CN111367285B - Wheeled mobile trolley cooperative formation and path planning method - Google Patents
Wheeled mobile trolley cooperative formation and path planning method Download PDFInfo
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Abstract
The invention discloses a wheel type mobile trolley cooperative formation and path planning method, which realizes real-time one-to-many autonomous communication of an intelligent trolley. The technical proposal is as follows: firstly, under the condition of independently constructing a Mecanum wheel mobile trolley platform, respectively carrying out mobile control and sensor information processing of the trolley through a master-slave controller; then, a multi-agent consistency protocol, a collision potential function and a path tracking function are combined to form formation control rate, and a Zigbee wireless communication module is utilized for carrying out data pairing transmission so as to realize multi-mobile-trolley formation control; finally, gradually reaching the sub-target point by combining a fuzzy control algorithm with an artificial potential field method to complete path planning. The invention 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, mapping and the like.
Description
Technical Field
The invention relates to the technical fields of wireless communication, path planning and embedding, in particular to a wheel type mobile trolley cooperative formation and path planning method.
Background
With the leap development of computer, communication, electronics and other technologies, robots are applied more deeply and penetrate into different application fields, and become an indispensable tool for social development. However, single-body robots cannot perform more complex tasks or require a lot of time to perform them in most cases. Researchers form a multi-agent system by utilizing a plurality of agents 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 collecting, processing and communication capabilities, however, after information transmission and interaction among local individuals, the whole system always shows high-efficiency cooperative capability 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, business, mapping and the like, and can bring great changes to the life of people. In a multi-agent system, formation control enables the multi-agent system to more efficiently complete tasks, and the formation control mainly realizes the following three parts: (1) formation, i.e., forming initially discrete intelligent agents into a desired formation; (2) form holding, namely how the multi-agent system holds the forms in the execution process and how the disturbed forms are recovered under the interference of the outside; (3) and path planning, namely, how the multi-agent system avoids collision when encountering static or dynamic obstacles, and planning the path.
At present, the multi-mobile robot formation control method can be mainly classified into a behavior-based method, an artificial potential field method, a pilot-following method, a virtual structure method and the like. In order to improve the robustness and safety of the multi-mobile-trolley formation control algorithm, uncertainty factors such as time delay, communication packet loss, unknown interference and the like in the motion process must also be considered. Meanwhile, not only the formation maintenance but also the collision between the mobile trolleys need to be considered in the movement process, and emergency situations such as formation transformation, artificial interference and the like can possibly occur in the movement process, so that a conflict prevention strategy is necessary.
The safe collision-free moving path is an important guarantee for completing the task of the mobile robot, so that the path planning method is also a hot spot problem of the mobile robot. Path planning techniques have evolved rapidly over the past 30 years, and path planning can be divided into global planning and local planning from the degree of perception of the environment by the robot. Global planning and local planning each have advantages and disadvantages, and hybrid planning is performed by combining the advantages of global planning and local planning when the constructed map information is known and the mobile robot is equipped with sensors to detect environmental information. Firstly, a global path is roughly planned by using known global information, the global path is used as a target of local planning, and the 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 the multi-mobile-trolley cooperative formation and path planning are performed in an actual application scene, the traditional method is difficult to meet application requirements due to the characteristics of environmental uncertainty, electromagnetic interference, time delay, communication packet loss and the like. Therefore, there is a need to develop a method to effectively accommodate 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 purpose of the embodiment of the specification is to provide a wheel type mobile trolley cooperative formation and path planning method, which utilizes the positioning information of the mobile trolley, performs information transmission by setting up 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, thereby realizing the cooperative formation and path planning of the plurality of wheel type mobile trolleys, being applicable to the practical application of a distributed control system, being more in line with the practical application scene and improving the stability of the system.
