CN116080423A

CN116080423A - Cluster unmanned vehicle energy supply system based on ROS and execution method thereof

Info

Publication number: CN116080423A
Application number: CN202310340662.2A
Authority: CN
Inventors: 杨淳; 盛点; 陈曦; 郭林洪
Original assignee: University of Electronic Science and Technology of China
Current assignee: University of Electronic Science and Technology of China
Priority date: 2023-04-03
Filing date: 2023-04-03
Publication date: 2023-05-09
Anticipated expiration: 2043-04-03
Also published as: CN116080423B

Abstract

The invention discloses a cluster unmanned vehicle energy supply system based on ROS and an execution method thereof, and relates to the technical field of ROS intelligent unmanned vehicles. The invention particularly provides a multi-vehicle cluster technology which is based on an ROS system and is provided with a laser radar, and can realize autonomous collaborative map building navigation of multiple vehicles and synchronous data updating of cloud. When the main vehicle is in a power failure, the power supply vehicle automatically goes to the position of the main vehicle, automatic alignment and energy supply are realized through the wireless charging module, and all map building data and trolley information in the process can be sent to a remote upper computer through a server deployed at a cloud to realize remote monitoring. The whole set of charging system, ROS system, communication system and chassis drive can greatly improve the efficiency of map construction and execution of disaster areas in rescue and relief work, and can provide energy guarantee for the stable operation of the system.

Description

Cluster unmanned vehicle energy supply system based on ROS and execution method thereof

Technical Field

The invention relates to the technical field of ROS intelligent unmanned vehicles, and particularly provides a multi-vehicle cluster technology which is based on an ROS system and is provided with a laser radar and can realize autonomous collaborative map building navigation of multiple vehicles and synchronous data updating of cloud. When the main vehicle is in a power failure, the power supply vehicle automatically goes to the position of the main vehicle, and the automatic alignment and energy supply are realized through the wireless charging module.

Background

Under the large background of frequent natural disasters nowadays, unmanned vehicles play an increasing role in the field of rescue and relief work. When the unmanned vehicle searches the disaster area, the unmanned vehicle is limited by a complex geographical environment, and a single unmanned vehicle is difficult to draw an exhaustive three-dimensional map of the disaster area in a golden time period. In addition, because unmanned vehicles suitable for rescue and relief work often need enough flexibility, the battery capacity of the unmanned vehicles is limited physically, and the practical requirements are difficult to meet.

In order to solve the problems, a part of scientific researchers put forward a concept that a plurality of unmanned vehicles can be functionally differentiated to improve the specificity of different industrial species in a specific field. Particularly reflected in the field of rescue and relief work, a cluster consisting of a plurality of differentiated vehicle types is proposed partially aiming at the field of energy source guarantee. However, technical searches indicate that real-time communication, global accurate position confirmation and advanced unmanned vehicle cluster for collaborative map drawing can be realized, and the advanced unmanned vehicle cluster is still blank.

And (3) researching energy source guarantee wireless charging. The wireless power supply technology and the application thereof in the fields of military and civil use at home and abroad have been primarily developed, and have demonstrated their superiority in some fields. Therefore, an autonomous wireless charging function is added for emergency intelligent equipment, and the energy source guaranteeing robot is developed, so that the intelligent energy source guaranteeing robot has important significance and urgency.

Disclosure of Invention

The invention aims to provide a systematic solution which can guarantee energy supply of a cluster unmanned vehicle in real time, greatly improve the efficiency of disaster area map building in rescue and relief work and realize remote monitoring and instruction issuing through a server.

In order to achieve the above purpose, the present invention provides the following technical solutions: the system comprises two types of ROS unmanned vehicles, and a local ROS system algorithm matched with the ROS unmanned vehicles and a cloud server control application;

