CN111367285A - Coordinated formation and path planning method for wheeled mobile trolleys - Google Patents
Coordinated formation and path planning method for wheeled mobile trolleys Download PDFInfo
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Abstract
The invention discloses a collaborative formation and path planning method for wheeled mobile trolleys, which realizes real-time one-to-many autonomous communication of intelligent trolleys. The technical scheme is as follows: firstly, under an autonomously built Mecanum wheel moving trolley platform, respectively carrying out movement control on the trolley and processing sensor information through a master controller and a slave controller; then, combining a multi-agent consistency protocol, a collision potential function and a path tracking function to form a formation control rate, and performing data pairing transmission by using a Zigbee wireless communication module to realize the formation control of multiple mobile trolleys; and finally, gradually reaching the child target point by combining a fuzzy control algorithm and an artificial potential field method to complete path planning. The method is mainly applied to the realization research of multi-agent trolley system formation and path planning, and can be applied to the fields of agriculture, industry, military, commerce, surveying and mapping and the like.
Description
Technical Field
The invention relates to the technical field of wireless communication, path planning and embedding, in particular to a method for collaborative formation and path planning of wheeled mobile trolleys.
Background
With the rapid development of computer, communication, electronics and other technologies, the application of robots is also deepened more and more, and the robots penetrate into different application fields, and become an indispensable tool for social development. However, when a single robot performs a task, it is impossible to perform a more complicated task or it takes a lot of time to perform the task in most cases. Researchers use a plurality of agents to form a multi-agent system through a specific algorithm, namely, each agent only has incomplete information and problem solving capability; each intelligent agent in the system has relatively simple functions and limited information collection, processing and communication capabilities, however, after information transmission and interaction among local individuals, the whole system often shows efficient cooperative ability and advanced intelligent level on a group level, so that difficult, complex and high-precision tasks which cannot be completed by a single intelligent agent are realized.
The multi-agent system can be widely applied to the fields of agriculture, industry, military, commerce, mapping and the like, and can bring huge changes to the lives of people.A formation control in the multi-agent system enables the multi-agent system to complete tasks more efficiently, and the formation control mainly realizes ① formation of formation, namely formation of expected formation of initially scattered agents, ② formation maintenance, namely how the multi-agent system maintains the formation of formation in the execution process and recovers disturbed formation under the interference of the outside, and ③ path planning, namely how the multi-agent system avoids collision when meeting static or dynamic obstacles and plans paths.
At present, the multi-mobile robot formation control method can be mainly divided into a behavior-based method, an artificial potential field method, a navigation-following method, a virtual structure method and the like. In order to improve the robustness and safety of the multi-trolley formation control algorithm, uncertain factors such as time delay, communication packet loss, unknown interference and the like in the motion process must be considered. Meanwhile, not only formation maintenance but also collision between the moving vehicles need to be considered during the movement, and because emergencies such as formation change, man-made interference and the like can occur during the movement, a collision prevention strategy is necessary.
The safe collision-free moving path is an important guarantee for completing tasks of the mobile robot, so the path planning method is also a hot problem for researching the mobile robot. Path planning techniques have developed rapidly over the last 30 years, and path planning can be divided into global planning and local planning from the perception of the robot on the environment. The global planning and the local planning have advantages and disadvantages respectively, and when the constructed map information is known and the mobile robot is provided with a sensor to detect the environment information, the advantages of the global planning and the local planning are combined to perform mixed planning. Firstly, a global path is roughly planned by utilizing known global information, the global path is used as a target of local planning, and an original path is corrected in real time in the motion process, so that the method has a good planning effect on a dynamic environment.
When multi-moving-trolley collaborative formation and path planning are carried out in an actual application scene, the traditional method is difficult to meet application requirements due to the characteristics of environment uncertainty, electromagnetic interference, time delay, communication packet loss and the like. Therefore, there is a need to develop a method to effectively adapt to the above-mentioned various environmental uncertainties.
Disclosure of Invention
The following presents a simplified summary of one or more aspects in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements of all aspects nor delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later.
