Rose seedling automatic planting device and method

Abstract

The present invention discloses an automatic rose seedling planting device and method, comprising a mobile body, on which a drilling device, a seedling throwing device, a soil compacting device and a control device are arranged, wherein the drilling device, the seedling throwing device and the soil compacting device are arranged on the mobile body at equal intervals, and the drilling device comprises a multifunctional soil sensor, which detects soil temperature, humidity and conductivity in real time; the control device controls the drilling device to adjust the drilling depth in real time according to the soil temperature, humidity and conductivity. The control device comprises a LIDAR sensor, an ultrasonic sensor and an inertial measurement unit, and the device can be accurately moved along the ridge by fusing the information of multiple sensors. The present invention can adjust the drilling depth in real time according to the soil environment during drilling, and the seedling planting depth is more reasonable and controllable; an advanced sensor system and a three-dimensional extended Kalman filter information fusion mechanism are used to achieve efficient and accurate field planting operations.

Description

Technical Field

[0001] The invention relates to the technical field of rose seedling planting and planting machinery, and in particular to an automatic rose seedling planting device and method. Background Art

[0002] The traditional method of rose planting is artificial intensive planting, which has at least the following problems: the planting depth and spacing of rose seedlings are unreasonable, and the seedlings are tilted. In traditional artificial intensive planting, the planting depth and spacing of rose seedlings are usually determined by the experience and feeling of the grower, but the soil conditions in different locations are different, and the environment is also different. If the same standard is used for all soils or the planting depth and spacing of rose seedlings are controlled by experience and feeling, the planting depth and spacing of rose seedlings will be unreasonable, the seedlings will be tilted, and the survival rate of rose seedlings will be low.

[0003] Therefore, it is necessary to design a new type of automated rose seedling automatic planting device to achieve precise positioning and environmental detection, reduce mechanical damage to the seedlings, and realize efficient and precise field planting operations. Summary of the invention

[0004] Therefore, an object of the present invention is to provide a rose seedling automatic planting device and method to solve the problems mentioned in the background technology and overcome the deficiencies in the prior art.

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

[0006] A rose seedling automatic planting device comprises a mobile body, on which a drilling device, a seedling throwing device, a soil compacting device and a control device are provided, wherein the drilling device is placed in the middle of the front end of the mobile body; the seedling throwing device and the soil compacting device are located on the same axis as the drilling device, and are sequentially placed on the mobile body at equal intervals; the drilling device comprises a multifunctional soil sensor, which detects soil temperature, humidity and conductivity in real time; the control device controls the drilling device to adjust the drilling depth in real time according to the soil temperature, humidity and conductivity, specifically: the control device establishes a state model, including a state equation and an output equation, sets an optimization function and constraints to solve the model to predict the state and output at N moments in the future, optimizes the model prediction according to the soil temperature, humidity and conductivity, and adjusts the drilling depth;

[0007] The state equation is: f(k+1)=Af(k)+Bu(k);

[0008] The output equation is: y(k)=Cf(k)+Du(k);

[0009] in f(k) is the current state vector, t(k), s(k) and e(k) are the soil temperature, moisture and conductivity at the kth moment, u(k) is the adjustment amount of the drilling depth, y(k) is the drilling depth at the kth moment, A, B, C and D are the state transfer matrix, control matrix, output matrix and direct transfer matrix respectively;

[0010] The optimization function is:

[0011]

[0012] Where y(k+Δk) is the predicted drilling depth, y i (k+Δk) is the expected perforation depth, N is the predicted time domain length, and m is the regularization parameter;

[0013] The constraints are: min ≤u(k)≤u max ;y min ≤y(k)≤y max ;

[0014] Among them, the constraint parameters are obtained through field performance testing of the device and material properties, min ,y max They are the minimum and maximum drilling depths that the device can achieve, ensuring that the design limit of the machine is not exceeded; min 、u max The minimum and maximum drilling depth adjustments are set based on the motor's operating limitations and safety requirements;

[0015] Solve the optimization problem and obtain the optimal drilling depth adjustment sequence for the next N moments as follows:

[0016] {u(k),u(k+1),…,u(k+N-1)}.