the first type of unmanned vehicles have lower quality and stronger flexibility, are hereinafter referred to as rescue and relief unmanned vehicles for short, are divided into two layers, and the first layer consists of a chassis control system and a battery; the first layer comprises a metal substrate (a 1), and four Mecanum omni-wheels are connected with a 12V motor (a 2); one end of the first logic signal level conversion module (a 3) is connected with two first direct current motor driving modules (a 4), and the other end of the first logic signal level conversion module is connected with the first Arduino MCU (a 5) so as to transmit an interrupt return signal; one end of the first DC voltage reduction module (a 6) is connected with a 12V first battery (a 7), and the other end of the first DC voltage reduction module is connected with a first raspberry group (a 8); the second layer consists of a master control communication system, a map building navigation sensor system and a wireless charging system; the second layer comprises a first raspberry group (a 8), and the first laser radar (a 9) and the RGB-D depth camera (a 13) are connected to the first raspberry group (a 8); the 3D printing wireless charging coil butt joint assembly (a 10) is fixed on the metal substrate; the first magnetic resonance wireless charging module (a 11) is connected to the first battery (a 7) through the DC-DC stabilized power supply module (a 12); the method comprises the steps that an upper computer of a terminal sends instruction information to a first raspberry group (a 8) through a local area network generated by an unmanned vehicle, receives real-time parameters and mapping information uploaded by the upper computer of the terminal, uploads the data to a server, and displays and operates global information through a visual operation interface at a remote control terminal;

the second class of unmanned vehicles has larger battery voltage, larger capacity and weaker maneuverability, and is hereinafter called energy source guarantee unmanned vehicles for short; the unmanned vehicle is structurally divided into two layers, wherein the first layer consists of a chassis control system and a battery, the layer comprises a special acrylic substrate (b 1), four Mecanum omnidirectional wheels are connected with a 12V motor (b 2), one end of a second logic signal level conversion module (b 3) is connected with two second direct current motor driving modules (b 4), and the other end of the second logic signal level conversion module is connected with a second Arduino MCU (b 5); one end of the second DC voltage reduction module (b 6) is connected with a 24V second battery (b 7), and the other end of the second DC voltage reduction module is connected with a second raspberry group (b 8); one end of the two second DC voltage reduction modules (b 9) is connected with the second battery (b 7), and the other end is connected with the second direct current motor driving module (b 4); the second layer consists of a master control communication system, a map building navigation sensor system and a wireless charging system; the layer comprises a second raspberry group (b 8), and the second laser radars (b 11) are connected to the second raspberry group (b 8); the 3D printing wireless charging coil assembly (b 10) is connected to the second battery (b 7) through the voltage-stabilizing power supply module (b 12); two ultrasonic modules (c 2) are also connected to the 3D printing wireless charging coil assembly (b 10) and used for accurate positioning; the upper computer of the terminal sends instruction information to the second raspberry group (b 8) through a local area network generated by the unmanned vehicle, receives the real-time parameters and the mapping information uploaded by the upper computer of the terminal, further uploads the data to a server, and presents and operates global information through a visual operation interface at a remote control terminal;

for the wireless charging system, two corresponding 3D printing components (c 1) used for butt joint and two ultrasonic modules (c 2) connected to the 3D components and used for accurate positioning are fixed on one surface of a second type unmanned vehicle; wherein the second magnetic resonance wireless charging module (c 3) is fixed on the 3D printing component (c 1); after the docking based on the ultrasonic module (c 2) is completed, the magnetic resonance wireless charging module is also connected to the second battery (b 7) through the voltage stabilizing charging module (b 12) to charge the second battery;

in a remote upper computer display program, a user needs to click a start button to start connection, and the connection state of a server is displayed in a text column above the start button; when the text display is connected, the charging information, the electric quantity and the action state of the trolleys are displayed on the right panel; meanwhile, the drawing building information is displayed in a picture window on the left side, and all the information is updated in real time under the condition of building connection; the user can also manually enable the trolley to execute charging operation through the forced charging button; when the user needs to log out, the stop button is pressed to disconnect, so that the program stops accepting data, and the server and the trolley still operate in the background.

