Inter-machine communication method suitable for strong coupling following type harvesting-unloading cooperative control

Abstract

The invention discloses an inter-machine communication method suitable for strong coupling following type harvesting-unloading cooperative control, which comprises the following steps of: adopting two different communication modes to complement each other, and designing a communication protocol and a data frame receiving and processing method; dead reckoning and communication delay compensation are adopted to obtain a system recursion equation and a measurement matrix of the Kalman filter; establishing a Kalman filter, and providing an inter-machine relative longitudinal distance calculation method to realize real-time acquisition of the position and course of the communication agricultural machine and the dual-machine relative longitudinal distance; data frames are packaged based on a satellite positioning system and an inertial measurement system, and are respectively sent by adopting two different communication modes. According to the method, the problems of data delay, packet loss, blockage, errors and the like in wireless communication can be effectively solved, and the method has short-time discontinuous-point cruising ability, so that the updating frequency of inter-machine communication data can be synchronized with the control frequency, and algorithm support is provided for real-time communication data fusion of various different wireless communication modes.

Description

Technical Field

[0001] The present invention belongs to the technical field of automatic driving operation of agricultural machinery, and specifically relates to an inter-machine communication method suitable for strongly coupled follow-up harvesting-unloading coordinated control. Background Art

[0002] With the acceleration of urbanization and the large-scale migration of rural labor to cities, the agricultural sector is facing an increasingly serious challenge of labor shortage. In response to this trend and to improve agricultural production efficiency, the concept of "full-cycle, all-weather unmanned farms" has emerged and is expected to become one of the key directions for the development of modern agriculture. In the operation process of unmanned farms, the harvesting stage is one of the most important links, which involves the efficient collaboration between harvesting machinery and grain transport vehicles.

[0003] In order to achieve effective coordination between harvesters and grain transport vehicles, especially during the process of grain unloading by harvesters, real-time data exchange between the two is crucial. Especially when grain transport vehicles need to accurately follow harvesters and receive grain, the communication quality between machines directly affects the operating accuracy and stability of the entire system. Therefore, developing a reliable inter-machine communication solution and supporting data processing methods is extremely important for realizing fully automated harvesting operations. Summary of the invention

[0004] The main purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art and to provide an inter-machine communication method suitable for strongly coupled follow-up harvesting-unloading coordinated control, so as to achieve accurate, effective and timely inter-machine communication, provide data guarantee for coordinated control, and provide theoretical and technical support for unmanned harvesting.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] The present invention provides an inter-machine communication method applicable to the coordinated control of strongly coupled follow-up harvesting and grain unloading. During the strongly coupled follow-up harvesting and grain unloading, the harvester and the grain transport vehicle travel in parallel and in the same direction. The inter-machine communication method comprises the following steps:

[0007] S1. Obtain confidence data of the harvester and the grain transporter; the confidence data includes position, heading, speed, acceleration, RTK quality indication and UTC time;

[0008] S2, using two different communication methods to complement each other between the harvester and the grain transport vehicle, and realizing data frame reception and transmission based on a preset communication protocol;

[0009] S3, using dead reckoning and communication delay compensation to obtain the system recursive equation and measurement matrix of the Kalman filter;

[0010] S4. Use the relative longitudinal distance calculation method between machines to achieve real-time acquisition of the position, heading and relative longitudinal distance between the two machines of the communicating agricultural machinery;

[0011] S5. Based on the satellite positioning system and the inertial measurement system, the data frames are packaged and sent respectively using two different communication methods.

[0012] As a preferred technical solution, in step S2, the preset communication protocol is specifically:

[0013] The data frame starts with "$" and ends with a newline character and a null character. It contains the plane coordinates X and Y, heading, speed, RTK quality indicator, UTC time and the number of working lines in the navigation coordinate system. Each segment of data is separated by a comma. Checksum is the CRC16 checksum.