[0017] Preferably, the mobile vehicle body includes a chassis, the chassis is connected to a plurality of wheels via a steering shaft and a connecting frame, the wheels are provided with tracks, and a steering motor and a drive motor are provided on the chassis, the steering motor is used to control the steering shaft, and the drive motor is used to drive the wheels.

[0018] Preferably, the punching device includes a nut screw and a punching motor, the punching motor is connected to a driving gear, the nut screw is mounted with a driven gear through a bearing, the driving gear and the driven gear are connected to each other through a synchronous belt, a spiral blade is provided at one end of the nut screw, and the multifunctional soil sensor is arranged in a central axis groove of the spiral blade.

[0019] Preferably, the seedling throwing device includes a conveying screw module and a seedling throwing tube, the conveying screw module is connected to a conveying motor and a seedling tray, the conveying motor provides power to the conveying screw module to drive the seedling tray to move, the seedling tray is provided with a bottom cover, and the bottom cover is connected to a bottom cover motor through a rotating hinge, the seedling throwing tube is arranged under the seedling tray and fixedly connected to the chassis of the mobile vehicle body, the center of the seedling throwing tube is on the same straight line as the spiral blade of the punching device and is 20 cm apart, the seedling tray and the seedling throwing tube are made of silicone and have smooth inner walls.

[0020] Preferably, the soil compacting device comprises a soil screw module and a compacting plate, the soil screw module is connected to a soil motor, the compacting plate is connected to the soil screw module via a connecting rod, a cylinder is provided on the compacting plate, and the compacting plate is provided with a groove.

[0021] Preferably, the control device includes a LIDAR sensor, an ultrasonic sensor, an inertial measurement unit, an air compressor, an industrial computer and a power supply arranged on the chassis of the mobile vehicle body, the inertial measurement unit includes an accelerometer and a gyroscope, the power supply and the industrial computer are respectively electrically connected and communicatively connected to the steering motor, the drive motor, the punching motor, the conveying motor, the bottom cover motor, the soil-carrying motor, the LIDAR sensor, the ultrasonic sensor and the inertial measurement unit.

[0022] Preferably, the industrial computer of the control device uses a three-dimensional extended Kalman filter to perform information fusion according to the environmental information measured by the LIDAR sensor, the ultrasonic sensor, and the inertial measurement unit, and drives the planting device to move under the control of the industrial computer, specifically:

[0023] First, a coordinate system is established with the center of gravity of the planting device as the origin, the ground as the XY plane, and the vertical upward as the Z axis, and the positions of the LIDAR sensor, the ultrasonic sensor, and the inertial measurement unit are uniformly converted into the coordinate system;

[0024] Establish the state vector X of the three-dimensional extended Kalman filter k and the observation vector Z k :

[0025] X k =[x k y k z k θ k φ k Ψ k v k ω k ] T

[0026] Zk =[z l z u z i，a z i，b ] T

[0027] Among them, x k ,y k 、z k is the coordinate position of the center of gravity, the initial value is (0, 0, 0), θ k is the yaw angle, φ k is the pitch angle, Ψ k is the roll angle, v k is the speed, ω k is the angular velocity;

[0028] The LIDAR sensor measurement data is: l =[z l，x z l，y z l，z ] T

[0029] The ultrasonic sensor measurement data is: u =[z u，x z u，y z u，z ] T

[0030] Among them, z l，x 、z l，y 、z l，z are the relative distances from the center of gravity of the planting device to the surrounding objects in the X, Y, and Z directions measured by the LIDAR sensor, respectively;

[0031] z u，x 、z u，y 、z u，z are the relative positions of the center of gravity of the planting device to the close-range obstacle in the X, Y, and Z directions measured by the ultrasonic sensor, respectively;

[0032] The accelerometer measurement data is: z i , a=[a i ,x i , ya i , z] T

[0033] The gyroscope measurement data is: z i，b =[b i，x b i，y b i，z ] T

[0034] Among them, a i，x 、ai，y 、a i，z are the accelerations of the planting device in the X, Y, and Z directions respectively; b i，x 、b i，y 、b i，z are the rotation rates of the planting device in the X, Y, and Z directions, respectively;

[0035] Secondly, a prediction model is established to predict the state and uncertainty at the next moment based on the current state and control input;