The technical scheme of the invention is as follows: a method of performing a ROS-based clustered unmanned vehicle energy supply system, the method comprising:

firstly, two unmanned vehicles are put into an area to be explored; after a power supply is started, the unmanned vehicle automatically completes automatic starting inspection, automatically executes a preset program after no error, starts an ROS system and related Launch nodes, and sets sensor drivers and information flow transmission topics thereof; finally, connection and data flow subscription between the clusters and the upper computer are carried out through the local area network which is generated autonomously;

secondly, after the upper computer issues an instruction for starting the joint mapping through the authority of an administrator at the server side, the two unmanned vehicles start a specified ROS program; the method comprises the steps that the first raspberry group (a 8) and the second raspberry group (b 8) respectively use peripheral environment data acquired through a first laser radar (a 9) and a second laser radar (b 11) at 30Hz frequency, and wheel speed data received by a first Arduino MCU (a 5) and a second Arduino MCU (b 5) and acquired by a motor Hall encoder are used as data integration reference objects of an Odom odometer through a fusion algorithm, and finally the real-time rate of a current single unmanned vehicle and the running track of the integrated single unmanned vehicle in a local map are calculated;

thirdly, uploading data acquired by the first laser radar (a 9) and the second laser radar (b 11) to an upper computer through a first raspberry group (a 8) and a second raspberry group (b 8), processing by a cartograph algorithm, smoothing noise errors which are difficult to avoid on hardware, carrying out multi-stack stacking fusion, quickly building a graph, and marking an obstacle and an unexplored complete pseudo boundary; in the process, map Merge nodes in an upper computer can automatically search and subscribe Map topic data issued by two types of unmanned vehicles, receive and carry out a feature point matching algorithm in real time, and fuse Map big frames built by the two types of vehicles to generate a summary Map with global effect; the Map Merge algorithm can continuously judge and correct the relative coordinates between two types of unmanned vehicles under the condition that the initial coordinate relation of the two types of unmanned vehicles is unknown, so that the two types of unmanned vehicles can confirm the position information mutually, centimeter-level full-space information sharing is realized, and the Map Merge algorithm is used for subsequent global navigation and positioning alignment in a cluster;

fourthly, an RGB-D camera (a 13) additionally arranged on the first type of rescue and relief unmanned vehicle is suitable for transmitting RGB three-channel images, and the RGB three-channel images are uploaded to an upper computer through a first raspberry group (a 8); meanwhile, the upper computer starts an Rtab three-dimensional mapping algorithm, and expands a two-dimensional map into a three-dimensional map with point cloud constructivity under the constraint of a two-dimensional laser radar by utilizing a camera to level a depth view field within 45 degrees, so that a region to be explored can be visually presented in a full-color three-dimensional mode. The second type of energy source guarantee unmanned vehicle has relatively low flexibility due to a large-capacity battery on the vehicle, but also can be accompanied with the first type of rescue and relief unmanned vehicle, and the second type of energy source guarantee unmanned vehicle assists in drawing during work exploration so as to ensure energy source supply and drawing efficiency at the same time;

and fifthly, when the first type of rescue and relief unmanned aerial vehicle is low in electric quantity (the preset program is below 20%), a low-electric quantity signal is sent to the upper computer through the first raspberry group (a 8), and the upper computer sends the space coordinates of the unmanned aerial vehicle to be charged to the energy source to ensure the unmanned aerial vehicle which is close to the space coordinates. The energy source of the received instruction ensures that the unmanned vehicles automatically plan an optimal global path between the unmanned vehicles to be charged through the parameters preset by the Move Base node, monitors and updates obstacle information in real time during operation, and acquires a Cost Map to optimize a local path solution. When the distance reaches a coarse positioning threshold (the default is that the distance is smaller than 20cm, and the angle deviation of the direction tail to the tail is smaller than 10 degrees), the second raspberry group (b 8) switches the issuing instruction to the chassis control system and switches the second Arduino MCU (b 5) of the main control board into a precise alignment program;

and sixthly, starting two ultrasonic modules (c 2) positioned at the tail of the energy-guaranteeing unmanned vehicle by a second Arduino MCU (b 5) to acquire millimeter-level distance data of the two vehicles. Through the PID algorithm, the energy source can ensure that the unmanned vehicle can automatically adjust the distance and direction of the unmanned vehicle for rescue and relief work. When the absolute data difference of the two ultrasonic modules is within 0.5cm (namely, the angle is smaller than 5 degrees) and the average value is within the range of 5-8cm, the alignment is completed, and the wireless charging system starts to charge the rescue and relief unmanned vehicle;

