CN112987796A - Unmanned aerial vehicle control method and device, computer readable storage medium and unmanned aerial vehicle - Google Patents
Unmanned aerial vehicle control method and device, computer readable storage medium and unmanned aerial vehicle Download PDFInfo
- Publication number
- CN112987796A CN112987796A CN202110502881.7A CN202110502881A CN112987796A CN 112987796 A CN112987796 A CN 112987796A CN 202110502881 A CN202110502881 A CN 202110502881A CN 112987796 A CN112987796 A CN 112987796A
- Authority
- CN
- China
- Prior art keywords
- unmanned aerial
- aerial vehicle
- target
- drone
- determining
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 68
- 238000003860 storage Methods 0.000 title claims abstract description 21
- 230000015572 biosynthetic process Effects 0.000 claims abstract description 35
- 238000004891 communication Methods 0.000 claims description 36
- 238000004590 computer program Methods 0.000 claims description 17
- 230000008569 process Effects 0.000 abstract description 13
- 238000010586 diagram Methods 0.000 description 13
- 238000004364 calculation method Methods 0.000 description 11
- 230000006870 function Effects 0.000 description 11
- 230000006872 improvement Effects 0.000 description 9
- 230000001133 acceleration Effects 0.000 description 7
- 238000005516 engineering process Methods 0.000 description 7
- 238000012545 processing Methods 0.000 description 6
- 230000003287 optical effect Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
- 229920001296 polysiloxane Polymers 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
- G05D1/104—Simultaneous control of position or course in three dimensions specially adapted for aircraft involving a plurality of aircrafts, e.g. formation flying
Landscapes
- Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The present specification discloses a method and an apparatus for controlling an unmanned aerial vehicle, a computer-readable storage medium, and an unmanned aerial vehicle, which determine an unmanned aerial vehicle route to which a target unmanned aerial vehicle belongs, and determine at least one other unmanned aerial vehicle currently located on the unmanned aerial vehicle route, as a reference unmanned aerial vehicle. Secondly, determining the actual state deviation of the target unmanned aerial vehicle and the reference unmanned aerial vehicle in the unmanned aerial vehicle air route according to the current state data of the target unmanned aerial vehicle and the current state data of the reference unmanned aerial vehicle. And then, determining control parameters for the target unmanned aerial vehicle according to the actual state deviation and the acquired expected state deviation which enables formation flight between the target unmanned aerial vehicle and the reference unmanned aerial vehicle. And finally, controlling the target unmanned aerial vehicle. According to the method, the state data of the target unmanned aerial vehicle can be adjusted in the flight process according to the expected state deviation between the target unmanned aerial vehicle and the reference unmanned aerial vehicle, so that collision among the unmanned aerial vehicles is effectively avoided, and the efficiency of the unmanned aerial vehicle in executing tasks is improved.
Description
Technical Field
The present specification relates to the field of unmanned aerial vehicle technology, and in particular, to an unmanned aerial vehicle control method and apparatus, a computer-readable storage medium, and an unmanned aerial vehicle.
Background
With the continuous development of unmanned technology, unmanned equipment such as unmanned vehicles, unmanned control robots, unmanned aerial vehicles, and the like have been applied to many fields, which brings great convenience to business execution in these fields.
In the same area, in the process of flying a large number of unmanned aerial vehicles, a flight task is usually formulated for the unmanned aerial vehicles individually, and air routes are planned for a single unmanned aerial vehicle. However, in practical application, the unmanned aerial vehicle executes the flight mission in this way, the calculation amount of the background planning system is very large, and once the calculation is not in place, collision between the unmanned aerial vehicles can be caused, so that potential safety hazards are brought, and the efficiency of the unmanned aerial vehicle executing the mission is reduced.
Therefore, how to improve the calculation efficiency of the unmanned aerial vehicle for executing tasks and effectively avoid collision among the unmanned aerial vehicles is a problem to be solved urgently.
Disclosure of Invention
The present specification provides a method and an apparatus for controlling an unmanned aerial vehicle, a computer-readable storage medium, and an unmanned aerial vehicle, which partially solve the above problems in the prior art.
The technical scheme adopted by the specification is as follows:
this specification provides a control method of an unmanned aerial vehicle, including:
determining an unmanned aerial vehicle route to which a target unmanned aerial vehicle belongs, and determining at least one other unmanned aerial vehicle currently located on the unmanned aerial vehicle route as a reference unmanned aerial vehicle;
determining actual state deviation of the target unmanned aerial vehicle and the reference unmanned aerial vehicle in the unmanned aerial vehicle air route according to the current state data of the target unmanned aerial vehicle and the current state data of the reference unmanned aerial vehicle;
determining control parameters for the target unmanned aerial vehicle according to the actual state deviation and the acquired expected state deviation which enables the target unmanned aerial vehicle and the reference unmanned aerial vehicle to carry out formation flight;
and controlling the target unmanned aerial vehicle according to the control parameters.
Optionally, the expected state deviation is determined based on a flight interval of the target drone and the reference drone to form a formation flight in the drone route, the flight interval being determined according to a time when the target drone enters the drone route.
Optionally, determining at least one other drone currently located on the drone airline, as a reference drone, specifically includes:
determining at least one drone in the drone route that establishes a communication connection with the target drone as a reference drone.