The embodiment of the specification aims to provide a coordinated formation and path planning method for wheeled mobile trolleys, which utilizes the self positioning information of the mobile trolleys, carries out information transmission by building a wireless communication system among a plurality of mobile trolleys, and senses the surrounding environment by means of a sensor module carried on the mobile trolleys, so that the coordinated formation and path planning of the wheeled mobile trolleys are realized, the coordinated formation and path planning method can be suitable for the practical application of a distributed control system, more accords with the practical application scene, and improves the stability of the system.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the invention discloses a coordinated formation and path planning method for wheeled mobile trolleys, which comprises the following steps:
step 1: the platform comprises a controller, a positioning module, a sensor module and a wireless communication module, wherein the controller comprises a master controller and a slave controller, the master controller is used for controlling the movement of the mobile trolley, and the slave controller is used for processing the information of the sensor;
step 2: the wireless communication module is used for communication, the controller is used for receiving and sending the position information of the current trolley, and meanwhile, a multi-agent consistency protocol, a collision potential function and a path tracking function are combined to form a formation control rate so as to complete formation control of a plurality of mobile trolleys;
and step 3: according to the characteristics of the sensor in practical application, the sensor data is processed in different areas; meanwhile, combining the fuzzy control algorithm with the artificial potential field method, calculating the sub-target points through the fuzzy control algorithm, reaching the sub-target points by using the artificial potential field method, and completing the path planning by gradually reaching the sub-target points.
According to an embodiment of the method for collaborative formation and path planning of wheeled mobile vehicles, the method further comprises the following steps: when formation control and path planning are carried out indoors, the current position of the intelligent vehicle is obtained by using a plurality of photoelectric encoders, and the method comprises the following steps: the controller reads the increased numerical value of the photoelectric encoder at intervals of set time to obtain the rotating speed of each Mecanum wheel, the real-time position of the trolley is calculated by utilizing a kinematic model of the mobile trolley, the calculated real-time position of the trolley takes the number of pulses obtained in unit time as a calculation unit, the conversion ratio of the pulses to the actual distance is obtained according to the radius of the used trolley wheel, and finally the actual distance is calculated.
According to one embodiment of the coordinated formation and path planning method for the wheeled mobile trolley, the Mecanum wheel mobile trolley realizes all-directional movement indoors and comprises a hub and rollers, wherein the hub is a main body support of the whole wheel, the rollers are drums installed on the hub, a hub shaft and a roller rotating shaft form an angle of 45 degrees, when the Mecanum wheel rotates, a part of steering force of the wheel is converted to a wheel normal vector by the rollers forming an angle of 45 degrees with a hub bearing, and the mobile trolley constructed by a plurality of Mecanum wheels is utilized to control the rotating speed of each wheel, so that the force generated by the wheel can be finally synthesized into a resultant vector in any horizontal direction, and the movement of the mobile trolley in any direction is ensured.
According to one embodiment of the coordinated formation and path planning method for wheeled mobile trolleys, a main controller receives processed sensor data; the wireless communication module realizes information receiving and sending; orthogonal decoding is carried out on the photoelectric encoders to obtain the position of the current trolley; the main controller obtains the expected state through the control decision and outputs a control signal to regulate the speed of the mobile trolley, wherein the wireless communication module is an XBEE module.
According to an embodiment of the coordinated formation and path planning method for wheeled mobile trolleys, wireless transmission of information among a plurality of mobile trolleys is achieved through the wireless communication module, a sending end of the wireless communication module can send information to a plurality of targets, a receiving end of the wireless communication module can receive the information of the plurality of targets, and the motion state of each related mobile trolley is obtained through receiving and sending of the main controller, wherein the wireless communication module is an XBEE module.
According to one embodiment of the coordinated formation and path planning method of the wheeled mobile vehicle, an XBEE module in a wireless network is configured into a coordinator, a router and a terminal, wherein the coordinator is responsible for establishing a network and selecting a working frequency band, and only one coordinator is allowed to exist in one network; the router is responsible for transmitting information and allowing the sub-equipment to join the network; the terminal is only responsible for receiving and transmitting information; therefore, a network topology among the trolleys is established, the network topology is composed of a coordinator and a plurality of routers, wherein the coordinator is connected with an upper computer, each mobile trolley is provided with one router, and the communication topology among the routers and the coordinator is connected according to actual requirements.