[0014] As a preferred technical solution, step S3 is specifically as follows:

[0015] Based on the dead reckoning principle, the motion state prediction equation of the harvester / grain transporter in the 2D plane navigation coordinate system is established as follows:

[0016]

[0017] Where: x h ,y h is the plane coordinate of the harvester in the navigation coordinate system at time t, which comes from satellite positioning; hx 、v hy is the forward speed of the harvester along the x and y axes in the navigation coordinate system at time t-1; a hx 、a hy is the acceleration of the harvester along the x and y axes in the navigation coordinate system at time t-1; Δt is the time interval of dead reckoning, which depends on the data update frequency of satellite positioning; θ h is the heading angle of the harvester at time t-1, which comes from satellite positioning; v h is the forward speed of the harvester, which comes from satellite positioning; a h is the acceleration of the harvester, which comes from the vehicle-mounted inertial measurement system; the motion state prediction equation of the grain transport vehicle in the 2D plane navigation coordinate system is consistent with that of the harvester;

[0018] Then the state equation describing the harvester / grain transporter is expressed as:

[0019] X t =AX t-1 +ω kal

[0020] Where: is a six-dimensional state space vector; ω kal Excite noise for the process; is the system state transfer matrix;

[0021] The observation equation for the position of the harvester / grain truck is:

[0022] Z t =HX t +v kal

[0023] Where: Z t is the state observation vector, is the observation matrix, v kal is the observation noise;

[0024] The interaction data between the harvester and the grain truck, that is, the observation vector Z t The communication delay compensation is as follows:

[0025]

[0026] Where: T C T is the UTC time (s) in the received data frame; l is the UTC time of the local agricultural machinery (s); T d is the communication delay (s);

[0027] In summary, the recursive process of the Kalman filter is as follows:

[0028]

[0029] The same approach is used to design the Kalman filters for the grain truck and the harvester.

[0030] As a preferred technical solution, the process excitation noise ω of the state equation kal The observation noise v of the observation equation kal All conform to the normal distribution, corresponding to the process error covariance matrix Q and the measurement error covariance matrix R of the system, that is:

[0031]

[0032] As a preferred technical solution, the method for calculating the relative longitudinal distance between machines is specifically as follows:

[0033] In order to enable the harvester to accurately unload grain into the grain transport vehicle during driving, it is necessary to make the grain unloading barrel outlet position P hu and the target point P for unloading gu coincidence; among them, P hu With P gu The relative lateral distance d la Adjust and control through advance path planning and real-time path tracking; relative longitudinal distance d loThe control is achieved by adjusting the relative speed of the vehicles, which requires real-time inter-machine communication.

[0034] By calculating P g The projection on the target heading gives the relative longitudinal distance d lo ; The positive and negative values ​​of cosβ are used to describe the relative front-to-back position relationship between the harvester and the grain transporter. It is stipulated that when the harvester is in front and the grain transporter is behind, the relative longitudinal distance d lo is positive, otherwise it is negative, then the relative longitudinal distance between machines is calculated as follows:

[0035]

[0036] As a preferred technical solution, wireless communication and data interaction are performed through two different communication modes, and the data sending and receiving frequencies of the two are respectively set to 1-10 Hz according to the characteristics of the respective communication modes.

[0037] As a preferred technical solution, the observation values ​​of the Kalman filter come from two different communication methods, and the two wireless communication methods are complementary; when the links of the two communication methods are unobstructed, switching is performed according to the distance between the harvester and the grain truck based on the characteristics of the two communication methods.

[0038] As a preferred technical solution, the communication method has the characteristic of self-organizing network, including but not limited to 4G, 5G, WIFI, and LORA.

[0039] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0040] (1) The Kalman filter based on dead reckoning and delay compensation proposed in the present invention can effectively solve the problems of data delay, packet loss, congestion, error, etc. in wireless communication, and has the ability to sustain short breakpoints, so that the update frequency of inter-machine communication data can be synchronized with the control frequency.

[0041] (2) The inter-machine communication implementation method proposed in the present invention can provide algorithm support for the real-time communication data fusion of multiple different wireless communication modes, so as to realize accurate, effective and timely inter-machine communication and provide data guarantee for collaborative control. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0043] Figure 1It is a schematic diagram of the coordinated harvesting-unloading operation according to an embodiment of the present invention.

[0044] Figure 2 It is a simplified schematic diagram of the geometric relationship of the coordinated harvesting-unloading operation according to an embodiment of the present invention.

[0045] Figure 3 This is a definition of a wireless communication data frame according to an embodiment of the present invention.

[0046] Figure 4 The present invention is a flowchart of receiving and processing data frames according to an embodiment of the present invention.

[0047] Figure 5 The figure is a schematic diagram of the overall structure of the data processing method for inter-machine communication according to an embodiment of the present invention.