[0036] State vector prediction:

[0037]

[0038] Among them, f(X k , U k ) is the state transfer function, U k is the control input, W k is the process noise, and W k ~N(0,

[0039] Q k ), with covariance Q k ;

[0040] The state transfer function is:

[0041] Covariance prediction:

[0042]

[0043] Among them, F k is the Jacobian matrix of the state transfer function to the state vector, is the prior covariance matrix at time k+1, P k is the posterior covariance matrix at time k;

[0044] Finally, measurement update is to use the measured value to correct the predicted state to obtain a more accurate state estimate;

[0045] The measurement model updates the state estimate:

[0046] in, is the measurement function, V k+1 is the measurement noise and is subject to V k+1 ~N(0,R k+1 ), with covariance R k+1 ;

[0047] Kalman gain:

[0048]

[0049] Among them, H k is the Jacobian matrix of the measurement function with respect to the state vector, R k is the measurement noise covariance matrix;

[0050] Status Update:

[0051] Covariance update: Where I is the identity matrix;

[0052] The industrial computer controls the drive motor and steering motor according to the fused calculation update results to drive the planting device to move.

[0053] The present invention also includes a method for automatically planting rose seedlings, comprising the following steps: S1: placing the seedlings in a seedling tray of a planting device, starting a power supply, and using a LIDAR sensor, an ultrasonic sensor, and an inertial measurement unit to sense environmental information in real time, using a three-dimensional extended Kalman filter to fuse the acquired environmental information, and an industrial computer controlling a drive motor and a steering motor according to a calculation update result of the fusion to enable the planting device to move accurately along a field ridge;

[0054] S2: The industrial computer controls the driving motor and the steering motor according to the environmental information to move the planting device to the target planting position, the drilling device starts, and the industrial computer controls the drilling motor to operate. The drilling motor drives the nut screw to rotate through the gear and the synchronous belt, and drives the spiral blade to rotate to form the first planting hole on the planting bed. During the drilling process, the multifunctional soil sensor monitors the soil temperature, humidity and conductivity at the drilling position of the planting bed in real time. The control device controls the drilling device to adjust the drilling depth according to the soil temperature, humidity and conductivity.

[0055] S3: The industrial computer controls the driving motor and the steering motor according to the environmental information to move the planting device to the next target planting position. The punching device and the seedling throwing device are started at the same time. The punching device punches holes on the planting bed to form a second planting hole. The conveying motor of the seedling throwing device drives the conveying screw module to move the seedling tray in a plane so that the hole of the seedling tray is concentric with the seedling throwing tube. The bottom cover motor controls the bottom cover of the seedling tray to open by rotating the hinge. The seedlings are thrown into the first planting hole through the seedling throwing tube due to gravity.

[0056] S4: The industrial computer controls the driving motor and the steering motor according to the environmental information to move the planting device to the next target planting position, and the punching device, the seedling throwing device and the soil compacting device are started at the same time. The punching device punches holes on the planting bed to form a third planting hole, and the seedling throwing device throws seedlings into the previous planting hole. At the same time, the industrial computer controls the soil motor of the soil compacting device to drive the soil screw module to move the compacting plate to fill the planting hole after the previous seedling is thrown, and then the cylinder controls the compacting plate to compact the soil;

[0057] S5: S4 is repeatedly executed until the punching device completes the last punching, then the punching device stops working, the seedling throwing device stops working after running once again, and the soil compacting device stops working after running twice again.

[0058] Preferably, the control device controls the drilling device to adjust the drilling depth according to the soil temperature, humidity and conductivity as follows:

[0059] The control device establishes a state model, including a state equation and an output equation, sets an optimization function, solves the model according to the constraint conditions to obtain the drilling depth, and the control device controls the drilling device according to the solution result;

[0060] The state equation is: f(k+1)=Af(k)+Bu(k);

[0061] The output equation is: y(k)=Cf(k)+Du(k);

[0062] in f(k) is the current state vector, t(k), s(k) and e(k) are the soil temperature, moisture and conductivity at the kth moment, u(k) is the adjustment amount of the drilling depth, y(k) is the drilling depth at the kth moment, A, B, C and D are the state transfer matrix, control matrix, output matrix and direct transfer matrix respectively;