According to one embodiment of the coordinated formation and path planning method for the wheeled mobile trolleys, the laser ranging radar is used indoors to acquire surrounding information, 360-degree all-dimensional laser ranging scanning is carried out within a set radius range of a two-dimensional plane, plane point cloud map information of the space where the laser ranging scanning is located is generated, and then the path planning of the mobile trolleys is achieved through a local planning algorithm.
According to one embodiment of the coordinated formation and path planning method for the wheeled mobile trolley, the laser ranging radar adopts a triangular ranging technology, ranging operation with fixed frequency is executed every second, the radar transmits modulated infrared laser signals, reflected light generated by the laser signals is received by the visual acquisition system after the infrared laser signals irradiate on a target object, the distance value between the target object and the laser radar is resolved in real time and then is output from the communication interface, and meanwhile, the laser detection device rotates under the traction of the motor belt, so that scanning perception of the surrounding external environment is realized.
According to one embodiment of the coordinated formation and path planning method for the wheeled mobile trolleys, the total number of the built Mecanum wheeled mobile trolleys is less than or equal to 5.
Compared with the existing common main communication technology Wi-Fi and Bluetooth, the ZigBee wireless communication technology has the advantages of simple structure, stable communication, lower power than Wi-Fi, one-to-many communication which cannot be realized by Bluetooth, and capability of realizing formation and path planning of a plurality of trolleys.
Drawings
The above features and advantages of the present disclosure will be better understood upon reading the detailed description of embodiments of the disclosure in conjunction with the following drawings. In the drawings, components are not necessarily drawn to scale, and components having similar relative characteristics or features may have the same or similar reference numerals.
FIG. 1 is a system module composition and communication relationship for a single wheeled mobile cart;
FIG. 2 is a schematic diagram of a network communication topology of a plurality of wheeled mobile carts;
fig. 3 is a schematic data processing diagram of a laser radar carried by a wheeled mobile trolley, wherein a gray area indicated by 1 is a data effective area, and a slash area indicated by 2 is a data locking area;
FIG. 4 is a flow chart of the software architecture of the master controller and the sensor data processing slave controller.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. It is noted that the aspects described below in connection with the figures and the specific embodiments are only exemplary and should not be construed as imposing any limitation on the scope of the present invention.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
The invention is described in further detail below with reference to the figures and specific examples. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
The embodiment provides a coordinated formation and path planning method for wheeled mobile trolleys, wherein 5 wheeled mobile trolleys automatically run in a certain formation form, and a detection system comprises a plurality of measurement units and can detect the motion state and the surrounding environment information of the current mobile trolley to complete path planning based on local information.
As shown in fig. 1, in order to implement formation movement and path planning for a plurality of mecanum wheel mobile dollies, a mecanum wheel mobile dolly platform is first required to be built, which includes five mobile dollies, and the mobile dolly platform has the following four modules in consideration of the functions required for implementing formation movement and path planning: the controller is used for processing the sensor information and the communication information and making a control decision on the mobile trolley; the positioning module is used for acquiring the position of the mobile trolley; the wireless communication module is used for realizing communication between the mobile trolleys and the upper computer; and the sensor module is used for detecting the environmental information in real time and providing environmental perception capability for the path planning algorithm. The controller is divided into a master controller and a slave controller. The master controller and the slave controller adopt STM32 microcontrollers, and the universal timer of the STM32 microcontrollers has powerful functions and has a counter mode, a PWM mode, an encoder interface mode and the like. The PWM mode can output multiple paths of PWM signals with different frequencies and different duty ratios, so that the rotating speed of a motor of the wheel type moving trolley is controlled. The encoder interface mode supports an incremental (orthogonal) encoder circuit for positioning, can be directly connected with a photoelectric encoder on a motor shaft, and counts signals by capturing signals of an orthogonal encoder A, B on a pin, so that the measurement of the rotating speed and the steering of a driving wheel of the control travelling trolley is realized.
The controller STM32 primarily accomplishes four parts of operation: receiving the processed sensor data through a UART; the UART transmits and receives information to and from a wireless communication module (in this embodiment, the wireless communication module is, for example, an XBEE module); carrying out orthogonal decoding on the four encoders to obtain the positions of the encoders; and obtaining an expected state through a control decision, and outputting PWM (pulse width modulation) through a timer to regulate the speed of the direct current motor.