a seventh step, when receiving the alignment completion signal, the second Arduino MCU (b 5) conducts a loop where the wireless charging system transmitting coil and the 24V second battery (b 7) are located through a relay in the wireless power supply coil assembly, so that the battery supplies power for the transmitting coil module, energy transfer between the transmitting coil and the receiving coil is realized through a magnetic resonance power supply principle, and the wireless receiving coil assembly supplies power for a vehicle-mounted 12V battery of the rescue and relief trolley through a rectifying circuit and a 12V-to-5V DC stabilized voltage power supply module (a 7);

eighth, when the rescue and relief unmanned vehicle is fully charged, the first raspberry group (a 8) sends the full-charge marker to the upper computer. After the upper computer issues a topic of stopping charging, the energy source guarantee unmanned vehicle resets a second Arduino MCU (b 5) accurate alignment program in the chassis control system back to the chassis control program, so that the energy source guarantee trolley and the rescue and relief trolley continue to work;

in the whole process, the upper computer can issue real-time data to the server, and the user remote control end operation interface can see the map of the whole exploration area and the position information and electric quantity information of each unmanned vehicle in the unmanned vehicle cluster; when the rescue and relief unmanned aerial vehicle needs to be charged, a user operation interface displays the unmanned aerial vehicle and displays charging voltage information in the charging process; in the process of unmanned vehicle clustering, a user forces the rescue and relief unmanned vehicles to charge through a remote control end operation interface or finishes charging in the charging process; when the electric quantity of the energy source guarantee unmanned vehicle is low, the energy source guarantee unmanned vehicle is also displayed on a user operation interface.

The trolley end uploading process (d 1) comprises the steps of reading data collected by a sensor and mapping information of the ROS system, and uploading the data in blocks in a mode of establishing socket connection with a server. The remote user receiving end (d 2) directly establishes socket connection with the server, and downloads and displays the map building condition through a picture transmission mode based on an http protocol of the server. And transmitting json files by a socket protocol for other text data including trolley electric quantity and trolley conditions so as to be convenient for a client to read and display.

Drawings

FIG. 1 is a schematic view of a first layer of a first type of unmanned vehicle, i.e., an emergency rescue and relief unmanned vehicle;

FIG. 2 is a schematic view of a second layer of a first type of unmanned vehicle, i.e., an emergency rescue and relief unmanned vehicle;

FIG. 3 is a schematic view of a first layer of an energy-guaranteeing unmanned vehicle of a second type;

fig. 4 is a schematic structural view of a second layer of the second class unmanned vehicle, i.e. the energy-guaranteeing unmanned vehicle;

FIG. 5 is a schematic diagram of a charging module and alignment on a second class of unmanned vehicles, i.e., energy conservation unmanned vehicles;

FIG. 6 is a schematic illustration of an overall workflow of a drone cluster;

FIG. 7 is a schematic diagram of the workflow of the uploading end;

fig. 8 is a schematic workflow diagram of a remote host.

In the figure, a1. metal substrate, a2. Motor, a3. First logic signal level conversion module, a4. first direct current motor drive module, a5. First Arduino MCU, a6. first DC voltage reduction module, a7. first battery, a8. first raspberry group, a9. first laser radar, a 10.3D print wireless charging coil docking assembly, a11. First magnetic resonance wireless charging module, a12. DC-DC regulated power supply module, a13.RGB-D depth camera, b1. acrylic substrate, b2.12V motor, b3. second logic signal level conversion module, b4. second direct current motor drive module, b5. second Arduino MCU, b6. second DC voltage reduction module, b7. second battery, b8. Second raspberry group, b9. Second DC voltage reduction module, b10.3D print wireless charging coil assembly, b11 second laser radar, b12. Regulated power supply module, c1.3D print component, c2. second magnetic resonance module.