Optionally, determining a control parameter for the target drone according to the actual state deviation and the acquired expected state deviation for enabling formation flight between the target drone and the reference drone specifically includes:
determining a leading drone located in the drone airline;
determining current corresponding reference state data of the leading unmanned aerial vehicle;
and determining control parameters for the target unmanned aerial vehicle on the basis of the reference state data according to the actual state deviation and the acquired expected state deviation which enables formation flight between the target unmanned aerial vehicle and the reference unmanned aerial vehicle.
Optionally, determining the current corresponding reference state data of the leading unmanned aerial vehicle specifically includes:
acquiring a state related item corresponding to the leading unmanned aerial vehicle, wherein the state related item is used for representing reference state data corresponding to the leading unmanned aerial vehicle at each moment in the unmanned aerial vehicle air route;
and determining the current corresponding reference state data of the leading unmanned aerial vehicle according to the state related items.
Optionally, the method further comprises:
if the target unmanned aerial vehicle reaches the scattered position of formation flight, disconnecting the communication connection between the target unmanned aerial vehicle and the reference unmanned aerial vehicle so that the unmanned aerial vehicle located in the unmanned aerial vehicle air line can control according to the state data of other unmanned aerial vehicles except the target unmanned aerial vehicle in the unmanned aerial vehicle air line.
Optionally, determining an unmanned aerial vehicle route to which the target unmanned aerial vehicle belongs specifically includes:
determining at least one unmanned aerial vehicle route corresponding to the delivery task as a candidate route according to the delivery task corresponding to the target unmanned aerial vehicle;
determining the number of unmanned aerial vehicles currently located in the candidate route as the number of unmanned aerial vehicles corresponding to the candidate route for each candidate route;
and determining the unmanned aerial vehicle route to which the target unmanned aerial vehicle belongs according to the number of the unmanned aerial vehicles corresponding to each candidate route.
This specification provides an unmanned aerial vehicle's controlling means, includes:
the acquisition module is used for determining an unmanned aerial vehicle route to which the target unmanned aerial vehicle belongs, and determining at least one other unmanned aerial vehicle currently located on the unmanned aerial vehicle route as a reference unmanned aerial vehicle;
the state determining module is used for determining the actual state deviation of the target unmanned aerial vehicle and the reference unmanned aerial vehicle in the unmanned aerial vehicle air route according to the current state data of the target unmanned aerial vehicle and the current state data of the reference unmanned aerial vehicle;
a parameter determination module, configured to determine a control parameter for the target unmanned aerial vehicle according to the actual state deviation and an acquired expected state deviation that enables formation flight between the target unmanned aerial vehicle and the reference unmanned aerial vehicle;
and the control module is used for controlling the target unmanned aerial vehicle according to the control parameters.
The present specification provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the above-described control method of a drone.
The present specification provides an unmanned aerial vehicle, including a memory, a processor, and a computer program stored on the memory and operable on the processor, wherein the processor implements the control method of the unmanned aerial vehicle when executing the program.
The technical scheme adopted by the specification can achieve the following beneficial effects:
in the method for controlling an unmanned aerial vehicle provided in the present specification, an unmanned aerial vehicle route to which a target unmanned aerial vehicle belongs is determined, and at least one other unmanned aerial vehicle currently located on the unmanned aerial vehicle route is determined as a reference unmanned aerial vehicle. Secondly, determining the actual state deviation of the target unmanned aerial vehicle and the reference unmanned aerial vehicle in the unmanned aerial vehicle air route according to the current state data of the target unmanned aerial vehicle and the current state data of the reference unmanned aerial vehicle. And then, determining control parameters for the target unmanned aerial vehicle according to the actual state deviation and the acquired expected state deviation which enables formation flight between the target unmanned aerial vehicle and the reference unmanned aerial vehicle. And finally, controlling the target unmanned aerial vehicle according to the control parameters.
Compared with the prior art, the method has the advantages that the method determines the air route of the unmanned aerial vehicle according to the flight task requirement, and adjusts the target unmanned aerial vehicle according to the state deviation between the target unmanned aerial vehicle and the reference unmanned aerial vehicle in the air route of the unmanned aerial vehicle, namely, the unmanned aerial vehicle is planned from the state of the formation of the unmanned aerial vehicles flying in the air route of the whole unmanned aerial vehicle to control the unmanned aerial vehicle, so that the redundant calculation for independently planning each aircraft is saved, and the efficiency of planning the unmanned aerial vehicle to execute the task is ensured.
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 a control method of an unmanned aerial vehicle in this specification;
fig. 2A and fig. 2B are schematic views of a flight process of an unmanned aerial vehicle provided in the present specification;
fig. 3 is a schematic diagram of a control device of an unmanned aerial vehicle provided in the present specification;
fig. 4 is a schematic diagram of a drone device corresponding to fig. 1 provided by the present description.
Detailed Description
In order to make the objects, technical solutions and advantages of the present disclosure more clear, the technical solutions of the present disclosure will be clearly and completely described below with reference to the specific embodiments of the present disclosure and the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present disclosure, and not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present specification without any creative effort belong to the protection scope of the present specification.
Fig. 1 is a schematic flow chart of a control method of an unmanned aerial vehicle in this specification, which specifically includes the following steps:
s100: determining an unmanned aerial vehicle route to which the target unmanned aerial vehicle belongs, and determining at least one other unmanned aerial vehicle currently located on the unmanned aerial vehicle route as a reference unmanned aerial vehicle.