The technical scheme adopted for solving the technical problems is as follows:
the invention discloses a wheel type mobile trolley cooperative formation and path planning method, which comprises the following steps:
step 1: independently constructing a Mecanum wheel mobile trolley platform, wherein the platform comprises a controller, a positioning module, a sensor module and a wireless communication module, 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 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, the multi-agent consistency protocol, the collision potential function and the path tracking function are combined to form a formation control rate, so that formation control of a plurality of mobile trolleys is completed;
step 3: according to the characteristics of the sensor in practical application, carrying out regional processing on the sensor data; and simultaneously, combining a fuzzy control algorithm with an artificial potential field method, calculating a sub-target point through the fuzzy control algorithm, reaching the sub-target point by using the artificial potential field method, and completing path planning by gradually reaching the sub-target point.
According to an embodiment of the wheeled mobile trolley cooperative formation and path planning method of the present invention, the method further comprises: 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 value added by the photoelectric encoder every interval set time to obtain the rotating speed of each Mecanum wheel, calculates the real-time position of the trolley by utilizing the kinematic model of the movable trolley, and the calculated real-time position of the trolley takes the number of pulses obtained in unit time as a calculation unit, obtains the conversion ratio of the pulses to the actual distance according to the radius of the used trolley wheel, and finally carries out actual distance dissociation calculation.
According to the embodiment of the wheel type movable trolley cooperative formation and path planning method, the movable trolley with the Mecanum wheels realizes omnibearing movement indoors, the Mecanum wheels consist of hubs and rollers, wherein the hubs are main body supports of the whole wheels, the rollers are drum-shaped objects arranged on the hubs, the hub shafts form an angle of 45 degrees with the rotating shafts of the rollers, when the Mecanum wheels rotate, a part of steering force of the wheels is converted into normal vectors of the wheels by the rollers forming an angle of 45 degrees with the hub bearings, and the movable trolley with the structure of a plurality of Mecanum wheels can finally synthesize resultant force vectors in any horizontal direction by controlling the rotating speed of each wheel, so that the movement of the movable trolley in any direction is ensured.
According to one embodiment of the wheeled mobile cart co-formation and path planning method of the present invention, a master controller receives processed sensor data; information receiving and transmitting are realized with the wireless communication module; performing orthogonal decoding on a plurality of photoelectric encoders to obtain the position of the current trolley; the main controller obtains a desired state through a 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 the embodiment of the wheel type mobile trolley cooperative formation and path planning method, the wireless communication module is used for realizing wireless transmission of information among a plurality of mobile trolleys, so that a transmitting end of the wireless communication module can transmit 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 relevant mobile trolley is obtained through receiving and transmitting of a main controller, wherein the wireless communication module is an XBEE module.
According to one embodiment of the wheeled mobile trolley cooperative formation and path planning method, an XBEE module in a wireless network is configured into three types of a coordinator, a router and a terminal, wherein the coordinator is responsible for establishing the network, selecting a working frequency band, and only one coordinator is allowed to exist in one network; the router is responsible for transferring information and allowing the sub-devices to join the network; the terminal is only responsible for receiving and transmitting information; the network topology among the plurality of trolleys is established, the network topology consists of a coordinator and a plurality of routers, wherein the coordinator is connected with an upper computer, each mobile trolley is provided with a router, and the communication topology between the routers and the coordinator is connected according to actual requirements.
According to the embodiment of the wheel type mobile trolley cooperative formation and path planning method, surrounding information is acquired indoors by using a laser ranging radar, 360-degree omnibearing laser ranging scanning is performed in a set radius range of a two-dimensional plane, plane point cloud map information of a space is generated, and path planning of the mobile trolley is realized by using a local planning algorithm.
According to the embodiment of the wheel type mobile trolley cooperative formation and path planning method, the laser ranging radar adopts a triangular ranging technology, ranging operation with fixed frequency is carried out every second, the radar emits modulated infrared laser signals, reflected light generated by the laser signals is received by the vision acquisition system after the radar irradiates a target object, the distance value between the target object and the laser radar is output from the communication interface after being resolved in real time, and meanwhile, the laser detection device rotates under the traction of the motor belt, so that the scanning perception of the surrounding external environment is realized.
According to the embodiment of the wheel type movable trolley cooperative formation and path planning method, the sum of the number of the built Mecanum wheel movable trolleys is less than or equal to 5.