[0048] Figure 6 The figure is a schematic diagram of the hardware architecture design for inter-machine communication according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present application.

[0050] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments.

[0051] The present embodiment provides an inter-machine communication method applicable to strongly coupled follow-up harvesting-unloading coordinated control, comprising the following steps:

[0052] S1. Obtain confidence data of the harvester and the grain transporter; the confidence data includes position, heading, speed, acceleration, RTK quality indication and UTC time.

[0053] S2. Two different communication methods are used to complement each other between the harvester and the grain transport vehicle, and data frame reception and transmission are realized based on a preset communication protocol.

[0054] Furthermore, the protocol for communication data between the harvester and the grain truck is as follows Figure 3As shown. The data frame starts with "$" and ends with a line break and a null character. It contains the plane coordinates X and Y, heading, speed, RTK quality indicator, UTC time and the number of working lines in the navigation coordinate system. Each segment of data is separated by a comma, and the Checksum is the CRC16 checksum.

[0055] Furthermore, two different communication methods are used as complements, and the information processing flow is as follows Figure 4 As shown, specifically:

[0056] S21, clear communication mode 1 (or communication mode 2);

[0057] S22, receiving and saving data frames;

[0058] S23, determine whether the data frame length is less than 100, and whether it ends with "$" or "r / n / 0"? If yes, proceed to the next step;

[0059] S24, determine whether the data verification is passed, if yes, proceed to the next step;

[0060] S25, data preservation and update;

[0061] S26. Data update flag of communication mode 1 (or communication mode 2) = true.

[0062] S3. Use dead reckoning and communication delay compensation to obtain the system recursive equation and measurement matrix of the Kalman filter.

[0063] Furthermore, the S3 is specifically:

[0064] Based on the dead reckoning principle, the motion state prediction equation of the harvester (grain transporter) in the 2D plane navigation coordinate system is established as follows:

[0065]

[0066] Where: x h ,y h is the harvester at time t (point P h ) Plane coordinates in the navigation coordinate system, which come from satellite positioning; v hx 、v hy is the harvester at time t-1 (point P h ) The forward speed along the x and y axes in the navigation coordinate system; a hx 、a hy is the harvester at time t-1 (point P h ) is the acceleration along the x and y axes in the navigation coordinate system; Δt is the time interval of dead reckoning, which depends on the data update frequency of satellite positioning; θ his the heading angle of the harvester at time t-1, which comes from satellite positioning; v h is the forward speed of the harvester, which comes from satellite positioning; a h is the acceleration of the harvester, which comes from the vehicle-mounted inertial measurement system. The motion state prediction equation of the grain transport vehicle in the 2D plane navigation coordinate system is consistent with that of the harvester.

[0067] Then the state equation describing the harvester (grain transporter) can be expressed as:

[0068] X t =AX t-1 +ω kal

[0069] Where: is a six-dimensional state space vector; ω kal Excite noise for the process; is the system state transfer matrix.

[0070] The observation equation of the harvester (grain transporter) position is:

[0071] Z t =HX t +v kal

[0072] Where: Z t is the state observation vector, is the observation matrix, v kal is the observation noise.

[0073] Compared with wired communication, wireless communication has a larger delay, and the delay time is uncertain. In order to reduce the impact of communication delay on real-time control, the interaction data between the harvester and the grain truck, that is, the observation vector Z t The communication delay compensation is as follows:

[0074]

[0075] Where: T C T is the UTC time (s) in the received data frame; l is the UTC time of the local agricultural machinery (s); T d is the communication delay (s).

[0076] In summary, the recursive process of the Kalman filter can be obtained as follows:

[0077]

[0078] Furthermore, the process excitation noise ω of the state equation kal The observation noise v of the observation equation kalAll conform to the normal distribution, corresponding to the process error covariance matrix Q and the measurement error covariance matrix R of the system, that is:

[0079]

[0080] S4. Use the relative longitudinal distance calculation method between machines to achieve real-time acquisition of the position, heading and relative longitudinal distance between the two machines of the communicating agricultural machinery;