The execution main body of the control method of the unmanned aerial vehicle related to the description can be the unmanned aerial vehicle, and can also be terminal equipment such as a server and a desktop computer. If use terminal equipment such as server, desktop computer as the execution main part, then terminal equipment can acquire unmanned aerial vehicle's state data to according to unmanned aerial vehicle's state data, determine control parameter, return the control parameter who determines for unmanned aerial vehicle, control unmanned aerial vehicle. For convenience of description, the following describes a control method of the unmanned aerial vehicle provided in this specification, with only the unmanned aerial vehicle as an execution subject.
In an embodiment of the present specification, the target drone may determine a drone airline to which the target drone belongs, and determine at least one other drone currently located on the drone airline, as the reference drone. The unmanned aerial vehicle course mentioned here can mean that unmanned aerial vehicle arrives the predetermined flight track of flight terminal point from the flight starting point, can record unmanned aerial vehicle in the unmanned aerial vehicle course and in each moment of predetermineeing the flight track, state data such as position, speed, acceleration that unmanned aerial vehicle corresponds.
In this embodiment, there are various methods for determining, by the target drone, another drone currently located on the drone route, for example, the target drone may establish a communication connection with another drone around the target drone through a wireless communication technology, and then determine whether the another drone establishing the communication connection is a reference drone of the same drone route. As another example, the target drone may determine, via the server, a reference drone that is in the same drone airline as the target drone.
In practical application, because the communication range of target unmanned aerial vehicle is limited, target unmanned aerial vehicle can't in fact establish communication connection with all unmanned aerial vehicles in the unmanned aerial vehicle airline, consequently, target unmanned aerial vehicle can establish communication connection with the unmanned aerial vehicle of reference in the communication range, refer to unmanned aerial vehicle and establish communication connection with other unmanned aerial vehicles in the communication range of self again, through the mode of information transfer, make target unmanned aerial vehicle acquire to be located this target unmanned aerial vehicle communication range, and be located the information of the unmanned aerial vehicle of reference of this unmanned aerial vehicle airline. Of course, the target drone may also communicate with a reference drone located outside the communication range of the target drone and located on the drone route through the server.
It should be noted that, the target drone establishes a communication connection with the reference drone within the communication range, and a structure diagram corresponding to a preset communication connection, such as a minimum spanning tree, needs to be satisfied to ensure normal communication between the drones. Under the condition of guaranteeing normal communication between the unmanned aerial vehicles, the unmanned aerial vehicle formation can be formed to the reference unmanned aerial vehicle in target unmanned aerial vehicle and the communication range and fly. In other words, reference to a drone in this description may refer to other drones that are located in the same flight formation as the target drone.
In this specification, the target drone may determine, according to a delivery task corresponding to the target drone itself, at least one drone route corresponding to the delivery task as a candidate route. Secondly, determining the number of the unmanned aerial vehicles currently located in the candidate route as the number of the unmanned aerial vehicles corresponding to the candidate route for each candidate route. And finally, determining the unmanned aerial vehicle route to which the target unmanned aerial vehicle belongs according to the number of the unmanned aerial vehicles corresponding to each candidate route.
In practical application, in the process of executing a distribution task, the number of unmanned aerial vehicles on the unmanned aerial vehicle route where the target unmanned aerial vehicle is located is increased, and the probability of collision between the unmanned aerial vehicles is increased. Therefore, the target unmanned aerial vehicle can select the candidate air routes with the number of the unmanned aerial vehicles within the set interval range from the candidate air routes corresponding to the delivery task, and the delivery task is executed through the candidate air routes, wherein the set interval range can be set manually according to actual requirements, namely, a proper set interval range is set manually, so that the probability of collision between the unmanned aerial vehicles is low, and the accuracy of the control parameters determined by the target unmanned aerial vehicle is high.
Further, the unmanned aerial vehicle air line selected by the target unmanned aerial vehicle may have other unmanned aerial vehicles to enter the unmanned aerial vehicle air line subsequently after the target unmanned aerial vehicle enters, so that the number of unmanned aerial vehicles in the unmanned aerial vehicle air line is increased, and the probability of collision among the unmanned aerial vehicles is increased. In order to ensure the flight safety of the target unmanned aerial vehicle, the target unmanned aerial vehicle needs to predict the number of unmanned aerial vehicles entering the unmanned aerial vehicle in a future period of time.
There may be a variety of ways for the target drone to predict the number of drones entering the drone flight path in a future period of time. For example, the target drone may predict the number of drones that the drone airline may enter in a future period of time according to historical data of the drone airline; for another example, the target unmanned aerial vehicle may predict the number of unmanned aerial vehicles entering the air route of the unmanned aerial vehicle for delivery in a future period of time according to the delivery task information of other unmanned aerial vehicles in the server.
The target unmanned aerial vehicle can determine the reference unmanned aerial vehicle quantity of the unmanned aerial vehicle air route according to the predicted number of unmanned aerial vehicles which can enter the unmanned aerial vehicle air route in a future period of time and the number of unmanned aerial vehicles already existing in the unmanned aerial vehicle air route, and then determine whether the unmanned aerial vehicle executes a distribution task through the unmanned aerial vehicle air route according to the reference unmanned aerial vehicle quantity and the set interval range.
In this specification, the unmanned aerial vehicle to which the control method of the unmanned aerial vehicle provided in this specification is applied may be used to execute a delivery task in a delivery field, for example, a service scenario in which the unmanned aerial vehicle is used to perform delivery such as express delivery, logistics, and takeout.
