CN111439382A - Intelligent combined unmanned aerial vehicle system - Google Patents
Intelligent combined unmanned aerial vehicle system Download PDFInfo
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- CN111439382A CN111439382A CN202010288926.0A CN202010288926A CN111439382A CN 111439382 A CN111439382 A CN 111439382A CN 202010288926 A CN202010288926 A CN 202010288926A CN 111439382 A CN111439382 A CN 111439382A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64C—AEROPLANES; HELICOPTERS
- B64C39/00—Aircraft not otherwise provided for
- B64C39/02—Aircraft not otherwise provided for characterised by special use
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
- B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
- B60L58/12—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to state of charge [SoC]
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64D—EQUIPMENT FOR FITTING IN OR TO AIRCRAFT; FLIGHT SUITS; PARACHUTES; ARRANGEMENTS OR MOUNTING OF POWER PLANTS OR PROPULSION TRANSMISSIONS IN AIRCRAFT
- B64D27/00—Arrangement or mounting of power plant in aircraft; Aircraft characterised thereby
- B64D27/02—Aircraft characterised by the type or position of power plant
- B64D27/24—Aircraft characterised by the type or position of power plant using steam, electricity, or spring force
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
- B64U50/00—Propulsion; Power supply
- B64U50/10—Propulsion
- B64U50/19—Propulsion using electrically powered motors
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L2200/00—Type of vehicles
- B60L2200/10—Air crafts
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
- B64U2101/00—UAVs specially adapted for particular uses or applications
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/16—Information or communication technologies improving the operation of electric vehicles
Abstract
The embodiment of the invention provides an intelligent combined unmanned aerial vehicle system which is characterized in that the system can be combined and separated in the air, has the task perception and scene understanding capacity, and comprises an unmanned aerial vehicle whole machine, an energy distribution module, a magnetic connection module, a cluster control and networking module and a communication reconstruction and cooperation module; the whole unmanned aerial vehicle comprises a long unmanned aerial vehicle and at least one sub unmanned aerial vehicle; the long unmanned aerial vehicle and the at least one sub unmanned aerial vehicle cooperate to complete a task according to a task perception and scene understanding algorithm through an energy distribution module, a magnetic connection module, a cluster control and networking module and a communication reconstruction and cooperation module.
Description
Technical Field
The invention belongs to the technical field of artificial intelligence, and relates to an intelligent combined unmanned aerial vehicle system.
Background
At present, the development of unmanned aerial vehicles is in a state of white heat, with the progress of key technologies such as communication, ad hoc network, sensors, navigation positioning, cloud computing, internet of things, big data and artificial intelligence, the idea that a large number of unmanned equipment forms an organic whole is becoming reality, the application of the intelligent technology can obviously improve the capability of an unmanned system, the unmanned system is a development direction of the unmanned system, the unmanned system is developed towards the direction of high autonomous level, and the posture of subversive technology causes high attention of all countries in the world.
The higher the autonomous control level of the unmanned aerial vehicle is, the stronger the capability of the unmanned aerial vehicle to autonomously complete tasks is. The development trend of the unmanned aerial vehicle is from remote control guidance to complete autonomous evolution, from individual autonomy to group complete autonomous development, and from individual attribute of the dummy to social attribute of the dummy. The unmanned aerial vehicle develops towards a multi-platform coordinated cooperation task, a knowledge engineering task, a cognitive task, a cluster cognitive task and a completely autonomous task.
At present, the development of the combined unmanned aerial vehicle emphasizes on the mechanical structure of a single unmanned aerial vehicle, and the interfaces of parts of the unmanned aerial vehicle are standardized so as to meet the requirements of flexible disassembly, quick assembly, convenient carrying and the like, but the method only considers the mechanical structure and has limited application scenes in the field of unmanned aerial vehicles.
BAE systems in the uk are studying unmanned aerial vehicle compounding technology and are currently in the conceptual phase, planned for 2040 years of use on military or civilian aircraft. In China, the combined unmanned aerial vehicle is still a blank, no scientific research institution is available to research the unmanned aerial vehicle, and the combined unmanned aerial vehicle has unique innovation and advancement.
Disclosure of Invention
The invention aims to provide an intelligent combined unmanned aerial vehicle system which is characterized in that the system can be combined and separated in the air, has the task perception and scene understanding capability and comprises an unmanned aerial vehicle whole machine, an energy distribution module, a magnetic connection module, a cluster control and networking module and a communication reconstruction and cooperation module; wherein the content of the first and second substances,
the whole unmanned aerial vehicle comprises a long unmanned aerial vehicle and at least one sub unmanned aerial vehicle; the long unmanned aerial vehicle and at least one sub unmanned aerial vehicle realize cooperative coordination to complete tasks according to task perception and scene understanding algorithms through an energy distribution module, a magnetic coupling module, a cluster control and networking module and a communication reconstruction and cooperation module;
the energy distribution module is used for realizing optimal configuration of energy resources according to the condition of distributed power supplies carried by each unmanned aerial vehicle;
the magnetic coupling module is used for realizing air separation and combination of all the sub unmanned aerial vehicles according to the technical parameters and task parameters preset by the unmanned aerial vehicles and the conditions of lifting balance, pushing balance and energy balance;
the cluster control and networking module is used for performing alliance division on the sub-unmanned aerial vehicle clusters and determining the number of the sub-unmanned aerial vehicles communicating with the long plane; and formation self-repairing when the sub unmanned aerial vehicle is damaged;
the communication reconstruction and cooperation module is used for reconstructing and cooperating communication resources of the unmanned aerial vehicle aiming at the communication module and the communication function of the unmanned aerial vehicle in the combined unmanned aerial vehicle so as to realize multiplexing gain or space diversity gain of communication.
