CN111404746A - Task optimization method and device - Google Patents
Task optimization method and device Download PDFInfo
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- CN111404746A CN111404746A CN202010178130.XA CN202010178130A CN111404746A CN 111404746 A CN111404746 A CN 111404746A CN 202010178130 A CN202010178130 A CN 202010178130A CN 111404746 A CN111404746 A CN 111404746A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0654—Management of faults, events, alarms or notifications using network fault recovery
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/18502—Airborne stations
- H04B7/18506—Communications with or from aircraft, i.e. aeronautical mobile service
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
Abstract
One embodiment disclosed in the present specification provides a method for task optimization, which includes setting a residual task amount and a residual task starting point by a task optimization starting node; the starting node broadcasts an assistance request to at least one target node of the task optimization, wherein the assistance request comprises the residual task amount and a residual task starting point; the initiating node reassigns the remaining task amount to at most one of the at least one target node in response to a task optimization request by the at most one consent node for the broadcasted assistance request; at most one of the consent nodes moves towards the remaining task start point after the scheduled time.
Description
Technical Field
The invention belongs to the technical field and the intelligent field of computers, and particularly relates to a method and a device for task optimization and a method for task optimization of an unmanned aerial vehicle.
Background
The conventional working principle of the unmanned aerial vehicle is that the server plans the operation path of the unmanned aerial vehicle and assigns an operation task to the unmanned aerial vehicle, the server knows the map of required operation, the current position and the operation capacity of each unmanned aerial vehicle, and the task is formulated for each unmanned aerial vehicle based on the map, but in the actual operation process, because of various internal and external factors, not every unmanned aerial vehicle can smoothly complete the task, and the communication between the unmanned aerial vehicle and the server is interrupted, for example, when the server breaks down, the unmanned aerial vehicle group can not obtain a new assignment instruction, and the whole operation task can not be completed.
Disclosure of Invention
In order to address the above situation, the present invention provides a method for task optimization, comprising:
the task node receives the task information from the server,
setting a residual task amount and a residual task starting point by a starting node of task optimization under the condition that communication with a server is interrupted;
the starting node broadcasts an assistance request to at least one target node of the task optimization, wherein the assistance request comprises the residual task amount and a residual task starting point;
the initiating node reassigns the remaining task amount to at most one of the at least one target node in response to a task optimization request by the at most one consent node for the broadcasted assistance request;
the at most one consent node moves towards the remaining task start point after the scheduled time.
Further, the task nodes receive task information from the server, and the server not only sends task information required to be completed to each task node, but also copies the task information of all other task nodes to each task node in a copy form.
Correspondingly, the invention also provides a device applying the method, which comprises the following steps:
the first transmission unit is used for receiving the task information from the server;
the storage unit is used for locally storing the task information;
the setting unit is used for setting the residual task amount and the residual task starting point of the starting node of the task optimization;
a second transmission unit, configured to broadcast an assistance request to at least one target node for task optimization, where the assistance request includes the remaining task amount and a remaining task starting point;
a reallocation unit for reallocating the remaining task amount to at most one of the at least one target node in response to a task optimization request of the at most one consent node for the broadcasted assistance request;
an execution unit for the at most one consent node to perform an action to move to the remaining task start point after a scheduled time.
The invention has the beneficial effects that: when the communication between the unmanned aerial vehicle and the server is interrupted, for example, when the server fails, even if a new assignment instruction cannot be directly obtained from the server, the whole operation task can be completed as much as possible through self-coordination among clusters, and the task completion degree is improved.
Drawings
FIG. 1 shows a flow chart of a method according to the invention;
fig. 2-3 show a block diagram of a drone to which the method is applied in one embodiment.
Detailed Description
The flow of the present invention and the functions realized are described in detail below with reference to the accompanying drawings.
Example one
In this embodiment, each task node to which the method is applied is an unmanned aerial vehicle, and in the initial stage of the task, the server plans the operation path of the unmanned aerial vehicle and assigns an operation task to the unmanned aerial vehicle. The server knows the map of the required operation, the current position and the operation capacity of each unmanned aerial vehicle, and formulates a task for each unmanned aerial vehicle based on the map of the required operation, the current position and the operation capacity. The server not only sends the task information required to be completed to each task node, but also copies the task information of all other task nodes to each task node in a copy mode.
