transportation track;

determining an unmanned aerial vehicle scheduling strategy according to the track route information corresponding to all the transportation tracks and the unmanned aerial vehicle bearing information; the unmanned aerial vehicle scheduling strategy is used for scheduling at least one target transport unmanned aerial vehicle to enter a corresponding transport track for flying, so that the distribution efficiency of the target transport area is improved.

As an optional implementation manner, in the first aspect of the present invention, the drone monitoring information includes one or more of number information, speed information, electric quantity information, and load information of the transportation drones.

As an optional implementation manner, in the first aspect of the present invention, the determining, according to the drone monitoring information corresponding to the transportation track, the drone bearer information corresponding to the transportation track includes:

according to the unmanned aerial vehicle monitoring information corresponding to the transportation track, determining quantity information of the transportation unmanned aerial vehicles in the transportation track, and determining the quantity information as unmanned aerial vehicle bearing information corresponding to the transportation track;

and/or the presence of a gas in the gas,

determining the quantity information of the transport unmanned aerial vehicles in the transport track and the speed information of all the transport unmanned aerial vehicles according to the unmanned aerial vehicle monitoring information corresponding to the transport track;

calculating the average unmanned aerial vehicle transportation speed corresponding to the transportation track according to the quantity information of the transportation unmanned aerial vehicles and the speed information of all the transportation unmanned aerial vehicles, and determining the average unmanned aerial vehicle transportation speed as the unmanned aerial vehicle bearing information corresponding to the transportation track;

and/or the presence of a gas in the gas,

determining electric quantity information of all the transportation unmanned aerial vehicles in the transportation track according to the unmanned aerial vehicle monitoring information corresponding to the transportation track;

calculating the pause operation rate of the unmanned aerial vehicle corresponding to the transportation track according to the electric quantity information of all the transportation unmanned aerial vehicles and the remaining operation distance of each transportation unmanned aerial vehicle on the transportation track, and determining the pause operation rate of the unmanned aerial vehicle as the bearing information of the unmanned aerial vehicle corresponding to the transportation track;

and/or the presence of a gas in the gas,

determining load information of all the transport unmanned aerial vehicles in the transport track according to the unmanned aerial vehicle monitoring information corresponding to the transport track;

determining scheduling priority information of each transport unmanned aerial vehicle according to the load information of each transport unmanned aerial vehicle;

and calculating the unmanned aerial vehicle transportation priority information corresponding to the transportation track according to the scheduling priority information of all the transportation unmanned aerial vehicles, and determining the unmanned aerial vehicle transportation priority information as the unmanned aerial vehicle bearing information corresponding to the transportation track.

As an optional implementation manner, in the first aspect of the present invention, the determining a scheduling policy of an unmanned aerial vehicle according to track route information corresponding to all the transportation tracks and the bearer information of the unmanned aerial vehicle includes:

determining a busyness degree parameter corresponding to any one of the transportation tracks according to the unmanned aerial vehicle bearing information;

determining the route matching degree of the target transport unmanned aerial vehicle and any one transport track according to the track route information and the route information of the target transport unmanned aerial vehicle;

and determining a transportation track corresponding to the target transportation unmanned aerial vehicle according to the busy degree parameter and the route matching degree so as to determine an unmanned aerial vehicle scheduling strategy.

As an optional implementation manner, in the first aspect of the present invention, the determining, according to the busy degree parameter and the route matching degree, a transportation track corresponding to the target transportation unmanned aerial vehicle includes:

for any one transportation track, calculating a track matching parameter between the transportation track and the target transportation unmanned aerial vehicle according to the busy degree parameter and the route matching degree;

sequencing all the transportation tracks from large to small according to the track matching parameters to obtain a track sequence;

and determining the transportation tracks corresponding to the target transportation unmanned aerial vehicle according to the transportation tracks with the preset number in the front of the track sequence.

As an optional implementation manner, in the first aspect of the present invention, a plurality of charging devices are disposed on the transportation track; the method further comprises the following steps:

determining the residual electric quantity of any transport unmanned aerial vehicle in any transport track according to the unmanned aerial vehicle monitoring information;

when the residual electric quantity of any one transport unmanned aerial vehicle is judged to be lower than a preset electric quantity threshold value, generating a charging instruction corresponding to the transport unmanned aerial vehicle; the charging instruction is used for indicating the transportation unmanned aerial vehicle to establish power supply connection with the nearest charging equipment.

As an alternative implementation, in the first aspect of the present invention, the drone monitoring information includes sensing information of the transporting drone; the sensing information comprises one or more of image sensing information, electromagnetic wave sensing information and sound sensing information; the method further comprises the following steps:

judging the flight state of any transport unmanned aerial vehicle in any transport track according to the unmanned aerial vehicle monitoring information;

and when any one of the transport unmanned aerial vehicles is in a dangerous state, generating a rescue instruction corresponding to the transport unmanned aerial vehicle.