Description of the embodiments

As shown in fig. 1, a first-class unmanned vehicle, namely an emergency rescue and disaster relief unmanned vehicle, has a lower quality and higher flexibility, is hereinafter referred to as an emergency rescue and disaster relief unmanned vehicle for short, and is divided into two layers, wherein the first layer consists of a chassis control system and a battery; the first layer comprises a metal substrate (a 1), and four Mecanum omni-wheels are connected with a 12V motor (a 2); one end of the first logic signal level conversion module (a 3) is connected with two first direct current motor driving modules (a 4), and the other end of the first logic signal level conversion module is connected with the first Arduino MCU (a 5) so as to transmit an interrupt return signal; one end of the first DC voltage reduction module (a 6) is connected with a 12V first battery (a 7), and the other end of the first DC voltage reduction module is connected with a first raspberry group (a 8); the second layer consists of a master control communication system, a map building navigation sensor system and a wireless charging system;

in the first step, before performing the exploration task, the related personnel need to put the two unmanned vehicles into the area to be explored. After the power supply is started, the unmanned vehicle automatically completes automatic starting inspection, automatically executes a preset program after no error, starts the ROS system and the relevant Launch nodes, and sets each sensor drive and information flow transmission topics thereof. And finally, connecting the clusters and the upper computer and subscribing the data stream through the local area network which is generated autonomously. Personnel may also manually control or modify part of the settings for the unmanned cart by joining the local area network.

As shown in fig. 2, a schematic structural diagram of a second layer of a first type of unmanned vehicle, i.e. an emergency rescue unmanned vehicle, wherein the second layer comprises a first raspberry group (a 8), and a first laser radar (a 9) and an RGB-D depth camera (a 13) are connected to the first raspberry group (a 8); the 3D printing wireless charging coil butt joint assembly (a 10) is fixed on the metal substrate; the first magnetic resonance wireless charging module (a 11) is connected to the first battery (a 7) through the DC-DC stabilized power supply module (a 12); the method comprises the steps that an upper computer of a terminal sends instruction information to a first raspberry group (a 8) through a local area network generated by an unmanned vehicle, receives real-time parameters and mapping information uploaded by the upper computer of the terminal, uploads the data to a server, and displays and operates global information through a visual operation interface at a remote control terminal;

fig. 3 is a schematic structural diagram of a first layer of an energy source guaranteeing unmanned vehicle of a second type, wherein the second type has larger battery voltage, larger capacity and weaker maneuverability, and is hereinafter simply referred to as the energy source guaranteeing unmanned vehicle; the unmanned vehicle is structurally divided into two layers, wherein the first layer consists of a chassis control system and a battery, the layer comprises a special acrylic substrate (b 1), four Mecanum omnidirectional wheels are connected with a 12V motor (b 2), one end of a second logic signal level conversion module (b 3) is connected with two second direct current motor driving modules (b 4), and the other end of the second logic signal level conversion module is connected with a second Arduino MCU (b 5); one end of the second DC voltage reduction module (b 6) is connected with a 24V second battery (b 7), and the other end of the second DC voltage reduction module is connected with a second raspberry group (b 8); one end of the two second DC voltage reduction modules (b 9) is connected with the second battery (b 7), and the other end is connected with the second direct current motor driving module (b 4);

fig. 4 is a schematic structural diagram of a second layer of the second type unmanned vehicle, i.e. the energy-guaranteeing unmanned vehicle; the second layer consists of a master control communication system, a map building navigation sensor system and a wireless charging system; the layer comprises a second raspberry group (b 8), and the second laser radars (b 11) are connected to the second raspberry group (b 8); the 3D printing wireless charging coil assembly (b 10) is connected to the second battery (b 7) through the voltage-stabilizing power supply module (b 12);

fig. 5 is a schematic structural diagram of a charging module and alignment on a second type of unmanned vehicle, i.e. an energy-guaranteeing unmanned vehicle; two ultrasonic modules (c 2) are also connected to the 3D printing wireless charging coil assembly (b 10) and used for accurate positioning; the upper computer of the terminal sends instruction information to the second raspberry group (b 8) through a local area network generated by the unmanned vehicle, receives the real-time parameters and the mapping information uploaded by the upper computer of the terminal, further uploads the data to a server, and presents and operates global information through a visual operation interface at a remote control terminal;

in the second step, if there is a connection to the internet, such as WIFI or a base station signal, the cart will communicate with the server according to the upload end procedure shown in fig. 8 and start the data upload procedure. After the basic starting process is completed, related personnel can monitor all information of the trolley at a remote end, including electric quantity, traveling state and map building data. After the upper computer issues an instruction for starting the joint mapping through the authority of the manager at the server side, the two unmanned vehicles start the appointed ROS program. The first raspberry group (a 8) and the second raspberry group (b 8) are used as data integration reference objects of the Odom odometer through a fusion algorithm together by the aid of peripheral environment data acquired by LiTRA LTME-02A through the first laser radar (a 9) and the second laser radar (b 11) at 30Hz frequency and wheel speed data received by the second Arduino MCU (b 5) and acquired by the motor Hall encoder, and finally the real-time rate of a current single unmanned vehicle and the running track of the integrated single unmanned vehicle in a local map are calculated.