In the task execution process, the unmanned aerial vehicle periodically communicates with the server at fixed time intervals, and when the unmanned aerial vehicle cannot obtain feedback of the server, namely under the condition that the communication between the unmanned aerial vehicle and the server is interrupted, the initial unmanned aerial vehicle for task optimization sets a residual task amount and a residual task starting point according to a first condition; the first condition is, for example, comparing the self state of the unmanned aerial vehicle, such as the battery power or the power failure rate, predicting the task amount and the operation intermediate point which can be completed by the unmanned aerial vehicle in combination with the virtual task map and the planned path on the map, setting the residual task amount based on the initially assigned task amount and the predicted task amount which can be completed, and setting the residual task starting point, namely the operation intermediate point, on the virtual task map.
The initiating drone broadcasts an assistance request to at least one target drone for the task optimization, the assistance request including the remaining task amount and a remaining task starting point;
after receiving the broadcast, at least one target unmanned aerial vehicle compares its own parameters and task amount according to a second condition severer than the first condition, and the own parameters, such as battery power, not only can meet the original task amount of the target unmanned aerial vehicle, but also can meet the residual task amount, and if the target unmanned aerial vehicle meeting the second condition does not exist, assistance cannot be provided for the starting unmanned aerial vehicle naturally; if more than one target unmanned aerial vehicle meeting the second condition exists, screening at most one target unmanned aerial vehicle meeting a third condition, including but not limited to distance and the like, from task information stored in the target unmanned aerial vehicle;
the granting drone feeds back information of its granting assistance to the initiating drone, which reallocates the remaining task volume to at most one of the at least one target drone in response to a task optimization request by the at most one granting drone for the remaining task volume that was broadcast;
the at most one agreeing drone moves to the remaining task starting point after completing its intended task.
Example two
In this embodiment, each node to which the method is applied is a lawn punching unmanned aerial vehicle. After the lawn is built, in addition to reasonable maintenance management such as fertilization, irrigation and trimming, the lawn needs to be timely perforated to form a channel for water to enter soil and create conditions for oxygen to enter, so that the physical properties and other characteristics of the lawn are improved, and the overground and underground parts of the lawn are promoted to grow. The unmanned aerial vehicle is designed for automatically and intelligently implementing the operation. At the beginning of lawn punching, the server plans the operation path of the lawn punching unmanned aerial vehicle and assigns an operation task to the unmanned aerial vehicle. The server knows the map of the required operation, the current position and the operation capacity of each unmanned aerial vehicle, and formulates a task for each unmanned aerial vehicle based on the map of the required operation, the current position and the operation capacity. The server not only sends the task information required to be completed to each task node, but also copies the task information of all other task nodes to each task node in a copy mode.
The lawn punching unmanned aerial vehicle comprises a frame, a first nail roller serving as a main implementation part of punching operation, two second nail rollers serving as a running part and a punching operation auxiliary implementation part, and a power part and a control part (not shown) which are installed on the frame. According to the working process of the unmanned aerial vehicle, components for determining the current position of the unmanned aerial vehicle, such as a GPS positioning device, are also an indispensable part of the control component, in addition, obstacle avoidance systems commonly used in the field, such as infrared sensors, ultrasonic sensors and other sensors, can also be added into the control component to perfect the function of the lawn punching unmanned aerial vehicle,
as shown in figure 2 of the drawings, in which,
the first nail roller 1 is rotatably arranged on the roller frame 4 and is fixed at the front end of the frame 3 through the roller frame 4;
two second nail rollers 2 mounted side by side at the rear end of the frame 3;
the two driving motors 5 are arranged at the middle section of the rack and respectively drive the two second nail rollers 2 to rotate through transmission chains (including but not limited to chain transmission, belt transmission and the like), so that the intelligent unmanned aerial vehicle is driven to advance and/or turn;
and the driving battery 6 is fixed on the frame and used for supplying power to the driving motor 5.
A plurality of lawn punching nails are uniformly welded on the outer surfaces of the first nail roller 1 and the second nail roller 2.