The second aspect of the invention discloses an unmanned aerial vehicle distribution planning device, which comprises:

the acquisition module is used for acquiring unmanned aerial vehicle monitoring information corresponding to the plurality of transportation tracks; the transportation track is arranged above the target transportation area so as to enable the transportation unmanned aerial vehicle to carry out flying distribution;

the bearing determining module is used for determining the unmanned aerial vehicle bearing information corresponding to the transportation track according to the unmanned aerial vehicle monitoring information corresponding to the transportation track;

the strategy determining module is used for determining an unmanned aerial vehicle scheduling strategy according to the track route information corresponding to all the transportation tracks and the unmanned aerial vehicle bearing information; the unmanned aerial vehicle scheduling strategy is used for scheduling at least one target transport unmanned aerial vehicle to enter a corresponding transport track to fly, so that the distribution efficiency of the target transport area is improved.

As an optional implementation manner, in the second aspect of the present invention, the drone monitoring information includes one or more of number information, speed information, electric quantity information, and load information of the transportation drones.

As an optional implementation manner, in the second aspect of the present invention, a specific manner of determining, by the bearer determining module, bearer information of the unmanned aerial vehicle corresponding to the transportation track according to the unmanned aerial vehicle monitoring information corresponding to the transportation track includes:

and/or the presence of a gas in the gas,

according to the unmanned aerial vehicle monitoring information corresponding to the transportation track, determining the quantity information of the transportation unmanned aerial vehicles in the transportation track and the speed information of all the transportation unmanned aerial vehicles;

and/or the presence of a gas in the gas,

and/or the presence of a gas in the atmosphere,

As an optional implementation manner, in the second aspect of the present invention, the specific manner in which the policy determining module determines the scheduling policy of the drone according to the track route information corresponding to all the transportation tracks and the bearer information of the drone includes:

determining a busy degree parameter corresponding to any one of the transportation tracks according to the unmanned aerial vehicle bearing information;

As an optional implementation manner, in the second aspect of the present invention, the specific manner in which the policy determining module determines the transportation track corresponding to the target transportation unmanned aerial vehicle according to the busy degree parameter and the route matching degree includes:

As an optional embodiment, in the second aspect of the present invention, a plurality of charging devices are disposed on the transportation rail; the device further comprises:

the electric quantity determining module is used for judging the residual electric quantity of any transport unmanned aerial vehicle in any transport track according to the unmanned aerial vehicle monitoring information;

the charging indication module is used for generating a charging instruction corresponding to the transportation unmanned aerial vehicle when the residual electric quantity of any transportation unmanned aerial vehicle is judged to be lower than a preset electric quantity threshold value; the charging instruction is used for indicating the transportation unmanned aerial vehicle to establish power supply connection with the nearest charging equipment.

As an optional embodiment, in the second aspect of the present invention, the drone monitoring information includes sensing information of the transport drone; the sensing information comprises one or more of image sensing information, electromagnetic wave sensing information and sound sensing information; the device further comprises:

the flight judging module is used for judging the flight state of any transport unmanned aerial vehicle in any transport track according to the unmanned aerial vehicle monitoring information;

and the rescue module is used for generating a rescue instruction corresponding to the transportation unmanned aerial vehicle when the transportation unmanned aerial vehicle is judged to be in a dangerous state.

The third aspect of the invention discloses another unmanned aerial vehicle distribution planning device, which comprises:

a memory storing executable program code;

a processor coupled with the memory;

the processor calls the executable program code stored in the memory to execute part or all of the steps of the unmanned aerial vehicle distribution planning method disclosed by the first aspect of the embodiment of the invention.

The fourth aspect of the embodiment of the present invention discloses an unmanned aerial vehicle distribution system, which includes a plurality of transportation tracks, a plurality of transportation unmanned aerial vehicles operating in the transportation tracks, and a control device respectively connected to the transportation tracks and the transportation unmanned aerial vehicles, wherein the control device is configured to perform part or all of the steps of the unmanned aerial vehicle distribution planning method disclosed in the first aspect of the embodiment of the present invention.

A fifth aspect of the present invention discloses a computer storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements part or all of the steps in the unmanned aerial vehicle distribution planning method disclosed in the first aspect of the embodiments of the present invention.