The task and scene planning algorithm models the tasks and scenes according to different working environments faced by the unmanned aerial vehicle, designs different strategy pools, and establishes corresponding strategy libraries; and when the unmanned aerial vehicle joint task is executed, calling a corresponding execution program from the corresponding strategy pool.
Preferably, the task and scenario planning algorithm further includes: the input data are preprocessed by a preprocessing unit, a feature extraction unit and a classification decision unit; wherein the content of the first and second substances,
the input data preprocessing unit is used for preprocessing the input data to enable the processed wireless signals to become the part of processing operation of the input of the classification algorithm; mapping from a signal space to an observation space, the process mainly comprises: correlation, filtering and power normalization of signals;
the feature extraction unit is used for extracting features, and mapping from an observation space with higher dimensionality to a feature space with lower dimensionality to extract time domain features, transform domain features and various statistic parameters of a received signal; the time domain features include histograms or other statistical parameters of the amplitude, phase of the signal; the transform domain characteristics comprise a power spectrum, a spectrum correlation function, time frequency distribution and other statistical parameters;
and the classification decision unit is used for performing classification decision, inputting the extracted characteristic parameters into the designed classifier and identifying the corresponding scene category.
Preferably, the classification decision unit comprises a learning training subunit, configured to perform learning training to find an appropriate decision rule through a known sample; and the identification subunit is used for designing a classifier by using the rules obtained by training to realize the identification of the unknown scene type.
Preferably, the energy distribution module comprises an electric quantity information acquisition unit, a screening unit and a control unit; wherein the content of the first and second substances,
the electric quantity information acquisition unit is used for acquiring electric quantity information of a main load and all unmanned aerial vehicle battery units when the unmanned aerial vehicle is combined;
the screening unit is used for screening any unmanned aerial vehicle battery unit with electric quantity information meeting the requirements from other battery units as a second power supply unit when the electric quantity information of one unmanned aerial vehicle battery unit does not meet the preset conditions, and the rest can be done in the same way;
the control unit is used for judging and respectively outputting a control instruction to the battery unit and the switch unit of each sub-unmanned aerial vehicle, and when the electric energy reserve of a certain sub-unmanned aerial vehicle is insufficient, the electric energy is coordinated through distributed energy control, and the whole cruising of the combined unmanned aerial vehicle is ensured.
Preferably, the magnetic coupling module comprises a mechanical structure unit, a current unit and a data unit; wherein the content of the first and second substances,
the mechanical structure unit is used for separating and combining the unmanned aerial vehicle, and conducting current and data, comprises an upper interface and a lower interface which are of concave-convex structures respectively, wherein the concave part of the upper interface is combined with the convex part of the lower interface to form a conducting area of the current and the data, and the convex part of the upper interface corresponds to the concave part of the lower interface to form a magnetic area.
The current unit is used for controlling the current direction to overturn magnetism, so that the functions of attraction and repulsion between the sub unmanned aerial vehicles are realized.
The data unit is used for transmitting data among the sub-unmanned aerial vehicles, and is convenient for the whole remote measurement control and data transmission of the combined unmanned aerial vehicle.
Preferably, the cluster control and networking module includes: a virtual alliance unit and a virtual long machine unit; wherein the content of the first and second substances,
the virtual alliance unit is used for designing a local communication mode based on a virtual alliance, when the distance between sub-networks in the cluster is larger than the communication radius, the network is called as an independent virtual alliance, one unmanned aerial vehicle in the virtual alliance unit is a navigation information unmanned aerial vehicle, and the other unmanned aerial vehicles are non-navigation information unmanned aerial vehicles.
The virtual long machine unit is used for communicating with the navigation information unmanned aerial vehicle in the virtual alliance, and other unmanned aerial vehicles in the virtual alliance indirectly acquire the information of the virtual long machine through communicating with the navigation information unmanned aerial vehicle, so that each unmanned aerial vehicle at any moment can directly or indirectly acquire the information of the virtual long machine.
When the communication degree of the sub unmanned aerial vehicle cluster is continuously increased, the number of the virtual alliances is continuously reduced, and the number of the unmanned aerial vehicles for obtaining the virtual long-distance machine information is also continuously reduced; when the whole cluster is communicated again, only one unmanned aerial vehicle is needed to obtain the information of the virtual long machine, the connectivity and the stability of the cluster can be ensured, and the communication resource of the system can be saved.