Accordingly, compared with the existing common mainstream communication technology Wi-Fi and Bluetooth, the method for collaborative formation and path planning of the wheeled mobile trolley provided by the invention has the advantages of simple structure, stable communication, lower power than Wi-Fi, realization of one-to-many communication which cannot be realized by Bluetooth, and realization of formation and path planning of multiple trolleys.
Drawings
The above features and advantages of the present invention will be better understood after reading the detailed description of embodiments of the present disclosure in conjunction with the following drawings. In the drawings, the components are not necessarily to scale and components having similar related features or characteristics may have the same or similar reference numerals.
FIG. 1 is a diagram of the system module composition and communication relationship of a single wheeled mobile cart;
FIG. 2 is a schematic diagram of a network communication topology for a plurality of wheeled mobile carts;
fig. 3 is a schematic view of laser radar data processing carried by a wheeled mobile trolley, wherein a gray area denoted by 1 is a data effective area, and a diagonal area denoted 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 drawings and the specific embodiments. It is noted that the aspects described below in connection with the drawings and the specific embodiments are merely exemplary and should not be construed as limiting the scope of the invention in any way.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present 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 will be described in further detail with reference to the drawings and the specific examples. The present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following examples.
The embodiment provides a wheel type mobile trolley cooperative formation and path planning method, 5 wheel type mobile trolleys automatically travel in a certain formation, and a detection system comprises a plurality of measurement units, can detect the motion state and surrounding environment information of the current mobile trolleys and finish 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 wheels, a mecanum wheel mobile trolley platform needs to be built first, and includes five mobile trolleys, and functions required for implementing formation movement and path planning are considered, so the mobile trolley platform is provided with the following four modules: the controller processes the sensor information and the communication information and makes a control decision on the mobile trolley; the positioning module is used for acquiring the self 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 detects the environmental information in real time and provides 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 has powerful functions and 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 motor rotating speed of the wheeled trolley is controlled. The encoder interface mode supports incremental (quadrature) encoder circuits for positioning, which can be directly connected with the photoelectric encoder on the motor shaft, and counts the signals through the quadrature encoder A, B on the capture pin, thereby realizing the measurement of controlling the rotation speed and the steering of the driving wheel of the mobile trolley.
The controller STM32 mainly implements the four parts of operations: receiving the processed sensor data through the UART; receiving and transmitting information through a UART and a wireless communication module (in the embodiment, the wireless communication module is an XBEE module for example); performing orthogonal decoding on the four encoders to obtain the positions of the four encoders; and obtaining an expected state through a control decision, and outputting PWM through a timer to regulate the speed of the direct current motor.
After the construction is completed, the second step of wireless communication is carried out by using the wireless communication module XBEE, the position information of the current trolley is received and sent by using the serial port of the controller, and meanwhile, the formation control rate is formed by combining a multi-agent consistency protocol, a collision potential function and a path tracking function, so that the formation control of a plurality of mobile trolleys is completed.
The formation control rate of the plurality of mobile trolleys is as follows:
u(t)＝u f (t)+u a (t)+u t (t) (1)，
wherein u is f (t) is a multi-agent coherence protocol item, u a (t) is a potential field function term of the small workshop anticollision, u t And (t) is a path tracking function term.
(1) Multi-agent coherence protocol item u f (t) is defined as follows:
wherein the method comprises the steps of
Control rate, a, formed for mobile cart j to mobile cart i ij For describing the connection between any two carts,/->
For moving the position of trolley i +.>
For relatively moving trolley p i From the above, u when the dolly forms a formation f (t)＝0。
(2) Anti-collision potential field function term u a (t) is defined as follows:
wherein the method comprises the steps of
For the control rate of potential field formed by the moving trolley j to the moving trolley i, the positive proportionality coefficient eta j ＞0，R a For safe collision distance ρ a Is the maximum radius of influence of the obstacle and 0 < ρ a ＜R a ，d ij And (t) is the distance between the mobile trolley i and the mobile trolley j. From the above, the distance between movable small workshops is smaller than R a The function will function to avoid collision phenomena when the distance is smaller and smaller>
Will tend to infinity. When->
When the formation will not have a collision risk.