As shown in fig. 3, the first spike roller 1 has a symmetrically arranged fixing plate 11 (only one is shown in the figure for showing the internal structure), an eccentric wheel shaft 12 penetrating the inside of the first spike roller 1 is mounted at the center of the fixing plate through a bearing, a pair of eccentric wheels 13 are fixed on the eccentric wheel shaft, and the ends of the eccentric wheel shaft 12 are respectively mounted on the roller frame 4.
In the embodiment, an excitation motor 7 is installed on the frame 3 and is in transmission connection with the eccentric wheel shaft 12, and the excitation motor 7 is controlled by the driving battery 6 to supply power, so as to drive the eccentric wheel 13 to rotate, so that the first nail roller 1 is excited and vibrated, the ground pressure is increased, and the punching effect is improved.
The rack-mounted control unit includes:
the first transmission unit is used for receiving the task information from the server and periodically communicating with the server at fixed time intervals;
the storage unit is used for locally storing the task information;
the setting unit is used for setting the residual task quantity and the residual task starting point, pre-judging the task quantity which can be completed and the operation middle stop point (the length of the path can be used for approximately replacing the task quantity to simplify pre-judging calculation) by combining a lawn map and a planned path on the lawn map based on the comparison of task information and self parameters, such as battery power or power failure rate, then setting the residual task quantity based on the initially assigned task quantity and the pre-judged task quantity which can be completed, and setting the residual task starting point on the lawn map, namely the operation middle stop point.
The second transmission unit starts the second transmission unit of the unmanned aerial vehicle to broadcast an assistance request to all other unmanned aerial vehicles in a communication range under the condition that the pre-judgment result of the setting unit of the second transmission unit is 'incomplete' (namely the residual task amount is not zero), wherein the assistance request comprises the residual task amount and a residual task starting point; in addition, the second transmission unit also has a function of receiving an assistance request of the other unmanned aerial vehicle when the unmanned aerial vehicle is the identity of the target node;
after the at least one target unmanned aerial vehicle receives the broadcast, the setting unit of the target unmanned aerial vehicle compares the self parameter and the task amount according to a second condition which is severer than the first condition, wherein the self parameter, such as the battery power, not only can meet the original task amount of the self parameter, but also can meet the residual task amount, and if the target unmanned aerial vehicle meeting the second condition does not exist, the setting unit of the target unmanned aerial vehicle cannot provide assistance for the starting unmanned aerial vehicle naturally;
if more than one target unmanned aerial vehicle meeting the second condition exists, each target unmanned aerial vehicle performs secondary screening according to locally stored task information, for example, the distance between the residual task starting point and the task completion point of the target unmanned aerial vehicle is compared with the distance between the residual task starting point and the task completion point of the target unmanned aerial vehicle, whether the target unmanned aerial vehicle is the nearest one from the residual task starting point is judged, and if the target unmanned aerial vehicle is the nearest one from the residual task starting point, the target unmanned aerial vehicle is used as the unmanned aerial vehicle to allow the target unmanned aerial vehicle to feed back to the starting unmanned;
the second transmission unit of the unmanned aerial vehicle gives feedback to the starting unmanned aerial vehicle of a task optimization request for assisting the starting unmanned aerial vehicle;
a reassignment unit to which a reassignment unit of an originating drone transfers the remaining task volume in response to the at most one task optimization request that agrees to the remaining task volume broadcast by the drone;
the storage unit of the unmanned aerial vehicle is permitted to update the originally stored task data, the newly transferred residual task amount is stored as the task to be executed by the unmanned aerial vehicle, and the unmanned aerial vehicle is permitted to execute the action of moving to the residual task starting point by the control component after the scheduled time.
It will be appreciated by persons skilled in the art that numerous variations and/or modifications may be made to the invention as shown in the specific embodiments without departing from the spirit or scope of the invention as broadly described. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive. Likewise, the invention encompasses any combination of features, in particular of features in the patent claims, even if this feature or this combination of features is not explicitly specified in the patent claims or in the individual embodiments herein.
Claims (5)
1. A method of task optimization, comprising:
the task node receives the task information from the server,
setting a residual task amount and a residual task starting point by a starting node of task optimization under the condition that communication with a server is interrupted;
the starting node broadcasts an assistance request to at least one target node of the task optimization, wherein the assistance request comprises the residual task amount and a residual task starting point;
the initiating node reassigns the remaining task amount to at most one of the at least one target node in response to a task optimization request by the at most one consent node for the broadcasted assistance request.