Preferably, the communication reconfiguration and cooperation module comprises: the device comprises a communication resource reconstruction unit and a multi-point cooperation intelligent communication unit.
The communication resource reconstruction unit is used for realizing multiplexing gain or space diversity gain of communication, and in the combined unmanned aerial vehicle, as each unmanned aerial vehicle possibly has a basic communication module and a communication function, the communication resource reconstruction unit can reconstruct and collaborate the communication resources.
The multi-point cooperative intelligent communication unit is used for adaptively and dynamically reconstructing and configuring communication resources according to the scene and the requirement of a work task and the execution stage of the task.
The invention has the beneficial effects that:
the combined unmanned aerial vehicle is formed by cooperatively sharing, distributing and grouping information resources by a plurality of sub-aircrafts, cooperative cooperation among the plurality of aircrafts is realized through a control system, complex tasks are jointly completed, and the purposes of saving energy efficiency and enhancing endurance are achieved through combination and decomposition.
The combined drone can achieve the purpose through autonomous behavior. Humanoid and even superman inorganic life forms in the aspects of perception, interaction, information processing, decision control, learning and execution capabilities, similar to science fiction future unmanned systems. The unmanned aerial vehicle cooperative work is combined, the task types are expanded, and the operation capability under the complex confrontation environment is enhanced.
This kind of novel combination unmanned aerial vehicle has created the unmanned aerial vehicle agent that has ultimate adaptability, possesses task perception, intelligent scene understanding, cluster control, fuses multiple high and new technologies such as communication and overlength continuation of the journey, can be according to task demand fast decomposition for many shelves of unmanned aerial vehicle to be suitable for multiple application scene.
Drawings
FIG. 1 is a functional diagram of an intelligent combined unmanned aerial vehicle according to the present invention;
FIG. 2 is a block diagram of an intelligent combined unmanned aerial vehicle system of the present invention;
FIG. 3 is a schematic diagram of a virtual farm machine according to the present invention;
fig. 4 is a schematic diagram of reconfigurable communication according to the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The novel intelligent combined unmanned aerial vehicle is a flexible aircraft system, a plurality of sub unmanned aerial vehicles are combined into a whole large unmanned aerial vehicle, and each unmanned aerial vehicle customizes the task load according to the application requirement; when the combined unmanned aerial vehicle flies integrally, when a target is reached, the sub unmanned aerial vehicle is separated, various tasks such as image acquisition, airdrop materials, relay communication and ultra-long endurance are executed, and the combined unmanned aerial vehicle returns in cooperation when the task is finished. As shown in fig. 1.
The magnetic coupling technology for separating and combining each sub unmanned aerial vehicle in the combined unmanned aerial vehicle in the air is adopted, the magnetic field is changed by controlling the current direction, the combining and separating functions among the combined unmanned aerial vehicles are realized, and the accident of mutual collision during air flight is avoided; the position of each sub-unmanned aerial vehicle is determined by using a GPS or Beidou navigation and positioning system, and ordered flight in the air is realized through a path planning function, so that work tasks are executed efficiently. The method adopts a machine learning technology, senses the tasks to be executed by the combined unmanned aerial vehicle, identifies malicious or non-malicious interference in the environment, understands communication scenes, designs various efficient coping strategy pools according to different application tasks, and flexibly executes various tasks such as image acquisition, airdrop materials, relay communication, ultra-long endurance and the like.
By adopting a long-machine virtual technology and researching and combining an intelligent cluster control technology in the unmanned aerial vehicle, the problem of cluster formation control under a switching topological structure is solved. When the network topology structure is changed due to formation change or partial communication network faults, the sub-unmanned aerial vehicle cluster is subjected to alliance division by using a distance as a principle, and the number of sub-unmanned aerial vehicles communicating with the virtual long machine is flexibly determined, as shown in fig. 3. When the virtual long machine breaks down, the system can take the backup candidate long machine as a new long machine, so that the destroy resistance of the machine set is achieved. Based on combination unmanned aerial vehicle formation, research is based on virtual center's wireless networking technique. By adopting the virtual center technology, the entity functions of communication, control, calculation, storage and the like can be separated, and multiple backups can be flexibly realized, so that the advantages of flexible communication structure and high robustness are realized. Based on task perception and scene understanding, optimal configuration of unit formation is achieved, and therefore the requirements of tasks are met.
Through the balanced design technology of energy and weight, the best weight of solar photovoltaic and high-energy density batteries in the combined unmanned aerial vehicle is researched to prolong the cruising ability of the combined unmanned aerial vehicle in flight. By utilizing distributed power supplies carried by all the sub unmanned aerial vehicles, a multi-power-supply current sharing technology based on task requirements and scene understanding is researched to realize optimal configuration of energy resources, so that the effects of saving energy and increasing voyage are achieved, and the requirements of all tasks are met; by adopting the technology, when any unmanned aerial vehicle power supply system in the combined unmanned aerial vehicle fails, other unmanned aerial vehicles can be connected for power supply.