Thirdly, uploading data acquired by the first laser radar (a 9) and the second laser radar (b 11) to an upper computer through a first raspberry group (a 8) and a second raspberry group (b 8), processing by a cartograph algorithm, smoothing noise errors which are difficult to avoid on hardware, carrying out multi-stack stacking fusion, quickly building a graph, and marking an obstacle and an unexplored complete pseudo boundary. In the process, map Merge nodes in the upper computer can automatically search and subscribe Map topic data issued by two types of unmanned vehicles, receive and carry out a feature point matching algorithm in real time, and fuse Map frameworks built by the two types of vehicles to produce a summary Map with global effect. The Map Merge algorithm can continuously judge and correct the relative coordinates between two types of unmanned vehicles under the condition that the initial coordinate relation of the two types of unmanned vehicles is unknown, so that the two types of unmanned vehicles can confirm the position information mutually, centimeter-level full-space information sharing is realized, and the Map Merge algorithm is used for subsequent global navigation and positioning alignment in a cluster.

Fourth, the RGB-D camera (a 13) additionally equipped on the first type of rescue and relief unmanned vehicle is suitable for transmitting RGB three-channel images, and the images are uploaded to an upper computer through the first raspberry group (a 8). Meanwhile, the upper computer starts an Rtab three-dimensional mapping algorithm, and expands a two-dimensional map into a three-dimensional map with point cloud constructivity under the constraint of a two-dimensional laser radar by utilizing a camera to level a depth view field within 45 degrees, so that a region to be explored can be visually presented in a full-color three-dimensional mode. The second type of energy source guarantee unmanned vehicle has relatively low flexibility due to a large-capacity battery on the vehicle, but also can be accompanied with the first type of rescue and relief unmanned vehicle, and the map building is assisted in the process of work exploration of the second type of energy source guarantee unmanned vehicle so as to ensure the energy source supply and map building efficiency at the same time.

Fig. 6 is a schematic diagram of the overall workflow of the unmanned vehicle cluster, the visual control of the user side issues an instruction, the public network side issues the instruction, the unmanned vehicle needs to calculate the real-time wheel speed and run the alignment program, and the upper computer needs to build the fusion of the graph algorithm and the path planning calculation.

And fifthly, when the first type of rescue and relief unmanned aerial vehicle is low in electric quantity (the preset program is below 20%), a low-electric quantity signal is sent to the upper computer through the first raspberry group (a 8), and the upper computer sends the space coordinates of the unmanned aerial vehicle to be charged to the energy source to ensure the unmanned aerial vehicle which is close to the space coordinates. The energy source of the received instruction ensures that the unmanned vehicles automatically plan an optimal global path between the unmanned vehicles to be charged through the parameters preset by the Move Base node, monitors and updates obstacle information in real time during operation, and acquires a Cost Map to optimize a local path solution. When the distance reaches a rough positioning threshold (the default is that the distance is less than 20cm, the angle deviation of the direction tail to the tail is less than 10 degrees), the second raspberry group (b 8) switches the issuing instruction to the chassis control system and switches the second Arduino MCU (b 5) of the main control board into a precise alignment program.

FIG. 7 is a schematic diagram of the workflow of the uploading end; the Python executes an uploading program, then monitors the running environment, establishes a socket link, judges whether the graph building program is started, if so, judges whether the graph building program is interrupted manually, if not, the socket link is disconnected, and the program is exited; if yes, disconnecting the socket connection, exiting the program, if not, modulating a ros map server library to obtain mapping data, then obtaining other information through a sensor, reading data, calculating the data size, partitioning the data, uploading the data through the established socket link, judging whether the transmission is successful, if yes, returning to judge whether the transmission is interrupted manually, if wrong, disconnecting the socket link, and exiting the program;

FIG. 8 is a schematic diagram of a workflow of a remote host computer; executing the program of the upper computer gui, then establishing a socket link of the server, judging whether the server is started or not, if so, judging whether the user is closed or not, if not, disconnecting the socket link, and exiting the program; and if the user is closed, disconnecting the socket link, exiting the program, if the user is not closed, downloading the picture through an http protocol, acquiring other data through the socket, displaying the data at the qt front end, and finally returning to judge whether the server is opened.