Compared with the prior art, the embodiment of the invention has the following beneficial effects:

in the embodiment of the invention, unmanned aerial vehicle monitoring information corresponding to a plurality of transportation tracks is obtained; the transportation track is arranged above the target transportation area so as to enable the transportation unmanned aerial vehicle to carry out flying distribution; determining unmanned aerial vehicle bearing information corresponding to the transportation track according to the unmanned aerial vehicle monitoring information corresponding to the transportation track; determining an unmanned aerial vehicle scheduling strategy according to the track route information corresponding to all the transportation tracks and the unmanned aerial vehicle bearing information; the unmanned aerial vehicle scheduling strategy is used for scheduling at least one target transport unmanned aerial vehicle to enter a corresponding transport track to fly, so that the distribution efficiency of the target transport area is improved. Therefore, the invention can determine the bearing condition of the transportation track based on the monitoring information acquired by the transportation tracks of the unmanned aerial vehicles, and further determine the scheduling strategy of the unmanned aerial vehicles, thereby realizing more efficient and more reasonable scheduling of the unmanned aerial vehicles so as to improve the distribution efficiency of the distribution area and bring better distribution service experience for users.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a schematic flow chart of a method for planning distribution of an unmanned aerial vehicle according to an embodiment of the present invention;

fig. 2 is a schematic structural diagram of an unmanned aerial vehicle distribution planning apparatus disclosed in the embodiment of the present invention;

fig. 3 is a schematic structural diagram of another unmanned aerial vehicle distribution planning apparatus disclosed in the embodiment of the present invention.

Detailed Description

In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The terms "first," "second," and the like in the description and claims of the present invention and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, article, or article that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or article.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

The invention discloses a method, a device and a system for planning distribution of unmanned aerial vehicles, which can determine the bearing condition of a transportation track based on monitoring information acquired by a plurality of unmanned aerial vehicle transportation tracks and further determine an unmanned aerial vehicle scheduling strategy, thereby realizing more efficient and more reasonable scheduling of the unmanned aerial vehicles so as to improve the distribution efficiency of a distribution area and bring better distribution service experience for users. The following are detailed below.

Example one

Referring to fig. 1, fig. 1 is a schematic flow chart of an unmanned aerial vehicle distribution planning method according to an embodiment of the present invention. The method described in fig. 1 may be applied to a corresponding control terminal, control device, or server, and the server may be a local server or a cloud server. As shown in fig. 1, the unmanned aerial vehicle distribution planning method may include the following operations:

101. and acquiring unmanned aerial vehicle monitoring information corresponding to the plurality of transportation tracks.

In the embodiment of the invention, the transportation track is arranged above the target transportation area so as to be used for the transportation of the unmanned aerial vehicle for flight distribution. Optionally, the transportation track can be closed track, like the tubulose track, unmanned aerial vehicle flies in the inner chamber, and closed track can guarantee that unmanned aerial vehicle's flight is difficult for receiving external factors's influence, for example in bad weather, unmanned aerial vehicle also can normally fly, and unmanned aerial vehicle's safety also can be protected simultaneously, for example unmanned aerial vehicle when losing the electricity or losing the signal and falling, can directly not fall to ground and damage, can receive by the track.

Optionally, the transportation track can be semi-enclosed, for example the cross-section is semi-circular or curved track, and certain cost can be saved to this type of track design, and also can provide certain sheltering from or bearing effect for unmanned aerial vehicle.

Optionally, the transportation track may be provided with a monitoring module for detecting a state of the transportation drone. Optionally, the drone monitoring information may include one or more of quantity information, speed information, power information, and load information of the transporting drones. Correspondingly, the monitoring module can also comprise one or more of a quantity monitoring unit, a speed monitoring unit, an electric quantity monitoring unit or a load monitoring unit. Specifically, the electric quantity monitoring unit also can be for establishing connection through the electric quantity detector who sets up on transportation unmanned aerial vehicle to acquire transportation unmanned aerial vehicle's electric quantity information in real time.

Optionally, transportation unmanned aerial vehicle can be used to transport the meal drink that makes, or semi-manufactured goods are like the batching package, for example, the food and beverage enterprise can transport meal preparation region through transportation unmanned aerial vehicle with semi-manufactured goods such as batching package or raw materials through the transportation track to through setting up at automatic food preparation robots such as the regional automatic machine people that fries rice, the semi-manufactured goods that will transport to are processed and are obtained the meal drink. Further, the food and beverage enterprise can transport the food and beverage article through transportation unmanned aerial vehicle and transport for the customer and enjoy.

Further, the transportation rail may be connected to a residence or receiving device of the customer, for example, a receiving device may be provided at a window of the customer to be connected with the transportation rail, so that the customer receives the object transported by the transportation drone. Further, can be provided with strorage device on the transportation track for deposit the article that transportation unmanned aerial vehicle transported, for the customer is from getting.

Further, the transportation track can also be provided with the module of charging for the transportation unmanned aerial vehicle that the electric quantity is not enough provides the service of charging, this service of charging can be for the task of automatic generation, also can be for the task that carries on based on unmanned aerial vehicle's request. Optionally, the charging service may require an entity corresponding to the transport drone to pay a certain fee.

102. And determining the unmanned aerial vehicle bearing information corresponding to the transportation track according to the unmanned aerial vehicle monitoring information corresponding to the transportation track.

103. And determining the scheduling strategy of the unmanned aerial vehicle according to the track route information corresponding to all the transportation tracks and the bearing information of the unmanned aerial vehicle.

In the embodiment of the invention, the unmanned aerial vehicle scheduling strategy is used for scheduling at least one target transport unmanned aerial vehicle to enter the corresponding transport track for flying, so that the distribution efficiency of a target transport area is improved.