[0063] The optimization function is:

[0064]

[0065] Where y(k+Δk) is the predicted drilling depth, y i (k+Δk) is the expected perforation depth, N is the predicted time domain length, and m is the regularization parameter;

[0066] The constraints are: min ≤u(k)≤u max ;y min ≤y(k)≤y max ;

[0067] Among them, the constraint parameters are obtained through field performance testing of the device and material properties, min ,y max They are the minimum and maximum drilling depths that the device can achieve, ensuring that the design limit of the machine is not exceeded; min 、u max The minimum and maximum drilling depth adjustments are set based on the motor's operating limitations and safety requirements;

[0068] Solve the optimization problem and obtain the optimal drilling depth adjustment sequence for the next N moments as follows:

[0069] {u(k),u(k+1),…,u(k+N-1)}.

[0070] Preferably, the LIDAR sensor, ultrasonic sensor and inertial measurement unit sense environmental information in real time, and the acquired environmental information is fused using a three-dimensional extended Kalman filter. The industrial computer controls the drive motor and the steering motor to move the planting device according to the fused calculation update result. Specifically:

[0071] First, a coordinate system is established with the center of gravity of the planting device as the origin, the ground as the XY plane, and the vertical upward as the Z axis, and the positions of the LIDAR sensor, the ultrasonic sensor, and the inertial measurement unit are uniformly converted into the coordinate system;

[0072] Establish the state vector X of the three-dimensional extended Kalman filter k and the observation vector Z k :

[0073] X k =[x k y k z k θ k φ k Ψ k v k ω k ] T

[0074] Z k =[z l z u z i，a z i，b ] T

[0075] Among them, x k ,y k 、z k is the coordinate position of the center of gravity, the initial value is (0, 0, 0), θ k is the yaw angle, φ k is the pitch angle, Ψ k is the roll angle, v k is the speed, ω k is the angular velocity;

[0076] The LIDAR sensor measurement data is: l =[z l，x z l，y z l，z ] T

[0077] The ultrasonic sensor measurement data is: u =[zu，x z u，y z u，z ] T

[0078] Among them, z l，x 、z l，y 、z l，z are the relative distances from the center of gravity of the planting device to the surrounding objects in the X, Y, and Z directions measured by the LIDAR sensor, respectively;

[0079] z u，x 、z u，y 、z u，z are the relative positions of the center of gravity of the planting device to the close-range obstacle in the X, Y, and Z directions measured by the ultrasonic sensor, respectively;

[0080] The accelerometer measurement data is: z i，a =[a i，x a i，y a i，z ] T

[0081] The gyroscope measurement data is: z i，b =[b i，x b i，y b i，z ] T

[0082] Among them, a i，x 、a i，y 、a i，z are the accelerations of the planting device in the X, Y, and Z directions respectively; b i，x 、b i，y 、b i，z are the rotation rates of the planting device in the X, Y, and Z directions, respectively;

[0083] Secondly, a prediction model is established to predict the state and uncertainty at the next moment based on the current state and control input;

[0084] State vector prediction:

[0085]

[0086] Among them, f(X k , U k ) is the state transfer function, U k is the control input, W k is the process noise, and W k ~N(0,Q k ), with covariance Q k ;

[0087] The state transfer function is:

[0088] Covariance prediction:

[0089]

[0090] Among them, F k is the Jacobian matrix of the state transfer function to the state vector, is the prior covariance matrix at time k+1, P k is the posterior covariance matrix at time k;

[0091] Finally, measurement update is to use the measured value to correct the predicted state to obtain a more accurate state estimate;

[0092] The measurement model updates the state estimate:

[0093] in, is the measurement function, V k+1 is the measurement noise and is subject to V k+1 ~N(0,R k+1 ), with covariance R k+1 ;

[0094] Kalman gain:

[0095]

[0096] Among them, H k is the Jacobian matrix of the measurement function with respect to the state vector, R k is the measurement noise covariance matrix;

[0097] Status Update:

[0098] Covariance update: Where I is the identity matrix;

[0099] The industrial computer controls the drive motor and steering motor according to the fused calculation update results to drive the planting device to move.