S102: and determining the actual state deviation of the target unmanned aerial vehicle and the reference unmanned aerial vehicle in the unmanned aerial vehicle air route according to the current state data of the target unmanned aerial vehicle and the current state data of the reference unmanned aerial vehicle.
In this specification embodiment, the target drone may determine the actual state deviation of the target drone from the reference drone in the drone airline according to its current state data and the current state data of the reference drone. The state data mentioned here may refer to the corresponding position, speed, and acceleration of the drone at each moment. The actual state deviation mentioned here may refer to a difference value of state data of the target drone and state data of the reference drone in the drone lane, such as a position difference value, a speed difference value, an acceleration difference value, and the like between the target drone and the reference drone.
In practical application, the target unmanned aerial vehicle can acquire the current state data of the reference unmanned aerial vehicle through communication connection, and the actual state deviation of the target unmanned aerial vehicle and the reference unmanned aerial vehicle is determined according to the difference value between the current state data of the target unmanned aerial vehicle and the current state data of the reference unmanned aerial vehicle. Target unmanned aerial vehicle and refer to unmanned aerial vehicle and can also upload the state data of self to the server, confirm target unmanned aerial vehicle and the actual state deviation that refers to unmanned aerial vehicle through the server, and the target unmanned aerial vehicle that receives the server and send with the actual state deviation that refers to unmanned aerial vehicle.
S104: and determining control parameters for the target unmanned aerial vehicle according to the actual state deviation and the acquired expected state deviation which enables formation flight between the target unmanned aerial vehicle and the reference unmanned aerial vehicle.
In this specification embodiment, the target drone may determine the control parameters for the target drone according to the actual state deviation and the acquired expected state deviation that enables formation flight between the target drone and the reference drone. The expected state deviation mentioned here may be determined based on a flight interval at which the target unmanned aerial vehicle and the reference unmanned aerial vehicle make formation flight in the unmanned aerial vehicle air route, the flight interval being determined according to a time when the target unmanned aerial vehicle enters the unmanned aerial vehicle air route, and the flight interval may also be a time interval set in advance by a human.
Specifically, because can take notes unmanned aerial vehicle in the unmanned aerial vehicle air route in predetermineeing each moment in the flight trajectory, state data such as position, speed, acceleration that unmanned aerial vehicle corresponds. That is to say, in the unmanned aerial vehicle air route, the position, the speed and the acceleration which the unmanned aerial vehicle is expected to reach at each moment are recorded, so that the target unmanned aerial vehicle can determine the difference value between the state data which the target unmanned aerial vehicle is expected to reach and the state data which the reference unmanned aerial vehicle is expected to reach in the unmanned aerial vehicle air route according to the flight interval between the target unmanned aerial vehicle and the reference unmanned aerial vehicle for formation flight in the unmanned aerial vehicle air route, determine the expected state deviation, and determine the control parameters aiming at the target unmanned aerial vehicle according to the expected state deviation and the actual state deviation.
In practical applications, there may be various methods for the target unmanned aerial vehicle to obtain the takeoff time of the target unmanned aerial vehicle and the reference unmanned aerial vehicle on the unmanned aerial vehicle air route. For another example, the target drone and the reference drone upload the takeoff time to the server, and the server calculates the flight interval and sends the flight interval to the target drone. The method of determining the flight interval is not limited by this description.
In this specification, the target drone may determine a leading drone located in a drone route, where the leading drone provides a reference for determining control parameters of the target drone. The target drone may also select a leading drone from the formation of drones. The method for determining the leading unmanned aerial vehicle by the target unmanned aerial vehicle from the affiliated unmanned aerial vehicle air line or the affiliated unmanned aerial vehicle formation of the target unmanned aerial vehicle can be various, for example, the leading unmanned aerial vehicle is determined by the takeoff time of the acquired reference unmanned aerial vehicle after the server or the communication connection with the reference unmanned aerial vehicle is established. For another example, the unmanned aerial vehicle with the strongest interference resistance is determined from the reference unmanned aerial vehicles to serve as a leading unmanned aerial vehicle, wherein if the unmanned aerial vehicles of which types are determined in advance have stronger interference resistance, the target unmanned aerial vehicle can acquire the unmanned aerial vehicle models of the reference unmanned aerial vehicles through communication connection with the reference unmanned aerial vehicles, and the unmanned aerial vehicle with the strongest interference resistance in the reference unmanned aerial vehicle is judged through the unmanned aerial vehicle models. For another example, the target drone may also determine, according to the identification data of the leading drone sent by the server, a leading drone in the drone formation to which the drone airline or the target drone belongs. The present description does not limit the method of determining the leading drone.
It should be noted that the leading drone may also be a virtual drone that does not actually exist, a position is selected from a drone airline where the target drone is located or a drone formation to which the target drone belongs as the virtual leading drone, and the position, speed, and acceleration of the virtual leading drone may be manually preset.
Further, the target drone may determine reference state data corresponding to the leading drone at the present time, where the reference state data mentioned here is state data of a position, a speed, an acceleration, and the like corresponding to the leading drone at each time of the drone route, which is specified in advance. And finally, determining control parameters for the target unmanned aerial vehicle on the basis of the reference state data according to the actual state deviation and the acquired expected state deviation between the target unmanned aerial vehicle and the reference unmanned aerial vehicle.