Based on the communication resource reconstruction and the multi-point cooperative communication technology of the combined unmanned aerial vehicle. In a combined drone, each drone has a basic communication module and communication function, and these communication resources can be reconstructed and co-processed to realize multiplexing of communication resources or to improve space diversity gain, as shown in fig. 4. And based on task perception and scene understanding, optimal configuration of communication resources is realized, so that the working requirement is met.
The invention discloses an intelligent combined unmanned aerial vehicle system which is characterized in that the system can be combined and separated in the air, has task perception and scene understanding capacity, and comprises an unmanned aerial vehicle whole machine, an energy distribution module, a magnetic connection module, a cluster control and networking module and a communication reconstruction and cooperation module; wherein the content of the first and second substances,
the whole unmanned aerial vehicle comprises a long unmanned aerial vehicle and at least one sub unmanned aerial vehicle; the long unmanned aerial vehicle and at least one sub unmanned aerial vehicle realize cooperative coordination to complete tasks according to task perception and scene understanding algorithms through an energy distribution module, a magnetic coupling module, a cluster control and networking module and a communication reconstruction and cooperation module;
the energy distribution module is used for realizing optimal configuration of energy resources according to the condition of distributed power supplies carried by each unmanned aerial vehicle;
the magnetic coupling module is used for realizing air separation and combination of all the sub unmanned aerial vehicles according to the technical parameters and task parameters preset by the unmanned aerial vehicles and the conditions of lifting balance, pushing balance and energy balance;
the cluster control and networking module is used for performing alliance division on the sub-unmanned aerial vehicle clusters and determining the number of the sub-unmanned aerial vehicles communicating with the long plane; and formation self-repairing when the sub unmanned aerial vehicle is damaged;
the communication reconstruction and cooperation module is used for reconstructing and cooperating communication resources of the unmanned aerial vehicle aiming at the communication module and the communication function of the unmanned aerial vehicle in the combined unmanned aerial vehicle so as to realize multiplexing gain or space diversity gain of communication.
The task and scene planning algorithm models the tasks and scenes according to different working environments faced by the unmanned aerial vehicle, designs different strategy pools, and establishes corresponding strategy libraries; and when the unmanned aerial vehicle joint task is executed, calling a corresponding execution program from the corresponding strategy pool.
According to an embodiment of the present invention, the task and scenario planning algorithm further comprises: the input data are preprocessed by a preprocessing unit, a feature extraction unit and a classification decision unit; wherein the content of the first and second substances,
the input data preprocessing unit is used for preprocessing the input data to enable the processed wireless signals to become the part of processing operation of the input of the classification algorithm; mapping from a signal space to an observation space, the process mainly comprises: correlation, filtering and power normalization of signals;
the feature extraction unit is used for extracting features, and mapping from an observation space with higher dimensionality to a feature space with lower dimensionality to extract time domain features, transform domain features and various statistic parameters of a received signal; the time domain features include histograms or other statistical parameters of the amplitude, phase of the signal; the transform domain characteristics comprise a power spectrum, a spectrum correlation function, time frequency distribution and other statistical parameters;
and the classification decision unit is used for performing classification decision, inputting the extracted characteristic parameters into the designed classifier and identifying the corresponding scene category.
According to an embodiment of the present invention, the classification decision unit includes a learning training subunit for learning training to find an appropriate decision rule through a known sample; and the identification subunit is used for designing a classifier by using the rules obtained by training to realize the identification of the unknown scene type.
According to one embodiment of the invention, the energy distribution module comprises an electric quantity information acquisition unit, a screening unit and a control unit; wherein the content of the first and second substances,
the electric quantity information acquisition unit is used for acquiring electric quantity information of a main load and all unmanned aerial vehicle battery units when the unmanned aerial vehicle is combined;
the screening unit is used for screening any unmanned aerial vehicle battery unit with electric quantity information meeting the requirements from other battery units as a second power supply unit when the electric quantity information of one unmanned aerial vehicle battery unit does not meet the preset conditions, and the rest can be done in the same way;
the control unit is used for judging and respectively outputting a control instruction to the battery unit and the switch unit of each sub-unmanned aerial vehicle, and when the electric energy reserve of a certain sub-unmanned aerial vehicle is insufficient, the electric energy is coordinated through distributed energy control, and the whole cruising of the combined unmanned aerial vehicle is ensured.
According to one embodiment of the invention, the magnetic coupling module comprises a mechanical structure unit, a current unit and a data unit; wherein the content of the first and second substances,
the mechanical structure unit is used for separating and combining the unmanned aerial vehicle, and conducting current and data, comprises an upper interface and a lower interface which are of concave-convex structures respectively, wherein the concave part of the upper interface is combined with the convex part of the lower interface to form a conducting area of the current and the data, and the convex part of the upper interface corresponds to the concave part of the lower interface to form a magnetic area.
The current unit is used for controlling the current direction to overturn magnetism, so that the functions of attraction and repulsion between the sub unmanned aerial vehicles are realized.
The data unit is used for transmitting data among the sub-unmanned aerial vehicles, and is convenient for the whole remote measurement control and data transmission of the combined unmanned aerial vehicle.