Therefore, the method described by the embodiment of the invention can determine the bearing condition of the transportation track based on the monitoring information acquired by the transportation tracks of the unmanned aerial vehicles, and further determine the scheduling strategy of the unmanned aerial vehicles, so that the unmanned aerial vehicles can be more efficiently and more reasonably scheduled to improve the distribution efficiency of the distribution area, and better distribution service experience is brought to users.

In an optional implementation manner, the determining, according to the monitoring information of the unmanned aerial vehicle corresponding to the transportation track in step 102, the load bearing information of the unmanned aerial vehicle corresponding to the transportation track includes:

according to the unmanned aerial vehicle monitoring information corresponding to the transportation track, determining the quantity information of the transportation unmanned aerial vehicles in the transportation track, and determining the quantity information as the bearing information of the unmanned aerial vehicles corresponding to the transportation track.

It is thus clear that implementing this optional implementation can be determined the quantity information for the unmanned aerial vehicle that the transportation track corresponds bears the information to more accurately determine unmanned aerial vehicle and bear the information, be favorable to improving the accuracy of follow-up calculation unmanned aerial vehicle scheduling strategy, and then improved unmanned aerial vehicle delivery planning's intelligent degree and accuracy.

determining the quantity information of the unmanned transport vehicles in the transport track and the speed information of all unmanned transport vehicles according to the unmanned vehicle monitoring information corresponding to the transport track;

according to the quantity information of the unmanned aerial vehicles and the speed information of all the unmanned aerial vehicles, the average unmanned aerial vehicle transportation speed corresponding to the transportation track is calculated, and the average unmanned aerial vehicle transportation speed is determined as the unmanned aerial vehicle bearing information corresponding to the transportation track.

Optionally, the sum of the speed information of all unmanned aerial vehicles in transportation can be calculated, and the ratio of the speed information to the quantity information is calculated to obtain the average unmanned aerial vehicle transportation speed that the transportation track corresponds, the average unmanned aerial vehicle transportation speed obtained in this way can be used for indicating the smooth degree of transportation of the average unmanned aerial vehicle on the corresponding transportation track, and the follow-up degree of speed that unmanned aerial vehicle passes through the transportation track that can further be used for indicating.

It is thus clear that implementing this optional embodiment can calculate the average unmanned aerial vehicle transportation speed that the transportation track corresponds according to the quantity information of transporting unmanned aerial vehicle and all unmanned aerial vehicle's of transporting speed information to determine average unmanned aerial vehicle transportation speed more accurately, be favorable to improving the follow-up accuracy of calculating the unmanned aerial vehicle scheduling strategy, and then improved unmanned aerial vehicle delivery planning's intelligent degree and accuracy.

determining the electric quantity information of all the transport unmanned aerial vehicles in the transport track according to the unmanned aerial vehicle monitoring information corresponding to the transport track;

according to the electric quantity information of all the transport unmanned aerial vehicles and the remaining running distance of each transport unmanned aerial vehicle on the transport track, calculating the unmanned aerial vehicle pause running rate corresponding to the transport track, and determining the unmanned aerial vehicle pause running rate as the unmanned aerial vehicle bearing information corresponding to the transport track.

Alternatively, the remaining travel distance of each transport drone may be obtained by calculating the distance from the current position of each transport drone to the target end position along the transport track.

Optionally, the remaining travelable distance of the transport unmanned aerial vehicle can be determined according to the electric quantity information of the transport unmanned aerial vehicle and the corresponding transport power consumption rule, and whether the remaining travelable distance is smaller than the remaining travel distance is judged, and when the judgment result is yes, the transport unmanned aerial vehicle is determined to be of a predicted suspension type, that is, the transport unmanned aerial vehicle can suspend operation in the transport track.

Optionally, a ratio between the number of the transport drones of the expected suspension type among all the transport drones on the transport track and the total number of all the transport drones may be calculated to obtain the suspension operation rate of the drones.

It is thus clear that implementing this optional embodiment can calculate the unmanned aerial vehicle pause rate that the transportation track corresponds according to all transportation unmanned aerial vehicle's electric quantity information to and each transportation unmanned aerial vehicle remaining operating distance on the transportation track, thereby determine unmanned aerial vehicle pause rate more accurately, be favorable to improving the follow-up accuracy of calculating the unmanned aerial vehicle scheduling strategy, and then improved unmanned aerial vehicle delivery planning's intelligent degree and accuracy.

determining the load information of all the transport unmanned aerial vehicles in the transport track according to the unmanned aerial vehicle monitoring information corresponding to the transport track;

and calculating the transportation priority information of the unmanned aerial vehicle corresponding to the transportation track according to the scheduling priority information of all the transportation unmanned aerial vehicles, and determining the transportation priority information of the unmanned aerial vehicle as the bearing information of the unmanned aerial vehicle corresponding to the transportation track.