Specifically, the target drone may determine the control parameters for the target drone with reference to the following formula:
in this specification embodiment, each unmanned aerial vehicle that is located in the unmanned aerial vehicle air route need refer to other unmanned aerial vehicle's state data in fact to determine its control parameter, so, each unmanned aerial vehicle that unmanned aerial vehicle air route flies all can regard as target unmanned aerial vehicle. In the above formula, therefore, first,
may be used to represent the control parameters of the ith target drone at the current time. For example, the speed of the ith target drone at the current time is determined.
The communication connection completion method can be used for indicating whether the ith target unmanned aerial vehicle and the jth reference unmanned aerial vehicle are in communication connection, the completion communication connection is 1, and the incomplete communication connection is 0.
The method can be used for indicating whether the target unmanned aerial vehicle and the leading unmanned aerial vehicle are in communication connection, the completion communication connection is 1, and the incomplete communication connection is 0.
、
The gain coefficient can be used for representing the gain coefficient, and the change of the control parameter determined by the target unmanned aerial vehicle is ensured to be in accordance with expectation.
Secondly, the first step is to carry out the first,
may be used to represent the current location of the ith target drone in the drone airline.
May be used to represent the current position of the jth reference drone in the drone flight path.
May be used to represent the current position of the leading drone in the drone airline.
May be used to indicate the deviation value to be achieved for the position between the i-th target drone and the j-th reference drone.
May be used to represent the current speed of the ith target drone in the drone flight path.
May be used to represent the current speed of the jth reference drone in the drone flight path.
May be used to represent the current speed of the leading drone in the drone flight path.
Finally, the process is carried out in a batch,
may be used to represent the corresponding status-related item of the leading drone. And the state related items are used for determining reference state data corresponding to the leading unmanned aerial vehicle in the unmanned aerial vehicle air route at each moment. Correspondingly, the target unmanned aerial vehicle can determine the current corresponding reference state data of the leading unmanned aerial vehicle according to the state related items. That is to say that the position of the first electrode,
the function item is changed along with time, the target unmanned aerial vehicle can determine the flight time length of the leading unmanned aerial vehicle in the unmanned aerial vehicle air route according to the current time, and further determine the reference state data corresponding to the leading unmanned aerial vehicle at the current moment according to the flight time length.
As can be seen from the above-mentioned formula,
may be used to represent the difference between the current position of the ith target drone and the current position of the jth reference drone.
The method can be used for determining the distance that the ith target unmanned aerial vehicle needs to be adjusted according to the difference value between the current position of the ith target unmanned aerial vehicle and the current position of the jth reference unmanned aerial vehicle and the expected distance to be spaced between the position of the ith target unmanned aerial vehicle and the position of the jth reference unmanned aerial vehicle. Based on this, the control parameter of the target unmanned aerial vehicle that follow-up was confirmed is that the target unmanned aerial vehicle is expected in fact to fly the back according to control parameter, can keep this expectation distance to a certain extent with between the jth unmanned aerial vehicle of referring to.
The target unmanned aerial vehicle can determine the control parameter of the ith target unmanned aerial vehicle at the current moment on the basis of the reference state data. As shown in fig. 2A and 2B.
Fig. 2A and fig. 2B are schematic views of a flight process of the unmanned aerial vehicle provided in this specification.
In FIG. 2A, drone position
For the position that the target drone a expects to arrive at, it can be seen from fig. 2A that the difference between the current position of the target drone a and the current position of the reference drone is greater than the drone position
The distance spaced from the position of the reference drone, and therefore,
the result of the calculation is a negative number,
the calculated result is a positive number. Similarly, the difference between the current position of the target drone a and the current position of the leading drone is greater than the drone position
The distance from the position of the leading drone, and therefore,
the result of the calculation is a negative number,
the calculated result is positive, that is, in the unmanned aerial vehicle route, the current position of the target unmanned aerial vehicle a does not reach the position that the target unmanned aerial vehicle a expects to reach at the current moment, and therefore, the target unmanned aerial vehicle a needs to be accelerated to reach the position of the unmanned aerial vehicle that expects to reach
。
Wherein the content of the first and second substances,
the speed of the leading unmanned aerial vehicle corresponding to the current moment can be represented, and the target unmanned aerial vehicle can determine the speed of the target unmanned aerial vehicle corresponding to the current moment according to the calculated speed needing to be increased by taking the speed of the leading unmanned aerial vehicle corresponding to the current moment as a reference.
In fig. 2B, the difference between the current position of the target drone a and the current position of the reference drone is smaller than the drone position
The distance spaced from the position of the reference drone, and therefore,
the result of the calculation is a positive number,
the result of the calculation is negative. Similarly, the difference between the current position of the target unmanned aerial vehicle A and the current position of the leading unmanned aerial vehicle is smaller than the position of the unmanned aerial vehicle
The distance from the position of the leading drone, and therefore,
the result of the calculation is a positive number,
the result of the calculation is negative, that is, in the unmanned aerial vehicle route, the current position of the target unmanned aerial vehicle a exceeds the position that the target unmanned aerial vehicle a expects to arrive at the current moment, therefore, the target unmanned aerial vehicle a needs to decelerate to reach the position of the unmanned aerial vehicle that expects to arrive
。
The target unmanned aerial vehicle can determine the speed of the target unmanned aerial vehicle corresponding to the current moment according to the calculated speed needing to be reduced by taking the speed of the leading unmanned aerial vehicle corresponding to the current moment as a reference.