[0100] Therefore, the present invention has the following beneficial effects:

[0101] The punching device of the present invention is equipped with a multifunctional soil sensor, which can monitor soil temperature, humidity and conductivity in real time when punching. The rose seedling planting device adjusts the punching depth of the punching device in real time according to the soil conditions, and the planting depth of the rose seedlings is more reasonable. At the same time, the punching device, the seedling throwing device, the soil compacting device and the like of the present invention are arranged on the mobile vehicle body at equal intervals, so that the planting intervals between the rose seedlings are also equidistant, and the spacing between the planted seedlings is uniform and reasonable. The synergistic effect of the two helps to improve the survival rate of the rose seedlings. BRIEF DESCRIPTION OF THE DRAWINGS

[0102] Figure 1 It is a schematic diagram of the overall structure of the planting device of the present invention;

[0103] Figure 2 Schematic diagram of the structure of the mobile device of the present invention

[0104] Figure 3 Schematic diagram of the structure of the punching device of the present invention

[0105] Figure 4 It is a structural schematic diagram of the seedling throwing device of the present invention.

[0106] Figure 5 It is a structural schematic diagram of the soil compacting device of the present invention.

[0107] Figure 6 It is a structural schematic diagram of the control device of the present invention

[0108] Figure 7 It is a flow chart of the method of the present invention.

[0109] In the figure: 1. Mobile body; 101. Track; 102. Chassis; 103. Steering connecting frame; 104. Steering shaft; 105. Steering motor; 106. Wheel; 107. Driving motor; 2. Punching device; 201. Nut screw; 202. Punching motor; 203. Bearing; 204. Synchronous belt; 205. Driving gear; 206. Driven gear; 207. Multifunctional soil sensor; 208. Spiral blade; 3. Seedling device; 301. Conveying motor; 302, conveying screw module; 303, seedling tray; 304, bottom cover motor; 305, rotating hinge; 306, seedling tray bottom cover; 307, seedling throwing tube; 4, soil compacting device; 401, soil motor; 402, soil screw module; 403, cylinder; 404, compacting plate; 5, control device; 501, LIDAR sensor; 502, ultrasonic sensor; 503, inertial measurement unit; 504, air compressor; 505, industrial computer; 506, power supply. DETAILED DESCRIPTION

[0110] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0111] like Figure 1-Figure 6As shown, an automatic rose seedling planting device comprises a mobile body 1, on which a punching device 2, a seedling throwing device 3, a soil compacting device 4 and a control device 5 are arranged, and the punching device 2 is placed in the middle of the front end of the mobile body 1; the seedling throwing device 3 and the soil compacting device 4 are located on the same axis with the punching device 5, and are placed on the mobile body 1 in sequence with equal intervals; the punching device 2 comprises a multifunctional soil sensor 207, and the multifunctional soil sensor 207 detects soil temperature, humidity and conductivity in real time; the control device 5 controls the punching device 2 to adjust the punching depth in real time according to the soil temperature, humidity and conductivity, specifically: the control device 5 establishes a state model, including a state equation and an output equation, sets an optimization function, solves the model according to the constraint conditions to obtain the punching depth, and the control device 5 controls the punching device 2 according to the solution result;

[0112] The state equation is: f(k+1)=Af(k)+Bu(k);

[0113] The output equation is: y(k) = Cf(k) + Du(k);

[0114] in f(k) is the current state vector, t(k), s(k) and e(k) are the soil temperature, moisture and conductivity at the kth moment, u(k) is the adjustment of the drilling depth at the kth moment, y(k) is the drilling depth at the kth moment, A, B, C and D are the state transfer matrix, control matrix, output matrix and direct transfer matrix respectively;

[0115] The optimization function is:

[0116]

[0117] Where y(k+Δk) is the predicted drilling depth at the k+Δkth moment, y i (k+Δk) is the expected perforation depth, N is the predicted time domain length, and m is the regularization parameter;

[0118] The constraints are: min ≤u(k)≤u max ;y min ≤y(k)≤y max ;

[0119] Among them, the constraint parameters are obtained through field performance testing of the device and material properties, min ,y max They are the minimum and maximum drilling depths that the device can achieve, ensuring that the design limit of the machine is not exceeded; min 、u max The minimum and maximum drilling depth adjustments are set based on the motor's operating limitations and safety requirements;

[0120] Solve the optimization problem and obtain the optimal drilling depth adjustment sequence for the next N moments as follows:

[0121] {u(k),u(k+1),…,u(k+N-1)}.