Optionally, the scheduling priority information of each transport unmanned aerial vehicle is determined according to the load information of each transport unmanned aerial vehicle, and may be determined according to the load information of each transport unmanned aerial vehicle and a preset load priority rule. Optionally, the load priority rule is used for limiting the corresponding relationship between the load weight and the priority level, preferably, the load priority rule may be a plurality of priorities corresponding to the load weights of a plurality of intervals, and by setting up the priority rule, the transport unmanned aerial vehicle with the heavier load can be released preferentially, so that the transport unmanned aerial vehicle can complete a task faster, and damage of the heavy object to the unmanned aerial vehicle is reduced.

Optionally, according to the scheduling priority information of all unmanned aerial vehicles, the unmanned aerial vehicle transportation priority information corresponding to the transportation track is calculated, and in all the unmanned aerial vehicles corresponding to the transportation track, the number of the unmanned aerial vehicles with high priority in the scheduling priority accounts for the total number of all the unmanned aerial vehicles so as to obtain the unmanned aerial vehicle transportation priority information.

It is thus clear that implementing this optional implementation can calculate the unmanned aerial vehicle transportation priority information that the transportation track corresponds according to all transportation unmanned aerial vehicle's scheduling priority information to determine unmanned aerial vehicle transportation priority information more accurately, be favorable to improving the follow-up accuracy of calculating the unmanned aerial vehicle scheduling strategy, and then improved unmanned aerial vehicle delivery planning's intelligent degree and accuracy.

In an optional implementation manner, the determining the scheduling policy of the drone according to the track route information corresponding to all the transportation tracks and the information carried by the drone in step 103 includes:

determining a busy degree parameter corresponding to any one transportation track according to the information carried by the unmanned aerial vehicle;

determining the route matching degree of the target transport unmanned aerial vehicle and any transport track according to the track route information and the route information of the target transport unmanned aerial vehicle;

Optionally, determining a busy degree parameter corresponding to any transportation track according to the information carried by the unmanned aerial vehicle may include:

and inputting one or more of the number information of the unmanned aerial vehicles, the average unmanned aerial vehicle transportation speed, the unmanned aerial vehicle suspension operation rate and the unmanned aerial vehicle transportation priority information, which are included in the unmanned aerial vehicle bearing information, into a preset busy calculation model to obtain a busy degree parameter. The busy calculation model is used for calculating the sum of products of one or more of the number information of the unmanned aerial vehicles, the average unmanned aerial vehicle transportation speed, the unmanned aerial vehicle pause operation rate and the unmanned aerial vehicle transportation priority information and the corresponding weight information. Alternatively, the corresponding weight information is used to indicate the importance degree of the corresponding parameter information, which may be determined empirically or experimentally, and the sum of all weight information should be 1.

Optionally, determining the route matching degree between the target transportation unmanned aerial vehicle and any transportation track according to the track route information and the route information of the target transportation unmanned aerial vehicle may include:

and calculating the similarity between the track route information of any transport track and the route information of the target transport unmanned aerial vehicle through a path matching algorithm, and determining the calculated similarity as the route matching degree of the target transport unmanned aerial vehicle and any transport track.

Therefore, the implementation of the optional implementation mode can determine the transportation track corresponding to the target transportation unmanned aerial vehicle according to the busyness degree parameter and the route matching degree so as to determine the unmanned aerial vehicle dispatching strategy, so that the unmanned aerial vehicle can be more efficiently and more reasonably dispatched to improve the dispatching efficiency of the dispatching area, and better dispatching service experience is brought to users.

In an optional implementation manner, the determining a transportation track corresponding to the target transportation unmanned aerial vehicle according to the busyness parameter and the route matching degree in the above steps includes:

for any transportation track, calculating a track matching parameter between the transportation track and the target transportation unmanned aerial vehicle according to the busy degree parameter and the route matching degree;

sequencing all the transportation tracks from large to small according to track matching parameters to obtain a track sequence;

and determining the transportation tracks corresponding to the target transportation unmanned aerial vehicle according to the transportation tracks with the number preset in the front of the track sequence.

Optionally, calculating a track matching parameter between the transportation track and the target transportation unmanned aerial vehicle according to the busy degree parameter and the route matching degree, and the calculating may include:

and inputting the busy degree parameter and the route matching degree into a preset track matching calculation model to obtain a track matching parameter. The track matching calculation model is used for calculating the sum of the busy degree parameter and the route matching degree and the product of the busy degree parameter and the route matching degree and the corresponding weight information. Optionally, the corresponding weight information is used to indicate the importance degree of the corresponding busyness parameter or route matching degree, which may be determined empirically or experimentally, and the sum of all weight information should be 1.