According to an embodiment of the present invention, the cluster control and networking module includes: a virtual alliance unit and a virtual long machine unit; wherein the content of the first and second substances,
the virtual alliance unit is used for designing a local communication mode based on a virtual alliance, when the distance between sub-networks in the cluster is larger than the communication radius, the network is called as an independent virtual alliance, one unmanned aerial vehicle in the virtual alliance unit is a navigation information unmanned aerial vehicle, and the other unmanned aerial vehicles are non-navigation information unmanned aerial vehicles.
The virtual long machine unit is used for communicating with the navigation information unmanned aerial vehicle in the virtual alliance, and other unmanned aerial vehicles in the virtual alliance indirectly acquire the information of the virtual long machine through communicating with the navigation information unmanned aerial vehicle, so that each unmanned aerial vehicle at any moment can directly or indirectly acquire the information of the virtual long machine.
When the communication degree of the sub unmanned aerial vehicle cluster is continuously increased, the number of the virtual alliances is continuously reduced, and the number of the unmanned aerial vehicles for obtaining the virtual long-distance machine information is also continuously reduced; when the whole cluster is communicated again, only one unmanned aerial vehicle is needed to obtain the information of the virtual long machine, the connectivity and the stability of the cluster can be ensured, and the communication resource of the system can be saved.
According to one embodiment of the invention, the communication reconfiguration and cooperation module comprises: the device comprises a communication resource reconstruction unit and a multi-point cooperation intelligent communication unit.
The communication resource reconstruction unit is used for realizing multiplexing gain or space diversity gain of communication, and in the combined unmanned aerial vehicle, as each unmanned aerial vehicle possibly has a basic communication module and a communication function, the communication resource reconstruction unit can reconstruct and collaborate the communication resources.
The multi-point cooperative intelligent communication unit is used for adaptively and dynamically reconstructing and configuring communication resources according to the scene and the requirement of a work task and the execution stage of the task.
The intelligent combined unmanned aerial vehicle system research route map is shown in fig. 2, and the specific steps are as follows:
1: tasks and scenarios are modeled for different work environments. According to different tasks, different strategy pools are designed, and the strategy pools comprise: cluster control and networking, magnetic coupling, energy distribution, communication reconfiguration and cooperation. Establishing a corresponding strategy library according to different small unmanned aerial vehicles and the whole combination; and when the unmanned aerial vehicle joint task is executed, calling a corresponding execution program from the corresponding strategy pool.
2: and researching cluster control and networking technology. The intelligent cluster control technology of the combined unmanned aerial vehicle based on the virtual long machine is researched so as to achieve the flexibility and the survivability of the combination of the machine sets. Based on the formation of the combined unmanned aerial vehicle, a wireless networking technology based on a virtual center is researched; the technology can separate the entity functions of communication, control, calculation, storage and the like, and realize the advantages of flexible communication structure and high robustness.
3: magnetic coupling techniques were investigated. According to the technical parameters and task parameters preset by the unmanned aerial vehicle, and the principles of weight lifting balance, push-drag balance, energy balance and the like, the magnetic coupling technology for realizing air separation and combination of the sub unmanned aerial vehicles is researched.
4: energy distribution techniques are studied. The optimal weight of the solar photovoltaic and high-energy-density battery in the combined unmanned aerial vehicle is researched by researching the balance design technology of energy and weight so as to prolong the cruising ability of the combined unmanned aerial vehicle in flight. A multi-power-supply current sharing technology based on task requirements and scene understanding is researched, and distributed power supplies carried by all combined unmanned aerial vehicles are utilized to achieve optimal configuration of energy resources.
5: communication reconfiguration and cooperative communication techniques are studied. Based on task perception and scene understanding, in the combined unmanned aerial vehicle, the communication resources of each sub-unmanned aerial vehicle are reconstructed and cooperatively processed, so that the optimal configuration of the communication resources is realized, and the multiplexing gain and the diversity gain of communication are improved.
Each module is described in detail below.
The task and scene scenario module
The intelligent combined unmanned aerial vehicle can support rich application scenes and task requirements. Because different application scenes, different task demands are different to the demands of each unmanned aerial vehicle platform such as control, flight, communication and the like, each parameter of the power, control, sensing, load, communication and other sub-systems is optimized and configured by researching intelligent task perception and scene understanding technology, each small unmanned aerial vehicle is reasonably designed, and finally, the small unmanned aerial vehicles are combined to form a comprehensive and intelligent whole unmanned aerial vehicle.