[0081] In the strong coupling follow-up harvesting-unloading, the harvester and the grain transporter travel in parallel and in the same direction. In order to enable the harvester to accurately unload grain into the grain transporter during driving, the harvester positioning point 1 and the grain transporter positioning point 6 are first determined, and then the exit position P of the grain unloading barrel 2 needs to be hu (i.e., unloading port 4) and unloading target point P gu (i.e. target unloading point 5) coincides (e.g. Figure 1 In addition, the harvester is provided with a GNSS antenna 3, and the grain transport vehicle is provided with a crawler 7. h is the navigation control point of the harvester; g is the navigation control point of the grain transport vehicle; hu P is the unloading point of the harvester; gu The target unloading point; d la P hu and P gu The relative lateral distance between lo P hu and P gu The relative longitudinal distance between them. hu With P gu The relative lateral distance d la Adjust and control through advance path planning and real-time path tracking; relative longitudinal distance d lo It is controlled by adjusting the relative vehicle speed, and its control requires real-time inter-machine communication.

[0082] When the harvester and the grain transporter track a straight path, the standard deviation of their heading swing is less than 0.06°. Therefore, it can be assumed that when unloading grain in coordination, the headings of the two machines are stable and consistent with the target heading. A simplified harvester cooperative unloading model can be obtained (e.g. Figure 2 shown), Figure 2 Medium (x h ,y h ) is P h The coordinates of the point; (x g ,y g ) is P g The coordinates of the point; v h is the travel speed of the harvester; v g is the speed of the grain truck; θ is the target heading of the harvester and the grain truck; l h The unloading point Phu The projection point in the θ direction to the harvester positioning point P h The distance; l g The target unloading point P gu To the grain truck positioning point P g The distance; l e for l h and l g The difference in length; P g ' is the position of the grain truck in the θ direction g Distance l e Point; P g "P g 'The projection point in the θ direction; P gu ' is the target unloading point P gu The projection point in the θ direction; β is P h P g ' and θ. By calculating P g The projection on the target heading can obtain the relative longitudinal distance d lo The positive and negative values ​​of cosβ can describe the relative front-to-back position relationship between the harvester and the grain transporter. It is stipulated that when the harvester is in front and the grain transporter is behind, the relative longitudinal distance d lo is positive, otherwise it is negative, then the relative longitudinal distance between machines can be calculated as follows:

[0083]

[0084] It can be seen that in real-time control of the relative longitudinal distance d lo When the control effect depends not only on the quality of the control method, but also on the update frequency, packet loss rate and real-time performance of the mutual position information.

[0085] S5. Based on the satellite positioning system and the inertial measurement system, the data frames are packaged and sent respectively using two different communication methods.

[0086] Furthermore, the information processing method of the inter-machine communication is as follows Figure 5 Wireless communication and data exchange are carried out through two different communication methods. The data transmission and reception frequencies of the two are set to 1-10Hz according to the characteristics of the communication methods. The Kalman filter is used for prediction and data fusion to realize the interaction of real-time positions between machines and obtain the relative longitudinal distance d lo , and increase the data update frequency and stabilize it at 10Hz, synchronized with the control frequency.

[0087] The observation values ​​of the Kalman filter come from two different communication methods, and the two wireless communication methods complement each other. When the links of the two communication methods are unobstructed, according to the characteristics of the two communication methods, the distance between the harvester and the grain transporter is used for switching. The hardware architecture of the inter-machine communication is as follows: Figure 6 As shown. Before each filter iteration, the observation value needs to be compensated for communication delay. Position is the plane coordinate of the satellite positioning point in the navigation coordinate system after Gaussian projection, coordinate transformation and delay compensation. The original latitude and longitude information of Position as well as UTC, Heading, Velocity, and RTK_flag all come from the real-time GPGGA message sent by the RTK-GNSS board in the navigation system of the harvester and grain truck. The fixed solution (RTK_flag = 4) is the normal state of satellite positioning, and the information under other solution categories is unreliable. Therefore, RTK_flag is selected as the flag for the Kalman filter to start initialization and normal operation. When the communication link between the harvester and the grain truck is interrupted for more than 6s, the corresponding abnormal communication between the machines should be handled.

[0088] It is understandable that there are many communication methods that have the characteristics of self-networking, such as 4G / 5G, WIFI, LORA, etc. Therefore, this method can also be used under networking conditions to achieve inter-machine communication for multi-machine collaborative operation.