S106: and controlling the target unmanned aerial vehicle according to the control parameters.
In this specification embodiment, target unmanned aerial vehicle can control target unmanned aerial vehicle according to control parameter. The control parameter mentioned here may refer to a specific control amount to be output when the unmanned aerial vehicle controls itself at each time. For example, the unmanned aerial vehicle controls the rotating speed of a propeller. The unmanned aerial vehicle can determine control parameters according to the speed that the target unmanned aerial vehicle will arrive and the current speed, and control the target unmanned aerial vehicle.
In this specification embodiment, if it is determined that the target unmanned aerial vehicle reaches the ravel position of formation flight, the communication connection between the target unmanned aerial vehicle and the reference unmanned aerial vehicle is disconnected, so that the unmanned aerial vehicle located in the unmanned aerial vehicle air route is controlled according to the state data of other unmanned aerial vehicles in the unmanned aerial vehicle air route except the target unmanned aerial vehicle. That is to say, if confirm that target unmanned aerial vehicle arrives the position of separating of formation flight, the unmanned aerial vehicle that is located the unmanned aerial vehicle airline need confirm again with self carry out communication connection's other unmanned aerial vehicles to guarantee this unmanned aerial vehicle's normal flight. The disaggregation position of formation flying mentioned here may refer to a destination to be reached by the formation where the target unmanned aerial vehicle is located, or may refer to a position where the target unmanned aerial vehicle departs from the flight formation by itself before reaching the destination and flies to the destination individually.
According to the method, the affiliated unmanned aerial vehicle air route is determined according to the flight task requirement, the target unmanned aerial vehicle is adjusted according to the state deviation between the target unmanned aerial vehicle and the reference unmanned aerial vehicle in the unmanned aerial vehicle air route, namely, the unmanned aerial vehicle is planned from the state of the formation of the unmanned aerial vehicles flying in the whole unmanned aerial vehicle air route, so that the unmanned aerial vehicle is controlled, redundant calculation for independently planning each aircraft is saved, and the planning efficiency of the unmanned aerial vehicle executing tasks is guaranteed.
The above method for controlling an unmanned aerial vehicle provided by one or more embodiments of this specification is based on the same idea, and this specification further provides a corresponding control device for an unmanned aerial vehicle, as shown in fig. 3.
Fig. 3 is a schematic diagram of a control device of an unmanned aerial vehicle provided in this specification, and specifically includes:
an obtaining module 300, configured to determine an unmanned aerial vehicle route to which a target unmanned aerial vehicle belongs, and determine at least one other unmanned aerial vehicle currently located on the unmanned aerial vehicle route, as a reference unmanned aerial vehicle;
a state determining module 302, configured to determine, according to the current state data of the target drone and the current state data of the reference drone, an actual state deviation of the target drone and the reference drone in the drone airline;
a parameter determining module 304, configured to determine a control parameter for the target drone according to the actual state deviation and the acquired expected state deviation that enables formation flight between the target drone and the reference drone;
and the control module 306 is configured to control the target unmanned aerial vehicle according to the control parameter.
Optionally, the parameter determining module 304 is specifically configured to determine the expected state deviation based on a flight interval of formation flight of the target drone and the reference drone in the drone route, where the flight interval is determined according to a time when the target drone enters the drone route.
Optionally, the obtaining module 300 is specifically configured to determine at least one drone, in the drone airline, that establishes a communication connection with the target drone, as a reference drone.
Optionally, the parameter determining module 304 is specifically configured to determine a leading drone located in the drone airline, determine current corresponding reference state data of the leading drone, and determine a control parameter for the target drone based on the reference state data according to the actual state deviation and the acquired expected state deviation for enabling formation flight between the target drone and the reference drone.
Optionally, the parameter determining module 304 is specifically configured to obtain a state related item corresponding to the leading unmanned aerial vehicle, where the state related item is used to represent reference state data corresponding to the leading unmanned aerial vehicle at each time in the unmanned aerial vehicle airline, and determine the reference state data corresponding to the leading unmanned aerial vehicle at present according to the state related item.
Optionally, the control module 306 is specifically configured to, if it is determined that the target drone reaches a disaggregated position for formation flight, disconnect the communication connection between the target drone and the reference drone, so that the drone located in the drone airline is controlled according to status data of other drones in the drone airline except the target drone.
Optionally, the obtaining module 300 is specifically configured to determine, according to the delivery task corresponding to the target unmanned aerial vehicle, at least one unmanned aerial vehicle route corresponding to the delivery task, as a candidate route, determine, for each candidate route, the number of unmanned aerial vehicles currently located in the candidate route, as the number of unmanned aerial vehicles corresponding to the candidate route, and determine, according to the number of unmanned aerial vehicles corresponding to each candidate route, an unmanned aerial vehicle route to which the target unmanned aerial vehicle belongs.
The present specification also provides a computer-readable storage medium storing a computer program, where the computer program is operable to execute the method for controlling the drone provided in fig. 1.
This specification also provides the schematic structure diagram of the unmanned aerial vehicle device shown in fig. 4. As shown in fig. 4, at the hardware level, the drone device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include hardware required for other services. The processor reads a corresponding computer program from the nonvolatile memory into the memory and then runs the computer program, so as to implement the control method of the drone described in fig. 1. Of course, besides the software implementation, the present specification does not exclude other implementations, such as logic devices or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may be hardware or logic devices.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Hardware Description Language), traffic, pl (core universal Programming Language), HDCal (jhdware Description Language), lang, Lola, HDL, laspam, hardward Description Language (vhr Description Language), vhal (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the various elements may be implemented in the same one or more software and/or hardware implementations of the present description.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an example of the present specification, and is not intended to limit the present specification. Various modifications and alterations to this description will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification should be included in the scope of the claims of the present specification.