The implementation method comprises the following steps: by researching algorithms such as a Deep Neural Network (DNN), a Convolutional Neural Network (CNN), a K Nearest Neighbor (KNN) and the like, contents such as scene understanding based on communication signal characteristics, scene understanding based on multidimensional sensing data, task perception based on the multidimensional sensing data and the like are deeply researched; in specific implementation, a classical low-complexity KNN algorithm technology can be preferentially adopted according to the computing performance of the platform. The specific research can be divided into three steps to realize task perception and scene understanding:
a) the input data is pre-processed such that the wireless signal is processed and then becomes the portion of the processing operation that is input to the classification algorithm. Mapping from a signal space to an observation space, the process mainly comprises: correlation, filtering, power normalization of the signal, etc.
b) And (3) feature extraction, namely mapping from an observation space with higher dimensionality to a feature space with lower dimensionality to extract parameters such as time domain features, transform domain features, various statistics and the like of the received signal, which is a key step of scene identification. The time domain features include histograms or other statistical parameters of the amplitude, phase of the signal. The transform domain features include power spectrum, spectral correlation function, time-frequency distribution and other statistical parameters.
c) And (4) classification decision, namely inputting the extracted characteristic parameters into a designed classifier, and identifying the corresponding scene category. This step is divided into two processes: firstly, learning and training, and seeking a proper decision rule through a known sample; and secondly, identifying, namely designing a classifier by using the rule obtained by training to realize the identification of the unknown scene type.
Cluster control and networking module
Aiming at the cluster formation control problem of the sub unmanned aerial vehicles under the switching topological structure, when the network topological structure is changed due to formation change or partial communication network faults, the sub unmanned aerial vehicle clusters are subjected to alliance division by using a distance as a principle, and the number of the sub unmanned aerial vehicles communicating with the virtual long machine is flexibly determined; by carrying out off-line layering on the expected formation and designing the corresponding repair rule, the formation self-repair problem when the sub unmanned aerial vehicle is damaged is solved, and the demands of decentralization, autonomy and autonomy of the combined unmanned aerial vehicle are met.
The implementation method comprises the following steps: the sub unmanned aerial vehicles are divided into a plurality of alliances by using the distance as a principle, and when the distance between the sub networks in the cluster is larger than the communication radius, the sub networks are called as an independent sub network. An independent sub-network forms a federation, as shown in fig. 3, a cluster in the figure comprises 2 independent sub-networks, the cluster is divided into 2 federations, and a local communication mode based on the federations is designed. In fig. 3, one unmanned aerial vehicle is a virtual long machine, each small circle represents one alliance, one unmanned aerial vehicle in each alliance is a navigation information unmanned aerial vehicle, the others are non-navigation information unmanned aerial vehicles, the virtual long machine only needs to communicate with the navigation information unmanned aerial vehicle in each alliance, and the other unmanned aerial vehicles indirectly acquire information of the virtual long machine through communication with the navigation information unmanned aerial vehicle.
Only select out an unmanned aerial vehicle (navigation information unmanned aerial vehicle) to obtain virtual long quick-witted information from every alliance, other alliance members obtain virtual long quick-witted information through navigation information unmanned aerial vehicle is indirect again, guarantee that every unmanned aerial vehicle can both directly or indirectly obtain virtual long quick-witted information at any moment, the degree of intercommunication when the cluster constantly increases, alliance quantity constantly reduces, the unmanned aerial vehicle quantity that obtains virtual long quick-witted information also constantly reduces, when whole cluster resumes the intercommunication, only need an unmanned aerial vehicle to obtain virtual long quick-witted information, just can guarantee the connectivity and the stability of cluster, be favorable to saving the communication resource of system.
The magnetic coupling module
And (3) researching a magnetic coupling technology for realizing air separation and combination of the sub-unmanned aerial vehicles by combining preset technical parameters and task parameters (including task load, idle time, maximum flight speed and maximum flight height) and principles of lifting balance, thrust-drag balance and energy balance, and performing demonstration, simulation verification and experimental verification on the researched scheme.
The implementation method comprises the following steps: the mechanical structure of the magnetic coupling technology comprises an upper interface and a lower interface which are respectively of a concave-convex structure, the concave-convex structure is respectively composed of a magnetic area and a conducting area, a concave part of the upper interface is combined with a convex part of the lower interface to form a conducting area of current and data, and the convex part of the upper interface corresponds to the concave part of the lower interface to form the magnetic area. When a plurality of sub unmanned aerial vehicles need to be combined in the air, the magnetic interfaces are mutually adsorbed; and when many son unmanned aerial vehicle need separate, thereby control current direction upset magnetism mutual repulsion.
Energy distribution module
By researching the technology of combining solar photovoltaic and high-energy density batteries in the unmanned aerial vehicle, a solar panel is laid on the wing; utilize many power of distributing type to flow equalize the technique, evenly provide the electric energy during the combination flight to arbitrary unmanned aerial vehicle electrical power generating system inefficacy, other unmanned aerial vehicles can plug into the power supply, thereby reach the energy can be saved, increase the effect of journey.
The implementation method comprises the following steps: the power management unit of the combined unmanned aerial vehicle comprises a plurality of battery units of the sub-unmanned aerial vehicles and switch units corresponding to the battery units. When the unmanned aerial vehicle is combined, the main load automatically acquires the electric quantity information of all the unmanned aerial vehicle battery units. When the electric quantity information of a certain unmanned aerial vehicle battery unit does not accord with the preset condition, any unmanned aerial vehicle battery unit with the electric quantity information meeting the requirements is screened from other battery units to serve as a second power supply unit, and the rest can be done in the same way. Each sub-unmanned aerial vehicle system is provided with a sampling detection circuit and a plurality of switch units and used for receiving sampling detection results, judging and respectively outputting control instructions to each unmanned aerial vehicle battery unit and the switch units, and controlling the disconnection of the unmanned aerial vehicle battery units which do not accord with electric quantity information to accord with the closing of the electric quantity information.