[0089] In another embodiment of the present application, based on the actual needs of collaborative harvesting and precise grain unloading operations, this example uses radio (Radio 5Ghz) as communication mode 1 and 4G Cat1 as communication mode 2. Figure 6 Build an inter-machine communication system. According to the characteristics of the two communication methods, the data update frequency of the radio (Radio 5Ghz) communication method is set to 5Hz, and the data update frequency of the 4G Cat1 communication method is set to 2Hz. The data frame definition of inter-machine communication is as follows: Figure 3 The processing method and process of inter-machine communication data are as follows:

[0090] S1, data verification and unpacking, as well as the selection and preservation of trusted data, such as Figure 4 As shown. Get the position, heading, speed, acceleration, RTK quality indicator, UTC time and other data of the other party's agricultural machinery.

[0091] S2. Compensate for communication delay based on the UTC time obtained by communication and the UTC time difference obtained by the local agricultural machinery satellite positioning system. The method of communication compensation is as follows:

[0092]

[0093] The two wireless communication modes of 4G and radio complement each other: when the 4G link and the radio link are unobstructed, according to the characteristics of the two communication modes, the distance between the harvester and the grain truck is used for switching. For short distances (<35m), the radio is used, and for long distances (≥35m), 4G is used. Before each filter iteration, the observation value needs to be delayed compensated.

[0094] Based on the dead reckoning principle, the motion state prediction equation of the harvester (grain transporter) in the 2D plane navigation coordinate system is established as follows:

[0095]

[0096] S3. The agricultural machinery motion state prediction equation obtained by dead reckoning is used as the system state recursion equation of the Kalman filter, and the inter-machine communication data after delay compensation is used as the measurement value of the Kalman filter to perform real-time iteration of the Kalman filter, wherein:

[0097] Based on the dead reckoning principle, the state equation describing the harvester h (grain transporter g) can be expressed as:

[0098] X t =AX t-1 +ω kal

[0099] Where: is a six-dimensional state space vector; ω kal Excite noise for the process; is the system state transfer matrix.

[0100] The observation equation of the harvester (grain transporter) position is:

[0101] Z t =HX t +v kal

[0102] Where: Z t is the state observation vector, is the observation matrix, v kal is the observation noise.

[0103] The recursive process of the Kalman filter is as follows:

[0104]

[0105] The same approach is used to design the Kalman filters for the grain truck and the harvester.

[0106] The process excitation noise ω of the state equation kal The observation noise v of the observation equation kalAll conform to the normal distribution, corresponding to the process error covariance matrix Q and the measurement error covariance matrix R of the system, that is:

[0107]

[0108] The ratio of the covariance matrices Q and R determines the performance of the Kalman filter, which is adjusted and calibrated through offline experiments.

[0109] The calculation and acquisition method of the relative longitudinal distance between two aircrafts is as follows:

[0110]

[0111] Therefore, the real-time position of the other communicating agricultural machinery and the relative longitudinal distance d between the two machines can be obtained based on dead reckoning and delay-compensated Kalman filter. lo The data update frequency is a stable 10Hz for subsequent control links.

[0112] S4, based on the RTK-GNSS positioning system and inertial measurement system of local agricultural machinery, using Figure 3 The data frame protocol shown is used to package data and send it using radio (Radio 5Ghz) and 4G Cat1 at frequencies of 5Hz and 2Hz respectively.

[0113] The overall structure of the inter-machine communication data processing method is as follows: Figure 5 shown.

[0114] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0115] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the protection scope of the present invention.

Claims

1. A machine communication method suitable for strong coupling follow-up harvesting-unloading coordinated control, characterized in that: During the strongly coupled follow-up harvesting and unloading, the harvester and the grain transport vehicle travel in parallel and in the same direction, and the inter-machine communication method includes the following steps: S1. Obtain confidence data of the harvester and the grain transporter; the confidence data includes position, heading, speed, acceleration, RTK quality indication and UTC time; S2, using two different communication methods to complement each other between the harvester and the grain transport vehicle, and realizing data frame reception and transmission based on a preset communication protocol; S3, using dead reckoning and communication delay compensation to obtain the system recursive equation and measurement matrix of the Kalman filter; S4. Use the relative longitudinal distance calculation method between machines to achieve real-time acquisition of the position, heading and relative longitudinal distance between the two machines of the communicating agricultural machinery; S5. Based on the satellite positioning system and the inertial measurement system, the data frames are packaged and sent respectively using two different communication methods.