(3) Path tracking function term u t (t) is defined as follows:
wherein the method comprises the steps of
Control rate of the mobile trolley i for the virtual leader, beta i The definition is as follows:
wherein c i For constants greater than zero, equation (9) ensures that there is at least one mobile cart available to obtain information of the virtual leader. When u is t When (t) =0, it is explained that the mobile cart capable of receiving the virtual leader information can completely follow the desired trajectory.
As shown in fig. 2, in the formation control, the mecanum wheel mobile trolleys need to communicate with each other in real time, and the following two requirements are met for the communication: the transmitting end can transmit information to a plurality of targets; the receiving end may receive information of a plurality of targets. According to the requirements and the factors such as communication performance, cost and the like, an XBEE module in the ZigBee production of DIGI company is selected. The XBEE module is a ZigBee module which is built in a module Flash by a ZigBee protocol, and comprises all peripheral circuits and complete protocol stacks, so that the module can be immediately put into use. The XBEE module has compact hardware and small volume, and comprises an ADC, a DAC, a comparator, a plurality of IO, I2C interfaces and the like. The software contains a complete ZigBee protocol stack, has a configuration tool X-CTU at a PC end, adopts a serial port to communicate with a user product, and can configure network topology parameters such as transmitting power, channels and the like for the module.
The implementation example uses a network topology diagram 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 placed on each Mecanum wheel mobile 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 trolley can transmit real-time information of the mobile trolley according to the established communication topology, and the completion of the formation tasks of a plurality of mobile trolleys can be ensured.
After formation control is completed, performing regional processing on sensor data according to the characteristics of the sensor in actual application; and simultaneously, combining a fuzzy control algorithm with an artificial potential field method, calculating a sub-target point through the fuzzy control algorithm, reaching the sub-target point by using the artificial potential field method, and completing path planning by gradually reaching the sub-target point.
The calculation of the child target point in the fuzzy control algorithm can be represented by the following model:
y＝f(u) (10)
where u is the input u= { D 1 ,D 2 ,D 3 ,D 4 }，D i (i=1, 2,3, 4) is obstacle distance information of four areas from right to left, and represents the near, middle, and far of the obstacle distance in three ambiguous languages { N, M, F }. Where y is the output y= { ρ, θ }, ρ is the distance from the target point to the moving trolley, and θ is the angle between the target point and the moving direction of the moving trolley. The three ambiguous languages { N, M, F } are used to represent the distance ρ of the target point from the mobile cart, the middle and the far. By { θ ] 1 ,θ 2 ,θ 3 ,θ 4 ,θ 5 ,θ 6 Six ambiguous languages represent the angle between the target point and the direction of motion of the mobile cart. Both the input and the output use a trigonometric function as the membership function.
As shown in fig. 3, further, the path planning needs to obtain global information in advance or obtain surrounding information in the motion process, so that a two-dimensional laser radar is used to realize 360-degree omnibearing laser ranging scanning within a set radius (for example, 6 meters) range of a two-dimensional plane, and generate plane point cloud map information of a space where the laser radar is located.
The number of scattered points generated by the rotation of the laser radar for one circle is more than 500, and the adjacent angle of the scattered points is less than 1 degree. Meanwhile, in order to obtain reliable data information, data information more than two weeks is obtained to carry out superposition analysis processing, so that missing points are prevented from occurring during detection. When processing lidar data, it was found that several problems occur if the repulsive forces generated by all the obstacle points are used for superposition: (1) the data volume is too large, the calculation is large, and (2) the size of the obstacle has a great influence on the repulsive force (the larger the obstacle is, the more scattered points are generated by detection, and the larger the repulsive force is). Therefore, it is necessary to combine the characteristics of the artificial potential field method and the actual analysis in processing the lidar data. In this embodiment, the 120 ° area on the left and right sides in the forward direction is used as the effective data area (240 ° area in total), and the gray area is the effective area. Meanwhile, aiming at the problems caused by overlarge data size and too many detection points of the same obstacle, if the obstacle exists in the repulsive force field range and the effective area, selecting the nearest obstacle point for repulsive force calculation, locking the area of 30 degrees around the point, and not selecting the obstacle point any more, wherein the rest areas continue to select the obstacle point according to the principle until the gray unlocking area does not exist the obstacle point or does not exist the gray unlocking area.