Communication reconfiguration and cooperation module
The intelligent communication refers to a communication technology with adaptive communication signal processing capabilities such as task perception, spectrum perception, environment recognition, interference recognition and scene understanding. In a combined drone, since each drone may have basic communication modules and communication functions, these communication resources may be reconstructed and cooperatively processed to achieve multiplexing gain or spatial diversity gain of communication.
The implementation method comprises the following steps: and adaptively and dynamically reconstructing and configuring the communication resources according to the requirements of the tasks and the perceived task scene and the execution stage of the tasks. For example, if remote operation is to be implemented, the members of the combined drone include a long drone with a long endurance, an image acquisition sub drone, a relay communication sub drone, and the like. As shown in fig. 4, in the process of remote flight of the combined unmanned aerial vehicle, since all the unmanned aerial vehicles fly in combination, when the margin of the point-to-point communication link is sufficient, the communication link of the submachine can be shut down, and only the link of one of the unmanned aerial vehicles, such as the long unmanned aerial vehicle, is reserved; when the margin of the point-to-point communication link is insufficient, the transmission distance can be increased by opening the communication link of the submachine and loading a communication waveform which can be reconstructed and has spatial multiplexing gain; when the sub unmanned aerial vehicle with the relay communication function performs work, the unit can directly perform remote communication or control.
Theoretically, the maximum space multiplexing or space diversity gain that can be obtained by the combined unmanned aerial vehicle is proportional to the total number of independent radio frequency channels of all the submachine. Due to the fact that the load capacity of the combined unmanned aerial vehicle is strong, if the directional antenna is adopted, the combined unmanned aerial vehicle has higher efficiency in the aspect of realizing ground-to-ground and air-to-air communication.
The invention has the beneficial effects that:
the combined unmanned aerial vehicle is formed by cooperatively sharing, distributing and grouping information resources by a plurality of sub-aircrafts, cooperative cooperation among the plurality of aircrafts is realized through a control system, complex tasks are jointly completed, and the purposes of saving energy efficiency and enhancing endurance are achieved through combination and decomposition.
The combined drone can achieve the purpose through autonomous behavior. Humanoid and even superman inorganic life forms in the aspects of perception, interaction, information processing, decision control, learning and execution capabilities, similar to science fiction future unmanned systems. The unmanned aerial vehicle cooperative work is combined, the task types are expanded, and the operation capability under the complex confrontation environment is enhanced.
This kind of novel combination unmanned aerial vehicle has created the unmanned aerial vehicle agent that has ultimate adaptability, possesses task perception, intelligent scene understanding, cluster control, fuses multiple high and new technologies such as communication and overlength continuation of the journey, can be according to task demand fast decomposition for many shelves of unmanned aerial vehicle to be suitable for multiple application scene.
It will be apparent to those skilled in the art that various changes and modifications may be made in the invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (7)
1. An intelligent combined unmanned aerial vehicle system is characterized in that the unmanned aerial vehicle system can be combined and separated in the air, has task perception and scene understanding capacity, and comprises an unmanned aerial vehicle complete machine, an energy distribution module, a magnetic connection module, a cluster control and networking module and a communication reconstruction and cooperation module; wherein the content of the first and second substances,
the whole unmanned aerial vehicle comprises a long unmanned aerial vehicle and at least one sub unmanned aerial vehicle; the long unmanned aerial vehicle and at least one sub unmanned aerial vehicle realize cooperative coordination to complete tasks according to task perception and scene understanding algorithms through an energy distribution module, a magnetic coupling module, a cluster control and networking module and a communication reconstruction and cooperation module;
the energy distribution module is used for realizing optimal configuration of energy resources according to the condition of distributed power supplies carried by each unmanned aerial vehicle;
the magnetic coupling module is used for realizing air separation and combination of all the sub unmanned aerial vehicles according to the technical parameters and task parameters preset by the unmanned aerial vehicles and the conditions of lifting balance, pushing balance and energy balance;
the cluster control and networking module is used for performing alliance division on the sub-unmanned aerial vehicle clusters and determining the number of the sub-unmanned aerial vehicles communicating with the long plane; and formation self-repairing when the sub unmanned aerial vehicle is damaged;
the communication reconstruction and cooperation module is used for reconstructing and cooperating communication resources of the unmanned aerial vehicle aiming at the communication module and the communication function of the unmanned aerial vehicle in the combined unmanned aerial vehicle so as to realize multiplexing gain or space diversity gain of communication.
The task and scene planning algorithm models the tasks and scenes according to different working environments faced by the unmanned aerial vehicle, designs different strategy pools, and establishes corresponding strategy libraries; and when the unmanned aerial vehicle joint task is executed, calling a corresponding execution program from the corresponding strategy pool.