Optionally, determining the transportation track corresponding to the target transportation unmanned aerial vehicle according to the transport tracks of the previous preset number of the track sequence may include:

determining a first transportation track of the track sequence as a transportation track corresponding to the target transportation unmanned aerial vehicle;

or the like, or, alternatively,

in the front preset number of transportation tracks of the track sequence, the transportation track with the track inlet closest to the target transportation unmanned aerial vehicle is determined as the transportation track corresponding to the target transportation unmanned aerial vehicle

Therefore, by implementing the optional implementation mode, the transportation track corresponding to the target transportation unmanned aerial vehicle can be determined according to the busyness degree parameter and the route matching degree, so that the unmanned aerial vehicle scheduling strategy can be determined, the unmanned aerial vehicle can be scheduled more efficiently and more reasonably, the distribution efficiency of a distribution area is improved, and better distribution service experience is brought to users.

In an optional embodiment, a plurality of charging devices are disposed on the transportation track, and specifically, the method further includes:

determining the residual electric quantity of any transport unmanned aerial vehicle in any transport track according to the monitoring information of the unmanned aerial vehicle;

when the residual electric quantity of any transport unmanned aerial vehicle is judged to be lower than a preset electric quantity threshold value, a charging instruction corresponding to the transport unmanned aerial vehicle is generated.

In an embodiment of the present invention, the charging instruction is used to instruct the transport drone to establish a power supply connection with the nearest charging device. For example, the charging instruction may be used to instruct the transport drone to travel to the path of the nearest charging device, or to instruct the nearest charging device to issue an instruction to notify the transport drone.

Therefore, the optional implementation mode can generate the charging instruction corresponding to the transportation unmanned aerial vehicle when the residual electric quantity of any transportation unmanned aerial vehicle is judged to be lower than the preset electric quantity threshold value, so that the unmanned aerial vehicle can be charged timely, and better distribution service experience is brought to users.

In an alternative embodiment, the drone monitoring information includes sensory information of the transporting drone; the sensing information comprises one or more of image sensing information, electromagnetic wave sensing information and sound sensing information; specifically, the method further comprises:

when judging that any transport unmanned aerial vehicle is in the dangerous state, generate the rescue instruction that this transport unmanned aerial vehicle corresponds.

In the embodiment of the invention, the three-dimensional model of the transport unmanned aerial vehicle can be established through the image sensing information and/or the electromagnetic wave sensing information in the sensing information of the transport unmanned aerial vehicle, and the flight state of the transport unmanned aerial vehicle is judged according to the three-dimensional model of the transport unmanned aerial vehicle and a preset three-dimensional analysis algorithm.

In the embodiment of the invention, the flight state of the transport unmanned aerial vehicle can be judged through the sound information in the sensing information of the transport unmanned aerial vehicle and the preset fault sound template through a sound matching algorithm, for example, when the similarity between the sound information and the fault sound template is calculated to be higher than the preset similarity threshold value, the flight state of the transport unmanned aerial vehicle is judged to be in a dangerous state.

In the embodiment of the invention, the rescue instruction can be used for indicating the nearest rescue equipment or the related personnel or organization corresponding to the transport unmanned aerial vehicle to rescue the transport unmanned aerial vehicle, and optionally, the rescue instruction can include the position of the transport unmanned aerial vehicle or the expected falling position.

It is thus clear that implementing this optional implementation can generate the rescue instruction that this transportation unmanned aerial vehicle corresponds when judging that arbitrary transportation unmanned aerial vehicle is in the dangerous condition to can realize in time rescuing for unmanned aerial vehicle, with the safety of guaranteeing unmanned aerial vehicle, bring better distribution service for the user and experience.

Example two

Referring to fig. 2, fig. 2 is a schematic structural diagram of an unmanned aerial vehicle distribution planning apparatus according to an embodiment of the present invention. The apparatus described in fig. 2 may be applied to a corresponding control terminal, a corresponding control device, or a server, where the server may be a local server or a cloud server, and the embodiment of the present invention is not limited thereto. As shown in fig. 2, the apparatus may include:

the acquisition module 201 is configured to acquire unmanned aerial vehicle monitoring information corresponding to a plurality of transportation tracks.

In the embodiment of the invention, the transportation track is arranged above the target transportation area so as to be used for the transportation of the unmanned aerial vehicle for flight distribution. Optionally, the transportation track can be closed track, like the tubulose track, unmanned aerial vehicle flies in the inner chamber, and closed track can guarantee that unmanned aerial vehicle's flight is difficult for receiving external factors's influence, for example in bad weather, unmanned aerial vehicle also can normally fly, and unmanned aerial vehicle's safety also can be protected simultaneously, for example unmanned aerial vehicle when losing the electricity or losing the signal and fall, can directly not fall to ground damage, can receive by the track.

Optionally, transportation unmanned aerial vehicle can be used to transport the meal drink that makes, or semi-manufactured goods are like the batching package, for example, the food and beverage enterprise can transport the food and beverage preparation region through transportation unmanned aerial vehicle with semi-manufactured goods such as batching package or raw materials, through transporting the track to automatic food preparation robots such as the automatic fried rice robot that sets up in the food and beverage preparation region, the semi-manufactured goods that will transport to are processed and are obtained the meal drink. Further, the food and beverage enterprise can transport the food and beverage article through transportation unmanned aerial vehicle and transport for the customer and enjoy.