When the laser radar is used for sensing environment information, measurement data is continuously output from the communication interface, and in order to prevent occupying a large amount of resources of the controller, a slave controller STM32 with low cost and proper performance is adopted to specially process the sensor data. During data processing, data is processed every 500ms and sent to the host controller through the UART.
As shown in fig. 4, the main controller adopts STM32, which has larger memory space and more pins for receiving and transmitting information (including neighbor information and laser radar data), orthogonal decoding of the encoder, control of the chassis of the trolley, control decision and the like. The chassis control reads the encoder data with the period of 5ms, calculates the current motion state and controls. In formation control, self information needs to be sent to a neighbor, and wireless transmission is carried out through the XBEE module every 25ms as a period.
The slave controller adopts STM32 to be responsible for using a laser radar sensor to sense the environment, laser radar processing data takes every 500ms as a period, 1000 groups of data are read each time (the scanning circle number is more than 2), and meanwhile, the data are processed according to the requirement of a path planning algorithm and are sent through a UART.
In the example, a virtual leader is set to plan and send an expected track, MATLAB is adopted as an upper computer, a coordinator in an XBEE network is connected through a serial port to send the expected track in a period of 5ms, and an XBEE is placed on each trolley and set into a router mode to send and receive information.
The foregoing description is only illustrative of the preferred embodiments of the present invention and is not intended to limit the scope of the invention, which is defined broadly in the appended claims, and any person skilled in the art to which the invention pertains will readily appreciate that many modifications, including those that fall within the metes and bounds of the claims, or equivalence of such metes and bounds thereof.
Claims (9)
1. A method for collaborative formation and path planning of wheeled mobile carts, the method comprising the steps of:
step 1: independently constructing a Mecanum wheel mobile trolley platform, wherein the platform comprises a controller, a positioning module, a sensor module and a wireless communication module, 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 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, the multi-agent consistency protocol, the collision potential function and the path tracking function are combined to form a formation control rate, so that formation control of a plurality of mobile trolleys is completed;
step 3: according to the characteristics of the sensor in practical application, carrying out regional processing on the sensor data; meanwhile, a fuzzy control algorithm is combined with an artificial potential field method, calculation of sub-target points is carried out through the fuzzy control algorithm, then the sub-target points are reached through the artificial potential field method, and path planning is completed through gradually reaching the sub-target points;
in step 2, the formation control rates of the plurality of mobile dollies are:
u(t)＝u f (t)+u a (t)+u t (t)，
wherein u is f (t) is a multi-agent coherence protocol item, u a (t) is a potential field function term of the small workshop anticollision, u t (t) is a path tracking function term;
(1) multi-agent coherence protocol item u f (t) is defined as follows:
wherein the method comprises the steps of
Control rate, a, formed for mobile cart j to mobile cart i ij For describing the connection between any two carts,/->
For moving the position of trolley i +.>
For relatively moving trolley p i Is fixed offset of (a);
(2) anti-collision potential field function term u a (t) is defined as follows:
wherein the method comprises the steps of
For the control rate of potential field formed by the moving trolley j to the moving trolley i, the positive proportionality coefficient eta j ＞0，R a For safe collision distance ρ a Is the maximum radius of influence of the obstacle and 0 < ρ a ＜R a ，d ij (t) is the moving trolley i and the movementDistance between the trolleys j;
(3) path tracking function term u t (t) is defined as follows:
wherein the method comprises the steps of
Control rate of the mobile trolley i for the virtual leader, beta i The definition is as follows:
wherein c i For constants greater than zero, equation (9) ensures that there is at least one mobile cart available to obtain information of the virtual leader;
in step 3, the calculation of the sub-target point in the fuzzy control algorithm may be represented by the following model:
y＝f(u)，
where u is the input u= { D 1 ,D 2 ,D 3 ,D 4 }，D i (i=1, 2,3, 4) is obstacle distance information of four areas from right to left, y is output y= { ρ, θ }, ρ is distance from the target point to the moving trolley, θ is included angle between the target point and the moving direction of the moving trolley, three ambiguity languages { N, M, F } are used to represent the distance ρ between the target point and the moving trolley, and { θ }, where 1 ,θ 2 ,θ 3 ,θ 4 ,θ 5 ,θ 6 Six (six)The fuzzy language indicates the included angle between the target point and the moving direction of the mobile trolley.