After the building is finished, in the second step, wireless communication is carried out by using a wireless communication module XBEE, the position information of the current trolley is received and sent by using a serial port of the controller, and meanwhile, a formation control rate is formed by combining a multi-agent consistency protocol, a collision potential function and a path tracking function, so that formation control of a plurality of mobile trolleys is finished.
The formation control rate of the plurality of moving trolleys is as follows:
u(t)＝uf(t)+ua(t)+ut(t) (1)，
wherein u isf(t) is a multi-agent coherence protocol item, ua(t) is an inter-car collision avoidance potential field function term, ut(t) is a path tracing function term.
① Multi-agent coherence protocol uf(t) is defined as follows:
wherein
Control rate formed for dolly j to dolly i, aijUsed for describing the connection relationship between any two trolleys,
in order to move the position of the trolley i,
for relatively moving the carriages piThe fixed offset of (a), from the above equation, u is obtained when the traveling cars form a formationf(t)＝0。
② anti-collision potential field function term ua(t) is defined as follows:
wherein
Proportional coefficient η for the rate of control of the potential field formed by dolly j on dolly ij＞0，RaFor safe collision distance, ρaIs the maximum radius of influence of the obstacle and 0 < rhoa＜Ra，dijAnd (t) is the distance between the moving trolley i and the moving trolley j. From the above formula, it can be obtained that the moving car-to-car distance is less than RaThe term function will work to avoid collision, as the distance gets smaller,
will tend to be infinite. When in use
The formation will not present a collision risk.
③ Path tracing function term ut(t) is defined as follows:
wherein
Control Rate for virtual leader on Mobile Car i, βiThe definition is as follows:
wherein c isiFor constants greater than zero, equation (9) ensures that there is at least one mobile car that can obtain information of the virtual leader. When u istWhen (t) is 0, it means that the mobile cart capable of receiving the virtual leader information can completely follow the desired trajectory.
As shown in fig. 2, in the fleet control, the mecanum wheel moving vehicles need to communicate with each other in real time, and the communication needs to satisfy the following two requirements: the sending end can send information to a plurality of targets; the receiving end can receive information of a plurality of targets. According to the requirements, communication performance, cost and other factors, an XBEE module in ZigBee manufactured by DIGI company is selected. The XBEE module is a ZigBee module which embeds a ZigBee protocol into a module Flash, already comprises all peripheral circuits and a complete protocol stack, and can be immediately used. The XBEE module is compact in hardware and small in size, and comprises an ADC (analog to digital converter), a DAC (digital to analog converter), a comparator, a plurality of IO (input/output) interfaces I2C and the like. The software internally comprises a complete ZigBee protocol stack, has a configuration tool X-CTU of a PC end, adopts a serial port and a user product for communication, and can configure network topology parameters such as transmitting power, channels and the like for the module.
The implementation example uses a network topological graph to establish a wireless communication network, and comprises a coordinator and five routers, wherein the coordinator is connected with an upper computer, one router is arranged on each Mecanum wheel moving trolley, and the communication topology between the routers and the coordinator is connected according to actual requirements. The wireless communication network is established through the XBEE module, so that each mobile car can transmit the real-time information of the mobile car according to the established communication topology, and the completion of the formation task of a plurality of mobile cars can be guaranteed.
After the formation control is finished, thirdly, processing the sensor data in a partition mode according to the characteristics of the sensor in practical application; meanwhile, combining the fuzzy control algorithm with the artificial potential field method, calculating the sub-target points through the fuzzy control algorithm, reaching the sub-target points by using the artificial potential field method, and completing the path planning by gradually reaching the sub-target points.
The calculation of the sub-target points in the fuzzy control algorithm can be represented by the following model:
y＝f(u) (10)
where u is the input u ═ D1,D2,D3,D4}，Di(i ═ 1,2,3,4) is obstacle distance information of four regions from right to left, and the near, medium, and far obstacle distances are expressed in three fuzzy languages { N, M, F }. And y is output y ═ ρ, θ }, ρ is the distance from the target point to the mobile trolley, and θ is the included angle between the target point and the moving direction of the mobile trolley. Three fuzzy languages of { N, M, F } are used to represent the distance p between the target point and the mobile vehicle. By { theta }1,θ2,θ3,θ4,θ5,θ6And six fuzzy languages represent the included angle between the target point and the moving direction of the mobile trolley. Both inputs and outputs use trigonometric functions as membership functions.