Claims (10)
1. A control method of an unmanned aerial vehicle is characterized by comprising the following steps:
determining an unmanned aerial vehicle route to which a target unmanned aerial vehicle belongs, and determining at least one other unmanned aerial vehicle currently located on the unmanned aerial vehicle route as a reference unmanned aerial vehicle;
determining actual state deviation of the target unmanned aerial vehicle and the reference unmanned aerial vehicle in the unmanned aerial vehicle air route according to the current state data of the target unmanned aerial vehicle and the current state data of the reference unmanned aerial vehicle;
determining control parameters for the target unmanned aerial vehicle according to the actual state deviation and the acquired expected state deviation which enables the target unmanned aerial vehicle and the reference unmanned aerial vehicle to carry out formation flight;
and controlling the target unmanned aerial vehicle according to the control parameters.
2. The method of claim 1, wherein the expected state deviation is determined based on a flight interval for the target drone to fly in formation with the reference drone in the drone lane, the flight interval determined from a time the target drone entered the drone lane.
3. The method of claim 1, wherein determining at least one other drone currently located on the drone airline as a reference drone specifically comprises:
determining at least one drone in the drone route that establishes a communication connection with the target drone as a reference drone.
4. The method according to claim 3, wherein determining control parameters for the target drone according to the actual state deviation and the acquired expected state deviation for formation flight between the target drone and the reference drone specifically includes:
determining a leading drone located in the drone airline;
determining current corresponding reference state data of the leading unmanned aerial vehicle;
and determining control parameters for the target unmanned aerial vehicle on the basis of the reference state data according to the actual state deviation and the acquired expected state deviation which enables formation flight between the target unmanned aerial vehicle and the reference unmanned aerial vehicle.
5. The method according to claim 4, wherein determining the current corresponding reference state data of the leading drone specifically includes:
acquiring a state related item corresponding to the leading unmanned aerial vehicle, wherein the state related item is used for representing reference state data corresponding to the leading unmanned aerial vehicle at each moment in the unmanned aerial vehicle air route;
and determining the current corresponding reference state data of the leading unmanned aerial vehicle according to the state related items.
6. The method of claim 3, wherein the method further comprises:
if the target unmanned aerial vehicle reaches the scattered position of formation flight, disconnecting the communication connection between the target unmanned aerial vehicle and the reference unmanned aerial vehicle so that the unmanned aerial vehicle located in the unmanned aerial vehicle air line can control according to the state data of other unmanned aerial vehicles except the target unmanned aerial vehicle in the unmanned aerial vehicle air line.
7. The method of claim 1, wherein determining the drone flight path to which the target drone belongs specifically comprises:
determining at least one unmanned aerial vehicle route corresponding to the delivery task as a candidate route according to the delivery task corresponding to the target unmanned aerial vehicle;
determining the number of unmanned aerial vehicles currently located in the candidate route as the number of unmanned aerial vehicles corresponding to the candidate route for each candidate route;
and determining the unmanned aerial vehicle route to which the target unmanned aerial vehicle belongs according to the number of the unmanned aerial vehicles corresponding to each candidate route.
8. A control device of an unmanned aerial vehicle, comprising:
the acquisition module is used for determining an unmanned aerial vehicle route to which the target unmanned aerial vehicle belongs, and determining at least one other unmanned aerial vehicle currently located on the unmanned aerial vehicle route as a reference unmanned aerial vehicle;
the state determining module is used for determining the actual state deviation of the target unmanned aerial vehicle and the reference unmanned aerial vehicle in the unmanned aerial vehicle air route according to the current state data of the target unmanned aerial vehicle and the current state data of the reference unmanned aerial vehicle;
a parameter determination module, configured to determine a control parameter for the target unmanned aerial vehicle according to the actual state deviation and an acquired expected state deviation that enables formation flight between the target unmanned aerial vehicle and the reference unmanned aerial vehicle;
and the control module is used for controlling the target unmanned aerial vehicle according to the control parameters.
9. A computer-readable storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, implements the method of any of the preceding claims 1 to 7.