2. According to claim 1, a machine communication method suitable for strong coupling follow-up harvesting-unloading coordinated control is characterized in that: In step S2, the preset communication protocol is specifically: The data frame starts with "$" and ends with a newline character and a null character. It contains the plane coordinates X and Y, heading, speed, RTK quality indicator, UTC time and the number of working lines in the navigation coordinate system. Each segment of data is separated by a comma. Checksum is the CRC16 checksum.

3. The inter-machine communication method suitable for strong coupling follow-up harvesting-unloading coordinated control according to claim 1, characterized in that: The step S3 is specifically as follows: Based on the dead reckoning principle, the motion state prediction equation of the harvester / grain transporter in the 2D plane navigation coordinate system is established as follows: Where: x h ,y h is the plane coordinate of the harvester in the navigation coordinate system at time t, which comes from satellite positioning; hx 、v hy is the forward speed of the harvester along the x and y axes in the navigation coordinate system at time t-1; a hx 、a hy is the acceleration of the harvester along the x and y axes in the navigation coordinate system at time t-1; Δt is the time interval of dead reckoning, which depends on the data update frequency of satellite positioning; θ h is the heading angle of the harvester at time t-1, which comes from satellite positioning; v h is the forward speed of the harvester, which comes from satellite positioning; a h is the acceleration of the harvester, which comes from the vehicle-mounted inertial measurement system; the motion state prediction equation of the grain transport vehicle in the 2D plane navigation coordinate system is consistent with that of the harvester; Then the state equation describing the harvester / grain transporter is expressed as: X t =AX t-1 +ω kal Where: X t =[x h v hx a hx y h v hy a hy ] t T is a six-dimensional state space vector; ω kal Excite noise for the process; is the system state transfer matrix; The observation equation for the position of the harvester / grain truck is: Z t =HX t +v kal Where: Z t is the state observation vector, is the observation matrix, v kal is the observation noise; The interaction data between the harvester and the grain truck, that is, the observation vector Z t The communication delay compensation is as follows: Where: T C T is the UTC time (s) in the received data frame; l is the UTC time of the local agricultural machinery (s); T d is the communication delay (s); In summary, the recursive process of the Kalman filter is as follows: The same approach is used to design the Kalman filters for the grain truck and the harvester.

4. The inter-machine communication method suitable for strong coupling follow-up harvesting-unloading coordinated control according to claim 3 is characterized in that: The process excitation noise ω of the state equation kal The observation noise v of the observation equation kal All conform to the normal distribution, corresponding to the process error covariance matrix Q and the measurement error covariance matrix R of the system, that is:

5. The inter-machine communication method suitable for strong coupling follow-up harvesting-unloading coordinated control according to claim 1, characterized in that: The method for calculating the relative longitudinal distance between machines is specifically as follows: In order to enable the harvester to accurately unload grain into the grain transport vehicle during driving, it is necessary to make the grain unloading barrel outlet position P hu and the target point P for unloading gu coincidence; among them, P hu With P gu The relative lateral distance d la Adjust and control through advance path planning and real-time path tracking; relative longitudinal distance d lo The control is achieved by adjusting the relative speed of the vehicles, which requires real-time inter-machine communication. By calculating P g The projection on the target heading gives the relative longitudinal distance d lo ; The positive and negative values ​​of cosβ are used to describe the relative front-to-back position relationship between the harvester and the grain transporter. It is stipulated that when the harvester is in front and the grain transporter is behind, the relative longitudinal distance d lo is positive, otherwise it is negative, then the relative longitudinal distance between machines is calculated as follows:

6. The inter-machine communication method suitable for strong coupling follow-up harvesting-unloading coordinated control according to claim 1, characterized in that: Wireless communication and data interaction are carried out through two different communication methods, and the data sending and receiving frequencies of the two are set to 1-10Hz respectively according to the characteristics of each communication method.

7. The inter-machine communication method applicable to the strong coupling follow-up harvesting-unloading coordinated control according to claim 1 is characterized in that: The observation values ​​of the Kalman filter come from two different communication methods, and the two wireless communication methods are complementary. When the links of the two communication methods are unobstructed, switching is performed according to the distance between the harvester and the grain truck based on the characteristics of the two communication methods.

8. The inter-machine communication method applicable to the strong coupling follow-up harvesting-unloading coordinated control according to claim 1 is characterized in that: The communication method has the characteristic of self-organizing network, including but not limited to 4G, 5G, WIFI, and LORA.

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