As shown in fig. 3, further, path planning needs to obtain global information in advance or obtain surrounding information during a movement process, so that a two-dimensional laser radar is used to perform 360-degree omnidirectional laser ranging scanning within a set radius (e.g., 6 meters) of a two-dimensional plane, and generate plane point cloud map information of a space where the two-dimensional laser radar is located.
The method comprises the steps of enabling a laser radar to rotate for one circle to generate more than 500 scattered points, enabling adjacent angles of the scattered points to be smaller than 1 degree, simultaneously, acquiring data information larger than two circles for obtaining reliable data information, and conducting superposition analysis processing to prevent missing points from occurring when detection occurs, and finding that when laser radar data is processed, several problems can occur if repulsive force generated by all obstacle points is used for superposition, wherein ① data volume is too large and calculation is large, ② obstacle size is large, the repulsive force is greatly affected (the larger the obstacle is, the more scattered points are generated when detection is performed, the larger the repulsive force is), therefore, when laser radar data is processed, characteristics of an artificial potential field method and actual analysis need to be combined, in the embodiment, a region 120 degrees left and right in the advancing direction is used as an effective data region (240 degrees are counted), a gray region is an effective region, problems caused by the fact that the data volume is too large and the same obstacle is detected are too much are simultaneously, if the obstacle has the repulsive force field range and the effective region, the nearest obstacle point is selected for calculation, the obstacle region is locked, the left and right and the obstacle region is locked without the gray region, and the remaining obstacle points are selected continuously according to the principle, and the principle of no obstacle is not locked.
When the laser radar is used for sensing the environmental information, the measurement data are continuously output from the communication interface, and in order to prevent the occupation of a large number of controller resources, a slave controller STM32 which is low in cost and proper in performance is added to specially process the sensor data. In the data processing process, data is processed every 500ms and transmitted to the main controller through the UART.
As shown in fig. 4, the main controller employs STM32, which has a large memory space and more pins responsible for receiving and transmitting information (including neighbor information and lidar data), encoder quadrature decoding, car chassis control and control decision, and the like. And the chassis control reads the encoder data in a period of 5ms, calculates the current motion state and controls the motion state. In the formation control, self information needs to be sent to the neighbor, and wireless transmission is carried out through the XBEE module in a cycle of every 25 ms.
The slave controller adopts STM32 to be responsible for utilizing the laser radar sensor to carry out environment perception, and the laser radar processing data uses every 500ms as the cycle, reads 1000 groups of data (the scanning number of turns is greater than 2 circles) each time, handles and sends through the UART according to the path planning algorithm demand simultaneously.
In the example, a virtual leader is set to plan and send the expected track, MATLAB is used as an upper computer, the MATLAB is connected with a coordinator in an XBEE network through a serial port to send the expected track in a period of 5ms, and one XBEE is placed on each trolley and set to be in a router mode to send and receive information.
The foregoing is merely a preferred embodiment of the invention and is not intended to limit the scope of the invention, which is defined by the claims appended hereto, and any other technical entity or method that is encompassed by the claims as broadly defined herein, or equivalent variations thereof, is contemplated as being encompassed by the claims.
Claims (9)
1. A coordinated formation and path planning method for wheeled mobile trolleys comprises the following steps:
step 1: the platform comprises a controller, a positioning module, a sensor module and a wireless communication module, wherein the controller comprises a master controller and a slave controller, the master controller is used for controlling the movement of the mobile trolley, and the slave controller is used for processing the information of the sensor;
step 2: the wireless communication module is used for communication, the controller is used for receiving and sending the position information of the current trolley, and meanwhile, a multi-agent consistency protocol, a collision potential function and a path tracking function are combined to form a formation control rate so as to complete formation control of a plurality of mobile trolleys;
and step 3: according to the characteristics of the sensor in practical application, the sensor data is processed in different areas; meanwhile, combining the fuzzy control algorithm with the artificial potential field method, calculating the sub-target points through the fuzzy control algorithm, reaching the sub-target points by using the artificial potential field method, and completing the path planning by gradually reaching the sub-target points.