[0122] More specifically, the multifunctional soil sensor 207 detects soil temperature, humidity and conductivity (reflecting soil salt content) in real time and adjusts the drilling depth in real time. The process is as follows:

[0123] (1) Establishing system status model

[0124] State equation: f(k+1)=Af(k)+Bu(k);

[0125] Output equation: y(k)=Cf(k)+Du(k);

[0126] Where f(k) = [t(k)s(k)e(k)] T ; f(k) is the current state vector, t(k), s(k) and e(k) are the soil temperature (℃), humidity (%) and conductivity (ms / cm) at the kth moment respectively; u(k) is the adjustment amount of the drilling depth at the kth moment (mm); y(k) is the drilling depth at the kth moment; A, B, C, D are the state transfer matrix, control matrix, output matrix and direct transfer matrix respectively.

[0127] The above-mentioned state transfer matrix, control matrix, output matrix and direct transfer matrix are explained here with examples.

[0128] For example: the state at time k is known and the state vector is x(k):

[0129] The transfer state matrix A describes the influence of the state at the kth moment on the state at the k+1th moment.

[0130]

[0131] a 11 、a 12 、a 13 They represent the influence coefficients of soil temperature t(k) at the kth moment, soil moisture s(k) at the kth moment, and electrical conductivity e(k) at the kth moment on soil temperature t(k+1) at the k+1th moment respectively;

[0132] a 21 、a 22 、a 23 They represent the influence coefficients of soil temperature t(k) at the kth moment, soil moisture s(k) at the kth moment, and electrical conductivity e(k) at the kth moment on soil moisture s(k+1) at the k+1th moment respectively;

[0133] a31 、a 32 , a 33 The influence coefficients of soil temperature t(k) at the kth moment, soil moisture s(k) at the kth moment and electrical conductivity e(k) at the kth moment on soil electrical conductivity e(k+1) at the k+1th moment respectively.

[0134] The control matrix B describes the influence of the drilling depth adjustment u(k) at the kth moment on the state at the k+1th moment.

[0135] B=[b 11 b 21 b 31 ] T ;

[0136] b 11 、b 21 、b 31 They are respectively expressed as the influence coefficients of the drilling depth adjustment u(k) at the kth moment on the soil temperature t(k+1), soil moisture s(k+1), and soil conductivity e(k+1) at the k+1th moment.

[0137] The output matrix C describes the influence of the state at the kth moment on the perforation depth y(k) at the kth moment.

[0138] C=[C 11 C 12 C 13 ];

[0139] C 11 , C 12 , C 13 are the influence coefficients of soil temperature t(k), soil moisture s(k) and electrical conductivity e(k) at the kth moment on the drilling depth y(k) at the kth moment.

[0140] The direct transfer matrix D describes the relationship between the perforation depth adjustment u(k) at the kth moment and the perforation depth at the kth moment. y In the system, the drilling depth is mainly adjusted indirectly by the change of system status (soil temperature, humidity, conductivity), not directly determined by the drilling depth adjustment amount. Therefore, the matrix D=0.

[0141] (2) Model prediction

[0142] MPC Optimization:

[0143]

[0144] Among them, y(k+Δk) is the predicted drilling depth, y i (k+Δk) is the expected perforation depth; N is the predicted time domain length; m is the regularization parameter;

[0145] Constraints:

[0146] u min ≤u(k)≤u max ;y min ≤y(k)≤y max ;

[0147] Among them, the constraint parameters are obtained through field performance testing of the device and material properties, min ,y max They are the minimum and maximum drilling depths that the device can achieve, ensuring that the design limit of the machine is not exceeded; min 、u max The minimum and maximum drilling depth adjustments are set based on the motor's operating limitations and safety requirements;

[0148] Through models and predictions, we can know the status and output of N moments in the future;