2. The wheeled mobile cart co-formulation and path planning method 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: the controller reads the value added by the photoelectric encoder every interval setting fixed time, obtains the rotating speed of each Mecanum wheel, and calculates the real-time position of the trolley by utilizing the 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, according to the radius of the used trolley wheel, the conversion ratio of the pulses to the actual distance is obtained, and finally the actual distance is calculated.
3. The method for collaborative formation and path planning for wheeled mobile trolleys according to claim 2, wherein the mobile trolleys with the wheels are moved in all directions indoors, the wheels with the wheels are composed of hubs and rollers, wherein the hubs are main body supports of the whole wheels, the rollers are drum-shaped objects mounted on the hubs, the hub shafts form an angle of 45 degrees with the rotation axes of the rollers, when the wheels with the wheels rotate, a part of steering force of the wheels is converted to normal vectors of the wheels by the rollers forming an angle of 45 degrees with the hub bearings, and the mobile trolleys with the structure of a plurality of wheels with the wheels rotating speed controlled to enable the forces generated by the wheels to be finally combined into resultant force vectors in any horizontal direction, thereby ensuring the movement of the mobile trolleys in any direction.
4. The method of collaborative formation and path planning for wheeled mobile carts of claim 1, wherein a master controller receives sensor data from a process; information receiving and transmitting are realized with the wireless communication module; performing orthogonal decoding on a plurality of photoelectric encoders to obtain the position of the current trolley; the main controller obtains a desired state through a 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 dollies according to claim 1, wherein wireless transmission of information among a plurality of mobile dollies is realized by using a wireless communication module, so that a transmitting end of the wireless communication module can transmit information to the plurality of dollies, a receiving end of the wireless communication module can receive information transmitted by the plurality of dollies, and the motion state of each relevant mobile dolly is obtained through receiving and transmitting of a main controller, wherein the wireless communication module is an XBEE module.
6. The method for collaborative formation and path planning for wheeled mobile vehicles according to claim 5, wherein the XBEE module in the wireless network is configured into three classes of coordinator, router and terminal, wherein the coordinator is responsible for establishing the network, selecting the working frequency band, and only one coordinator is allowed to exist in one network; the router is responsible for transferring information and allowing the sub-devices to join the network; the terminal is only responsible for receiving and transmitting information; the network topology among the plurality of trolleys is established, the network topology consists of a coordinator and a plurality of routers, wherein the coordinator is connected with an upper computer, each mobile trolley is provided with a router, and the communication topology between the routers and the coordinator is connected according to actual requirements.
7. The wheel type mobile trolley cooperative formation and path planning method according to claim 1, wherein surrounding information is acquired indoors by using a laser ranging radar, 360-degree omnibearing laser ranging scanning is performed in a set radius range of a two-dimensional plane, plane point cloud map information of a space is generated, and path planning of the mobile trolley is achieved by means of a local planning algorithm.
8. The method for collaborative formation and path planning for wheeled mobile dollies according to claim 7, wherein the laser ranging radar adopts a triangle ranging technique, ranging operation with fixed frequency is performed every second, the radar emits modulated infrared laser signals, reflected light generated by the laser signals is received by the vision acquisition system after the radar irradiates the target object, the distance value between the target object and the laser radar is calculated in real time and then is output from the communication interface, and the laser detection device rotates under the traction of the motor belt, so that scanning sensing of the surrounding external environment is realized.
9. The method for collaborative formation and path planning for wheeled mobile dollies according to claim 1, wherein the sum of the number of built mecanum wheeled mobile dollies is less than or equal to 5.
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