2. The method for collaborative formation and path planning for wheeled mobile carts of claim 1, further comprising: when formation control and path planning are carried out indoors, the current position of the intelligent vehicle is obtained by using a plurality of photoelectric encoders, and the method comprises the following steps: reading the value increased by the photoelectric encoder at intervals of a set fixed time by the controller to obtain the rotating speed of each Mecanum wheel, and calculating the real-time position of the trolley by utilizing a kinematic model of the mobile trolley; the calculated real-time position of the trolley is calculated by taking the number of pulses obtained in unit time as a calculation unit, obtaining a conversion ratio of the pulses to the actual distance according to the radius of the used trolley wheel, and finally calculating the actual distance.
3. The method as claimed in claim 2, wherein the Mecanum wheel moving vehicle is moved in all directions in the room, the Mecanum wheel is composed of a hub and rollers, wherein the hub is a main body frame of the whole wheel, the rollers are drums mounted on the hub, the hub axis is 45 ° to the roller rotating axis, when the Mecanum wheel rotates, a part of the steering force of the wheel is converted to the normal vector of the wheel by the rollers which are 45 ° to the hub bearing, the moving vehicle constructed by using a plurality of Mecanum wheels is controlled by the speed of rotation of each wheel, so that the force generated by the wheel is finally synthesized into the resultant vector of any horizontal direction, thereby ensuring the movement of the moving vehicle in any direction.
4. The method for collaborative formation and path planning for wheeled mobile carts of claim 1 wherein the master controller receives sensor data from a warp; the wireless communication module realizes information receiving and sending; orthogonal decoding is carried out on the photoelectric encoders to obtain the position of the current trolley; the main controller obtains the expected state through the control decision and outputs a control signal to regulate the speed of the mobile trolley, wherein the wireless communication module is an XBEE module.
5. The method for collaborative formation and path planning of wheeled mobile carts as claimed in claim 1, wherein the wireless communication module is used to realize wireless transmission of information between a plurality of mobile carts, so that a sending end of the wireless communication module can send information to a plurality of carts, and a receiving end of the wireless communication module can receive information sent by a plurality of carts, and obtain the motion status of each related mobile cart by receiving and sending of the main controller, wherein the wireless communication module is an XBEE module.
6. The method for collaborative formation and path planning of wheeled mobile carts as claimed in claim 5, wherein XBEE modules in a wireless network are configured into three types of coordinator, router and terminal, wherein the coordinator is responsible for establishing a network, selecting an operating frequency band, and only one coordinator is allowed to exist in one network; the router is responsible for transmitting information and allowing the sub-equipment to join the network; the terminal is only responsible for receiving and transmitting information; therefore, a network topology among the trolleys is established, the network topology is composed of a coordinator and a plurality of routers, wherein the coordinator is connected with an upper computer, each mobile trolley is provided with one router, and the communication topology among the routers and the coordinator is connected according to actual requirements.
7. The method as claimed in claim 1, wherein the laser ranging radar is used indoors to obtain surrounding information, the laser ranging scanning is performed in 360 degrees in all directions within a set radius of a two-dimensional plane, and planar point cloud map information of a space where the laser ranging scanning is located is generated, thereby realizing path planning of the mobile cart by using a local planning algorithm.
8. The method for collaborative formation and path planning of wheeled mobile dollies according to claim 7, wherein a laser ranging radar adopts a triangulation ranging technique, performs a ranging operation with a fixed frequency per second, emits a modulated infrared laser signal, receives reflected light generated by the laser signal by a vision acquisition system after irradiating a target object, resolves a distance value between the target object and the laser radar in real time, outputs the resolved distance value from a communication interface, and simultaneously rotates a laser detection device under the traction of a motor belt, thereby realizing scanning and sensing of the surrounding external environment.
9. The method for collaborative formation and path planning of wheeled mobile carts of claim 1, wherein the total number of built mecanum wheeled mobile carts is less than or equal to 5.
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