2. The intelligent combination drone system of claim 1, wherein the task and scenario solution algorithm further comprises: the input data are preprocessed by a preprocessing unit, a feature extraction unit and a classification decision unit; wherein the content of the first and second substances,
the input data preprocessing unit is used for preprocessing the input data to enable the processed wireless signals to become the part of processing operation of the input of the classification algorithm; mapping from a signal space to an observation space, the process mainly comprises: correlation, filtering and power normalization of signals;
the feature extraction unit is used for extracting features, and mapping from an observation space with higher dimensionality to a feature space with lower dimensionality to extract time domain features, transform domain features and various statistic parameters of a received signal; the time domain features include histograms or other statistical parameters of the amplitude, phase of the signal; the transform domain characteristics comprise a power spectrum, a spectrum correlation function, time frequency distribution and other statistical parameters;
and the classification decision unit is used for performing classification decision, inputting the extracted characteristic parameters into the designed classifier and identifying the corresponding scene category.
3. The intelligent combined drone system of claim 2, wherein the classification decision unit includes a learning training subunit for learning training to find a suitable decision rule by known samples; and the identification subunit is used for designing a classifier by using the rules obtained by training to realize the identification of the unknown scene type.
4. The intelligent combined unmanned aerial vehicle system of claim 1, wherein the energy distribution module comprises an electric quantity information acquisition unit, a screening unit, and a control unit; wherein the content of the first and second substances,
the electric quantity information acquisition unit is used for acquiring electric quantity information of a main load and all unmanned aerial vehicle battery units when the unmanned aerial vehicle is combined;
the screening unit is used for screening any unmanned aerial vehicle battery unit with electric quantity information meeting the requirements from other battery units as a second power supply unit when the electric quantity information of one unmanned aerial vehicle battery unit does not meet the preset conditions, and the rest can be done in the same way;
the control unit is used for judging and respectively outputting a control instruction to the battery unit and the switch unit of each sub-unmanned aerial vehicle, and when the electric energy reserve of a certain sub-unmanned aerial vehicle is insufficient, the electric energy is coordinated through distributed energy control, and the whole cruising of the combined unmanned aerial vehicle is ensured.
5. The intelligent combination drone system of claim 1, wherein the magnetic coupling module includes a mechanical structure unit, a current unit, and a data unit; wherein the content of the first and second substances,
the mechanical structure unit is used for separating and combining the unmanned aerial vehicle, and conducting current and data, comprises an upper interface and a lower interface which are of concave-convex structures respectively, wherein the concave part of the upper interface is combined with the convex part of the lower interface to form a conducting area of the current and the data, and the convex part of the upper interface corresponds to the concave part of the lower interface to form a magnetic area.
The current unit is used for controlling the current direction to overturn magnetism, so that the functions of attraction and repulsion between the sub unmanned aerial vehicles are realized.
The data unit is used for transmitting data among the sub-unmanned aerial vehicles, and is convenient for the whole remote measurement control and data transmission of the combined unmanned aerial vehicle.
6. The intelligent combined drone system of claim 1, wherein the cluster control and networking module includes: a virtual alliance unit and a virtual long machine unit; wherein the content of the first and second substances,
the virtual alliance unit is used for designing a local communication mode based on a virtual alliance, when the distance between sub-networks in the cluster is larger than the communication radius, the network is called as an independent virtual alliance, one unmanned aerial vehicle in the virtual alliance unit is a navigation information unmanned aerial vehicle, and the other unmanned aerial vehicles are non-navigation information unmanned aerial vehicles.
The virtual long machine unit is used for communicating with the navigation information unmanned aerial vehicle in the virtual alliance, and other unmanned aerial vehicles in the virtual alliance indirectly acquire the information of the virtual long machine through communicating with the navigation information unmanned aerial vehicle, so that each unmanned aerial vehicle at any moment can directly or indirectly acquire the information of the virtual long machine.
When the communication degree of the sub unmanned aerial vehicle cluster is continuously increased, the number of the virtual alliances is continuously reduced, and the number of the unmanned aerial vehicles for obtaining the virtual long-distance machine information is also continuously reduced; when the whole cluster is communicated again, only one unmanned aerial vehicle is needed to obtain the information of the virtual long machine, the connectivity and the stability of the cluster can be ensured, and the communication resource of the system can be saved.
7. The intelligent combined drone system of claim 1, wherein the communication reconfiguration and collaboration module includes: the device comprises a communication resource reconstruction unit and a multi-point cooperation intelligent communication unit.
The communication resource reconstruction unit is used for realizing multiplexing gain or space diversity gain of communication, and in the combined unmanned aerial vehicle, as each unmanned aerial vehicle possibly has a basic communication module and a communication function, the communication resource reconstruction unit can reconstruct and collaborate the communication resources.
The multi-point cooperative intelligent communication unit is used for adaptively and dynamically reconstructing and configuring communication resources according to the scene and the requirement of a work task and the execution stage of the task.
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