And a bearing determining module 202, configured to determine, according to the unmanned aerial vehicle monitoring information corresponding to the transportation track, that the unmanned aerial vehicle corresponding to the transportation track bears the information.

The strategy determining module 203 is used for determining an unmanned aerial vehicle scheduling strategy according to the track route information corresponding to all the transportation tracks and the unmanned aerial vehicle bearing information; the unmanned aerial vehicle scheduling strategy is used for scheduling at least one target transport unmanned aerial vehicle to enter the corresponding transport track for flying, so that the distribution efficiency of the target transport area is improved.

Therefore, the device described by the embodiment of the invention can determine the bearing condition of the transportation track based on the monitoring information acquired by the transportation tracks of the unmanned aerial vehicles, and further determine the scheduling strategy of the unmanned aerial vehicles, so that the unmanned aerial vehicles can be more efficiently and more reasonably scheduled to improve the distribution efficiency of a distribution area, and better distribution service experience is brought to users.

As an optional implementation manner, the specific manner in which the bearer determining module 202 determines the information bearer of the unmanned aerial vehicle corresponding to the transportation track according to the monitoring information of the unmanned aerial vehicle corresponding to the transportation track includes:

determining the quantity information of the unmanned planes in the transportation track and the speed information of all the unmanned planes according to the unmanned plane monitoring information corresponding to the transportation track;

according to the quantity information of the unmanned aerial vehicles and the speed information of all the unmanned aerial vehicles, calculating the average unmanned aerial vehicle transportation speed corresponding to the transportation track, and determining the average unmanned aerial vehicle transportation speed as the unmanned aerial vehicle bearing information corresponding to the transportation track.

Optionally, the remaining distance to be travelled of the transport unmanned aerial vehicle may be determined according to the electric quantity information of the transport unmanned aerial vehicle and the corresponding transport power consumption rule, and it is determined whether the remaining distance to be travelled is less than the remaining distance to be travelled, and when the determination result is yes, it is determined that the transport unmanned aerial vehicle is of a predicted suspension type, that is, the transport unmanned aerial vehicle may suspend its operation in the transport track.

Optionally, the number of transport drones of the type expected to pause among all the transport drones on the transport track may be calculated as a ratio to the total number of all the transport drones, so as to obtain the drone pause operation rate.

Optionally, the scheduling priority information of each transport unmanned aerial vehicle is determined according to the load information of each transport unmanned aerial vehicle, and may be determined according to the load information of each transport unmanned aerial vehicle and a preset load priority rule. Optionally, the load priority rule is used for limiting the corresponding relation between the load weight and the priority level, preferably, the load priority rule can be a plurality of priorities corresponding to the load weights of a plurality of intervals, and through the setting, the transport unmanned aerial vehicle with heavier load can be released preferentially, so that the unmanned aerial vehicle can complete the task more quickly, and damage of the heavy object to the unmanned aerial vehicle is reduced.

As an optional implementation manner, the policy determining module 203 determines a specific manner of the scheduling policy of the unmanned aerial vehicle according to the track route information corresponding to all the transportation tracks and the bearer information of the unmanned aerial vehicle, including:

inputting one or more of the number information of the unmanned aerial vehicles in transportation, the average unmanned aerial vehicle transportation speed, the unmanned aerial vehicle pause operation rate and the unmanned aerial vehicle transportation priority information, which are included in the unmanned aerial vehicle bearing information, into a preset busy calculation model to obtain a busy degree parameter. The busy calculation model is used for calculating the sum of products of one or more of the number information of the unmanned aerial vehicles, the average unmanned aerial vehicle transportation speed, the unmanned aerial vehicle pause operation rate and the unmanned aerial vehicle transportation priority information and the corresponding weight information. Alternatively, the corresponding weight information is used to indicate the degree of importance of the corresponding parameter information, which may be determined empirically or experimentally, and the sum of all weight information should be 1.

As an optional implementation manner, the determining module 203 determines a specific manner of the transportation track corresponding to the target transportation unmanned aerial vehicle according to the busyness parameter and the route matching degree, and includes:

or the like, or, alternatively,

As an optional implementation mode, a plurality of charging devices are arranged on the transportation track; the device also includes:

the electric quantity determining module is used for judging the residual electric quantity of any transport unmanned aerial vehicle in any transport track according to the monitoring information of the unmanned aerial vehicle;

and the charging indication module is used for generating a charging instruction corresponding to the transportation unmanned aerial vehicle when the residual electric quantity of any transportation unmanned aerial vehicle is judged to be lower than a preset electric quantity threshold value.