10. A drone comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the method of any of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110502881.7A CN112987796B (en) | 2021-05-10 | 2021-05-10 | Unmanned aerial vehicle control method and device, computer readable storage medium and unmanned aerial vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110502881.7A CN112987796B (en) | 2021-05-10 | 2021-05-10 | Unmanned aerial vehicle control method and device, computer readable storage medium and unmanned aerial vehicle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112987796A true CN112987796A (en) | 2021-06-18 |
| CN112987796B CN112987796B (en) | 2021-09-24 |
Family
ID=76337292
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110502881.7A Active CN112987796B (en) | 2021-05-10 | 2021-05-10 | Unmanned aerial vehicle control method and device, computer readable storage medium and unmanned aerial vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112987796B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114384934A (en) * | 2022-01-14 | 2022-04-22 | 中国民用航空总局第二研究所 | Method for acquiring air collision probability of unmanned aerial vehicle |
| CN114384936A (en) * | 2022-01-20 | 2022-04-22 | 天津云圣智能科技有限责任公司 | Unmanned aerial vehicle parameter debugging method and device and server |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101427770B1 (en) * | 2012-05-16 | 2014-08-12 | 전자부품연구원 | Method of dynamic tree topology formation in swarming UAV sensor network |
| CN107121986A (en) * | 2017-05-24 | 2017-09-01 | 浙江大学 | The method that a kind of unmanned plane flight pattern of Behavior-based control is kept |
| CN109407694A (en) * | 2017-08-18 | 2019-03-01 | 清华大学 | Unmanned plane formation control method, readable storage medium storing program for executing, equipment and unmanned plane |
| CN110502032A (en) * | 2019-08-31 | 2019-11-26 | 华南理工大学 | A kind of unmanned plane cluster formation flight method of Behavior-based control control |
| CN111158393A (en) * | 2020-01-09 | 2020-05-15 | 沈阳工业大学 | Unmanned aerial vehicle control method and device, electronic equipment and storage medium |
| CN112585557A (en) * | 2020-04-26 | 2021-03-30 | 深圳市大疆创新科技有限公司 | Method and device for controlling unmanned aerial vehicle and unmanned aerial vehicle |
-
2021
- 2021-05-10 CN CN202110502881.7A patent/CN112987796B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101427770B1 (en) * | 2012-05-16 | 2014-08-12 | 전자부품연구원 | Method of dynamic tree topology formation in swarming UAV sensor network |
| CN107121986A (en) * | 2017-05-24 | 2017-09-01 | 浙江大学 | The method that a kind of unmanned plane flight pattern of Behavior-based control is kept |
| CN109407694A (en) * | 2017-08-18 | 2019-03-01 | 清华大学 | Unmanned plane formation control method, readable storage medium storing program for executing, equipment and unmanned plane |
| CN110502032A (en) * | 2019-08-31 | 2019-11-26 | 华南理工大学 | A kind of unmanned plane cluster formation flight method of Behavior-based control control |
| CN111158393A (en) * | 2020-01-09 | 2020-05-15 | 沈阳工业大学 | Unmanned aerial vehicle control method and device, electronic equipment and storage medium |
| CN112585557A (en) * | 2020-04-26 | 2021-03-30 | 深圳市大疆创新科技有限公司 | Method and device for controlling unmanned aerial vehicle and unmanned aerial vehicle |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114384934A (en) * | 2022-01-14 | 2022-04-22 | 中国民用航空总局第二研究所 | Method for acquiring air collision probability of unmanned aerial vehicle |
| CN114384936A (en) * | 2022-01-20 | 2022-04-22 | 天津云圣智能科技有限责任公司 | Unmanned aerial vehicle parameter debugging method and device and server |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112987796B (en) | 2021-09-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112987796B (en) | Unmanned aerial vehicle control method and device, computer readable storage medium and unmanned aerial vehicle | |
| CN111665844B (en) | Path planning method and device | |
| CN112766468B (en) | Trajectory prediction method and device, storage medium and electronic equipment | |
| CN111208838B (en) | Control method and device of unmanned equipment | |
| CN107735737B (en) | Waypoint editing method, device, equipment and aircraft | |
| CN112629550B (en) | Method and device for predicting obstacle track and model training | |
| CN111522245B (en) | Method and device for controlling unmanned equipment | |
| CN112346467B (en) | Control method and device of unmanned equipment | |
| CN112013853B (en) | Method and device for verifying track points of unmanned equipment | |
| CN112033421A (en) | Method and device for detecting lane in electronic map | |
| CN114581167A (en) | Service abnormity identification method and device, storage medium and electronic equipment | |
| CN113031641B (en) | Unmanned aerial vehicle control method and device, storage medium and unmanned aerial vehicle | |
| CN113064439B (en) | Method and device for controlling unmanned equipment and setting hinge | |
| CN112731957B (en) | Unmanned aerial vehicle control method and device, computer readable storage medium and unmanned aerial vehicle | |
| CN113296544A (en) | Unmanned aerial vehicle return path planning method, unmanned aerial vehicle, electronic device and computer-readable storage medium | |
| CN113848913B (en) | Control method and control device of unmanned equipment | |
| CN112987754B (en) | Unmanned equipment control method and device, storage medium and electronic equipment | |
| CN113031656B (en) | Unmanned aerial vehicle control method and device | |
| CN113298445B (en) | Method and device for model training and unmanned equipment scheduling | |
| CN116300842A (en) | Unmanned equipment control method and device, storage medium and electronic equipment | |
| CN114280960A (en) | Automatic driving simulation method and device, storage medium and electronic equipment | |
| CN113886119A (en) | Fault repairing method and device | |
| JP2020087145A (en) | Computer system and program | |
| CN113486452B (en) | Method and device for remotely controlling unmanned equipment | |
| CN113673034A (en) | Unmanned aerial vehicle state prediction method and device, storage medium and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20211201 Address after: 100080 2106-030, 9 North Fourth Ring Road, Haidian District, Beijing. Patentee after: BEIJING SANKUAI ONLINE TECHNOLOGY Co.,Ltd. Patentee after: Meituan Technology Co., Ltd Address before: 100080 2106-030, 9 North Fourth Ring Road, Haidian District, Beijing. Patentee before: BEIJING SANKUAI ONLINE TECHNOLOGY Co.,Ltd. |
|
| TR01 | Transfer of patent right |