[0149] (3) Real-time control

[0150] Control input calculation: Solve the optimization problem, the optimal drilling depth adjustment sequence for the next N moments:

[0151] {u(k),u(k+1),…,u(k+N-1)};

[0152] Real-time adjustment: Apply the first drilling depth adjustment u(k) to the system and adjust the drilling depth in real time:

[0153] y(k)=Cf(k)+Du(k);

[0154] Update system status: Update the system status based on the latest status and control input:

[0155] f(k+1)=Af(k)+Bu(k);

[0156] The time step is k, and the above steps are repeated. The sensor continuously collects data, performs model prediction optimization, and adjusts the drilling depth.

[0157] The punching device 2 of the present invention is equipped with a multifunctional soil sensor 207, which can monitor soil temperature, humidity and conductivity in real time when punching. The seedling planting device of the present invention adjusts the depth of the punching in real time according to the soil conditions, and the seedling planting depth is more reasonable and controllable. The punching device 2, the seedling throwing device 3, and the soil compacting device 4 of the present invention are arranged on the mobile body 1 at equal intervals, so that the planting spacing between the seedlings is also equal, and the seedling spacing is uniform and reasonable.

[0158] As an implementation method, the punching device 2, the seedling throwing device 3 and the soil compacting device are installed on the device at an equal interval of 20 cm, and the three are operated and stopped successively. The present invention sets a fixed planting spacing for roses, which is a 20 cm equal spacing seedling spacing set for rose seedlings, which is more suitable for the growth of rose seedlings and helps to improve the survival rate of rose seedlings.

[0159] More specifically, Figure 1 As shown, the punching device 2 is arranged at the front end of the mobile body 1, the seedling throwing device 3 is arranged above the middle of the mobile body 1, the soil compacting device 4 is fixed behind the seedling throwing device 3, and the control device 5 is distributed on the mobile body 1. The control device 5 senses and integrates external information to provide power and centralized control for the entire planting process.

[0160] Further, such as Figure 2 As shown, the mobile body 1 includes a chassis 102, and the chassis 102 is connected to a plurality of wheels 106 through a steering shaft 104 and a connecting frame 103. The wheels 106 are provided with tracks 101. A steering motor 105 and a drive motor 107 are provided on the chassis 102. The steering motor 105 is used to control the steering shaft 104, and the drive motor 107 is used to drive the wheels 106.

[0161] Specifically, the mobile body 1 includes a track 101, a chassis 102, a steering connecting frame 103, a steering shaft 104, a steering motor 105, wheels 106 and a driving motor 107, which are used to support and move the automatic seedling planting device. The device adopts the track 101 structure to increase the stability of the moving process.

[0162] Further, as attached Figure 3 As shown, the punching device 2 includes a nut screw 201 and a punching motor 202, the punching motor 202 is connected to a driving gear 205, the nut screw 201 is installed with a driven gear 206 through a bearing 203, the driving gear 205 and the driven gear 206 are connected through a synchronous belt 204, a spiral blade 208 is provided at one end of the nut screw 201, and a multifunctional soil sensor 207 is arranged in the central axis groove of the spiral blade 208.

[0163] Specifically, the drilling device 2 includes a nut screw 201, a drilling motor 202, a bearing 203, a synchronous belt 204, a driving gear 205, a driven gear 206, a multifunctional soil sensor 207, and a spiral blade 208; the nut screw 201 is fixed on the chassis 102 of the mobile body 1 side by side with the drilling motor 202 through the bearing 203; the driving gear 205 is fixedly connected to the output shaft end of the drilling motor 202; the driven gear 206 is installed on the nut screw 201 and is located below the bearing 203, and the outer walls of the driving gear 205 and the driven gear 206 are sleeved with a synchronous belt 204 to transmit power; the spiral blade 208 is installed at the bottom of the nut screw 201, and the multifunctional soil sensor 207 is installed in the central axis groove of the spiral blade 208 to detect the soil temperature, humidity and conductivity (reflecting the salt content of the soil) in real time and adjust the drilling depth in real time.