And sixthly, starting two ultrasonic modules (c 2) positioned at the tail of the energy-guaranteeing unmanned vehicle by a second Arduino MCU (b 5) to acquire millimeter-level distance data of the two vehicles. Through the PID algorithm, the energy source can ensure that the unmanned vehicle can automatically adjust the distance and direction of the unmanned vehicle for rescue and relief work. When the absolute data difference of the two ultrasonic modules is within 0.5cm (namely, the angle is smaller than 5 degrees) and the average value is within the range of 5-8cm, the alignment is completed, and the wireless charging system starts to charge the rescue and relief unmanned vehicle.

And seventhly, when receiving an alignment completion signal, the second Arduino MCU (b 5) conducts a loop where the wireless charging system transmitting coil and the 24V second battery (b 7) are located through a relay in the wireless power supply coil assembly, so that the battery supplies power for the transmitting coil module, energy transfer between the transmitting coil and the receiving coil is realized through a magnetic resonance power supply principle, and the wireless receiving coil assembly supplies power for the vehicle-mounted 12V first battery (a 7) of the rescue and relief car through a rectifying circuit and a 12V-to-5V DC-DC stabilized power supply module (a 12).

Eighth, when the rescue and relief unmanned vehicle is fully charged, the first raspberry group (a 8) sends the full-charge marker to the upper computer. After the upper computer issues the topic of stopping charging, the energy source guarantee unmanned vehicle resets the second Arduino MCU (b 5) accurate alignment program in the chassis control system back to the chassis control program, so that the energy source guarantee trolley and the rescue and relief trolley can work continuously.

Claims

1. The cluster unmanned aerial vehicle energy supply system based on the ROS is characterized by comprising two types of ROS unmanned aerial vehicles, wherein a local ROS system algorithm matched with the two types of ROS unmanned aerial vehicles and a cloud server control application;

the first type of unmanned vehicles are rescue and relief unmanned vehicles, the unmanned vehicle is divided into two layers, and the first layer consists of a chassis control system and a battery; the first layer comprises a metal substrate (a 1), and four Mecanum omni-wheels are connected with a 12V motor (a 2); one end of the first logic signal level conversion module (a 3) is connected with two first direct current motor driving modules (a 4), and the other end of the first logic signal level conversion module is connected with the first Arduino MCU (a 5) so as to transmit an interrupt return signal; one end of the first DC voltage reduction module (a 6) is connected with a 12V first battery (a 7), and the other end of the first DC voltage reduction module is connected with a first raspberry group (a 8); the second layer consists of a master control communication system, a map building navigation sensor system and a wireless charging system; the second layer comprises a first raspberry group (a 8), and the first laser radar (a 9) and the RGB-D depth camera (a 13) are connected to the first raspberry group (a 8); the 3D printing wireless charging coil butt joint assembly (a 10) is fixed on the metal substrate; the first magnetic resonance wireless charging module (a 11) is connected to the first battery (a 7) through the DC-DC stabilized power supply module (a 12); the method comprises the steps that an upper computer of a terminal sends instruction information to a first raspberry group (a 8) through a local area network generated by an unmanned vehicle, receives real-time parameters and mapping information uploaded by the upper computer of the terminal, uploads the data to a server, and displays and operates global information through a visual operation interface at a remote control terminal;