The at most one consent node moves towards the remaining task start point after the scheduled time.
2. The method of claim 1, wherein the task nodes receive task information from a server, and the server not only sends task information required to be completed by the server to each task node, but also copies the task information of all other task nodes to each task node in a copy form.
3. An apparatus for task optimization, comprising:
the first transmission unit is used for receiving the task information from the server;
the storage unit is used for locally storing the task information;
the setting unit is used for setting the residual task amount and the residual task starting point of the starting node of the task optimization;
a second transmission unit, configured to broadcast an assistance request to at least one target node for task optimization, where the assistance request includes the remaining task amount and a remaining task starting point;
a reallocation unit for reallocating the remaining task amount to at most one of the at least one target node in response to a task optimization request of the at most one consent node for the broadcasted assistance request;
an execution unit for the at most one consent node to perform an action to move to the remaining task start point after a scheduled time.
4. The apparatus according to claim 3, wherein the task information includes not only task information that each task node needs to complete itself, but also task information of all other drones stored in a copy form.
5. A method of task optimization for a drone, comprising:
receiving task information from a server;
the starting unmanned aerial vehicle for task optimization sets a residual task amount and a residual task starting point according to a first condition;
the initiating drone broadcasts an assistance request to at least one target drone for the task optimization, the assistance request including the remaining task amount and a remaining task starting point;
the initiating drone, in response to a task optimization request by at most one of the at least one target drone for the broadcasted assistance request, reallocate the remaining task amount to the at most one granting drone;
the at most one agreeing drone moves to the remaining task starting point after completing its intended task.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010178130.XA CN111404746A (en) | 2020-03-14 | 2020-03-14 | Task optimization method and device |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202010178130.XA CN111404746A (en) | 2020-03-14 | 2020-03-14 | Task optimization method and device |
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| CN111404746A true CN111404746A (en) | 2020-07-10 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113635302A (en) * | 2021-07-29 | 2021-11-12 | 深圳墨影科技有限公司 | Integrated mobile cooperative robot control system based on field bus |
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| CN104320484A (en) * | 2014-11-05 | 2015-01-28 | 河海大学常州校区 | Task immigration method in wireless sensor network based on integral incentive mechanism |
| CN104950673A (en) * | 2015-06-11 | 2015-09-30 | 昆明理工大学 | Method for distributing targets cooperatively attacked by unmanned aerial vehicle group |
| CN105867415A (en) * | 2016-04-20 | 2016-08-17 | 沈阳航空航天大学 | Cooperative control policy based on secure communication of multiple unmanned aerial vehicles |
| US20170057081A1 (en) * | 2015-08-26 | 2017-03-02 | Airbus Operations Gmbh | Modular robot assembly kit, swarm of modularized robots and method of fulfilling tasks by a swarm of modularized robot |
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2020
- 2020-03-14 CN CN202010178130.XA patent/CN111404746A/en not_active Withdrawn
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103279129A (en) * | 2013-04-24 | 2013-09-04 | 清华大学 | Quantum control method and system of visual navigation of unmanned aerial vehicle group |
| CN104320484A (en) * | 2014-11-05 | 2015-01-28 | 河海大学常州校区 | Task immigration method in wireless sensor network based on integral incentive mechanism |
| CN104950673A (en) * | 2015-06-11 | 2015-09-30 | 昆明理工大学 | Method for distributing targets cooperatively attacked by unmanned aerial vehicle group |
| US20170057081A1 (en) * | 2015-08-26 | 2017-03-02 | Airbus Operations Gmbh | Modular robot assembly kit, swarm of modularized robots and method of fulfilling tasks by a swarm of modularized robot |
| CN105867415A (en) * | 2016-04-20 | 2016-08-17 | 沈阳航空航天大学 | Cooperative control policy based on secure communication of multiple unmanned aerial vehicles |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113635302A (en) * | 2021-07-29 | 2021-11-12 | 深圳墨影科技有限公司 | Integrated mobile cooperative robot control system based on field bus |
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