As an optional implementation, the drone monitoring information includes sensing information of the transport drone; the sensing information comprises one or more of image sensing information, electromagnetic wave sensing information and sound sensing information; the device also includes:

the flight judging module is used for judging the flight state of any transport unmanned aerial vehicle in any transport track according to the monitoring information of the unmanned aerial vehicle;

and the rescue module is used for generating a rescue instruction corresponding to the transportation unmanned aerial vehicle when any transportation unmanned aerial vehicle is judged to be in a dangerous state.

EXAMPLE III

Referring to fig. 3, fig. 3 is a schematic structural diagram of another unmanned aerial vehicle distribution planning apparatus disclosed in the embodiment of the present invention. As shown in fig. 3, the apparatus may include:

a memory 301 storing executable program code;

a processor 302 coupled to the memory 301;

the processor 302 calls the executable program code stored in the memory 301 to execute part or all of the steps of the unmanned aerial vehicle distribution planning method disclosed in the embodiment of the present invention.

Example four

The embodiment of the invention discloses a computer storage medium, which stores computer instructions, and when the computer instructions are called, the computer instructions are used for executing part or all of the steps in the unmanned aerial vehicle distribution planning method disclosed by the embodiment of the invention.

EXAMPLE five

The embodiment of the invention discloses an unmanned aerial vehicle distribution system which comprises a plurality of transportation tracks, a plurality of transportation unmanned aerial vehicles running in the transportation tracks and a control device respectively connected to the transportation tracks and the transportation unmanned aerial vehicles, wherein the control device is used for executing part or all steps in the unmanned aerial vehicle distribution planning method disclosed by the embodiment of the invention so as to realize distribution planning of the plurality of transportation unmanned aerial vehicles.

Specifically, the relevant technical details of the transportation track and the transportation unmanned aerial vehicle in the embodiment of the present invention may refer to the corresponding descriptions in the first embodiment, and the embodiment of the present invention is not described again.

The above-described embodiments of the apparatus are merely illustrative, and the modules described as separate parts may or may not be physically separate, and the parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Through the above detailed description of the embodiments, those skilled in the art will clearly understand that the embodiments may be implemented by software plus a necessary general hardware platform, and may also be implemented by hardware. Based on such understanding, the above technical solutions may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, where the storage medium includes a Read-Only Memory (ROM), a Random Access Memory (RAM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), a One-time Programmable Read-Only Memory (OTPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc-Read-Only Memory (CD-ROM), or other disk memories, CD-ROMs, or other magnetic disks, A tape memory, or any other medium readable by a computer that can be used to carry or store data.

Finally, it should be noted that: the method, the device and the system for planning the distribution of the unmanned aerial vehicle disclosed in the embodiment of the invention are only preferred embodiments of the invention, and are only used for illustrating the technical scheme of the invention, but not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art; the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An unmanned aerial vehicle delivery planning method, the method comprising:

determining an unmanned aerial vehicle scheduling strategy according to the track route information corresponding to all the transportation tracks and the unmanned aerial vehicle bearing information; the unmanned aerial vehicle scheduling strategy is used for scheduling at least one target transport unmanned aerial vehicle to enter a corresponding transport track to fly, so that the distribution efficiency of the target transport area is improved.

2. The unmanned aerial vehicle distribution planning method of claim 1, wherein the unmanned aerial vehicle monitoring information comprises one or more of quantity information, speed information, power information, and load information of the transport unmanned aerial vehicles.

3. The unmanned aerial vehicle distribution planning method of claim 1, wherein the determining, according to the unmanned aerial vehicle monitoring information corresponding to the transportation track, unmanned aerial vehicle bearer information corresponding to the transportation track comprises:

and/or the presence of a gas in the gas,

and/or the presence of a gas in the atmosphere,

4. The unmanned aerial vehicle delivery planning method of claim 1, wherein determining an unmanned aerial vehicle scheduling policy according to the track route information corresponding to all the transportation tracks and the unmanned aerial vehicle carrying information comprises:

5. The unmanned aerial vehicle distribution planning method of claim 4, wherein determining the transportation track corresponding to the target transportation unmanned aerial vehicle according to the busyness degree parameter and the route matching degree comprises:

6. The unmanned aerial vehicle distribution planning method of claim 1, wherein a plurality of charging devices are disposed on the transportation track; the method further comprises the following steps:

7. The unmanned aerial vehicle delivery planning method of claim 1, wherein the unmanned aerial vehicle monitoring information comprises sensory information of the transport unmanned aerial vehicle; the sensing information comprises one or more of image sensing information, electromagnetic wave sensing information and sound sensing information; the method further comprises the following steps:

8. An unmanned aerial vehicle delivery planning device, characterized in that the device includes:

9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.

10. An unmanned aerial vehicle distribution system, the system comprising a plurality of transportation tracks, a plurality of transport unmanned aerial vehicles operating in the transportation tracks, and control means connected to the transportation tracks and the transport unmanned aerial vehicles, respectively, the control means being configured to perform the unmanned aerial vehicle distribution planning method of any one of claims 1-7.