the second class of unmanned vehicles are energy-guaranteed unmanned vehicles; the unmanned vehicle is structurally divided into two layers, wherein the first layer consists of a chassis control system and a battery, the layer comprises a special acrylic substrate (b 1), four Mecanum omnidirectional wheels are connected with a 12V motor (b 2), one end of a second logic signal level conversion module (b 3) is connected with two second direct current motor driving modules (b 4), and the other end of the second logic signal level conversion module is connected with a second Arduino MCU (b 5); one end of the second DC voltage reduction module (b 6) is connected with a 24V second battery (b 7), and the other end of the second DC voltage reduction module is connected with a second raspberry group (b 8); one end of the two second DC voltage reduction modules (b 9) is connected with the second battery (b 7), and the other end is connected with the second direct current motor driving module (b 4); the second layer consists of a master control communication system, a map building navigation sensor system and a wireless charging system; the layer comprises a second raspberry group (b 8), and the second laser radars (b 11) are connected to the second raspberry group (b 8); the 3D printing wireless charging coil assembly (b 10) is connected to the second battery (b 7) through the voltage-stabilizing power supply module (b 12); two ultrasonic modules (c 2) are also connected to the 3D printing wireless charging coil assembly (b 10) and used for accurate positioning; the upper computer of the terminal sends instruction information to the second raspberry group (b 8) through a local area network generated by the unmanned vehicle, receives the real-time parameters and the mapping information uploaded by the upper computer of the terminal, further uploads the data to a server, and presents and operates global information through a visual operation interface at a remote control terminal;

2. The method of claim 1, wherein the steps of the method include:

fourthly, an RGB-D camera (a 13) additionally arranged on the first type of rescue and relief unmanned vehicle is suitable for transmitting RGB three-channel images, and the RGB three-channel images are uploaded to an upper computer through a first raspberry group (a 8); meanwhile, the upper computer starts an Rtab three-dimensional mapping algorithm, a camera is utilized to horizontally extend a depth view field within 45 degrees, and a two-dimensional map is expanded into a three-dimensional map with point cloud constructivity under the constraint of a two-dimensional laser radar, so that a region to be explored can be visually presented in a full-color three-dimensional mode; the second type of energy source guarantee unmanned vehicle has relatively low flexibility due to a large-capacity battery on the vehicle, but also can be accompanied with the first type of rescue and relief unmanned vehicle, and the second type of energy source guarantee unmanned vehicle assists in drawing during work exploration so as to ensure energy source supply and drawing efficiency at the same time;

fifthly, when the electric quantity of the first type of rescue and relief unmanned aerial vehicle is low, a low-electric quantity signal is sent to an upper computer through a first raspberry group (a 8), and the upper computer sends the space coordinates of the unmanned aerial vehicle to be charged to the energy source guaranteeing unmanned aerial vehicle with a short distance; the energy source of the received instruction ensures that the unmanned vehicles automatically plan an optimal global path between the unmanned vehicles to be charged through the parameters preset by the Move Base node, monitors and updates barrier information in real time during operation, and acquires a Cost Map to optimize a local path solution; when the distance reaches the coarse positioning threshold, the second raspberry group (b 8) sends a command to the chassis control system, and the second Arduino MCU (b 5) of the main control board is switched into a precise alignment program;

step six, a second Arduino MCU (b 5) starts two ultrasonic modules (c 2) positioned at the tail of the energy-guaranteeing unmanned vehicle to acquire millimeter-level distance data of the two vehicles; through a PID algorithm, the energy source guarantee unmanned vehicle can automatically adjust the distance and direction of the rescue and relief unmanned vehicle, when the absolute data difference of the two ultrasonic modules is within 0.5cm and the average value is within the range of 5-8cm, the alignment is completed, and the wireless charging system starts to charge the rescue and relief unmanned vehicle;

a seventh step, when an alignment completion signal is received, a second Arduino MCU (b 5) conducts a loop where a wireless charging system transmitting coil and a 24V second battery (b 7) are located through a relay in a wireless power supply coil assembly, so that the battery supplies power for a transmitting coil module, energy transfer of the transmitting coil and a receiving coil is realized through a magnetic resonance power supply principle, and the wireless receiving coil assembly supplies power for a vehicle-mounted 12V first battery (a 7) of the rescue and relief car through a rectifying circuit and a 12V-to-5V DC-DC stabilized power supply module (a 12);

eighth, when the unmanned aerial vehicle for rescuing is fully charged, the first raspberry group (a 8) sends a full-charge marker to the upper computer, and after the upper computer issues a topic for stopping charging, the unmanned aerial vehicle for energy source guarantee resets a second Arduino MCU (b 5) accurate alignment program in the chassis control system back to the chassis control program, so that the trolley for energy source guarantee and the trolley for rescuing continue to work;