[0164] Further, such as Figure 4 As shown, the seedling throwing device 3 includes a conveying screw module 302 and a seedling throwing tube 307. The conveying screw module 302 is connected to a conveying motor 301 and a seedling tray 303. The conveying motor 301 provides power for the conveying screw module 302 to drive the seedling tray 303 to move. The seedling tray 303 is provided with a bottom cover, and the bottom cover is connected to a bottom cover motor 304 through a rotating hinge 305. The seedling throwing tube 307 is arranged below the seedling tray 303 and is fixedly connected to the chassis 102 of the mobile body 1. The center of the seedling throwing tube 307 is on the same straight line as the spiral blade 208 of the punching device 2 and is 20 cm apart. The seedling tray 303 and the seedling throwing tube 307 are made of silicone and have smooth inner walls.

[0165] Specifically, the seedling throwing device 3 is composed of a conveying motor 301, four groups of conveying screw rod modules 302, a seedling tray 303, a bottom cover motor 304, a rotating hinge 305, a seedling tray bottom cover 306 and a seedling throwing tube 307; the conveying motor 301 is fixedly connected to the shaft ends of the four groups of conveying screw rod modules 302, the four groups of conveying screw rod modules 302 are placed above the middle end of the mobile body 1, and two groups of conveying screw rod modules 302 are distributed horizontally, and the other two groups of conveying screw rod modules 302 are longitudinally fixed under the transverse modules, and the seedling tray 303 is fixed to the two longitudinal groups of screw rod modules. On the rod module, the bottom cover motor 304 is placed at the bottom of the seedling tray 303, and the seedling tray bottom cover 306 is fixedly connected to the output shaft end of the bottom cover motor 304 through a rotating hinge 305. The seedling throwing tube 307 is placed under the seedling tray 303 and is fixedly connected to the chassis 102 of the mobile body 1. The center of the seedling throwing tube 307 and the spiral blade 208 of the punching device 2 are in the same straight line and are 20 cm apart; the seedling tray 303 and the seedling throwing tube 307 are made of silicone material and have a smooth inner wall, which can prevent the seedlings from being damaged or twisted during the precise vertical seedling throwing process.

[0166] When seedlings are transported and released, among the four groups of conveying screw modules 302, two groups of longitudinally distributed conveying screw modules and two groups of transversely distributed screw modules are driven by the conveying motor 301 to drive the seedling tray 303 to move in the plane formed by the longitudinal and transverse screw modules; when the seedling holes on the seedling tray 303 are concentric with the seedling delivery tube 307, the industrial control computer 505 controls the bottom cover motor 304 to operate, and controls the opening of the bottom cover by rotating the hinge 305 to release the seedlings.

[0167] Further, such as Figure 5 As shown, the soil compacting device 4 includes a soil screw module 402 and a compacting plate 404. The soil screw module 402 is connected to a soil motor. The compacting plate 404 is connected to the soil screw module 402 through a connecting rod. A cylinder 403 is provided on the compacting plate 404, and a groove is provided on the compacting plate 404.

[0168] Specifically, the soil compacting device 4 includes a soil screw module 402, which is placed at the rear end of the seedling throwing device 3 and fixedly connected to the chassis 102 of the mobile vehicle 1, and the center of the soil screw module 402 is 20 cm away from the center of the seedling throwing tube 307; the axial end of the soil screw module 402 is connected to a soil motor 401, and compacting plates 404 with grooves are installed on both sides to avoid damaging the seedlings during the soil compacting process, and a cylinder 403 is fixed on the upper surface of the compacting plate 404. The pressure of the compacting plate is adjusted by controlling the air pressure of the cylinder 403, so that the soil can be effectively compacted without damaging the seedlings during the soil compacting process.

[0169] Further, such as Figure 6 As shown, the control device 5 includes a LIDAR sensor 501, an ultrasonic sensor 502, an inertial measurement unit 503, an air compressor 504, an industrial computer 505 and a power supply 506 arranged on the chassis 102 of the mobile vehicle body 1. The inertial measurement unit 503 includes an accelerometer and a gyroscope. The power supply 506 and the industrial computer 505 are respectively connected to the steering motor 105, the driving motor 107, the punching motor 202, the conveying motor 301, the bottom cover motor 304, the soil lofting motor 401, the LIDAR sensor 501, the ultrasonic sensor 502, and the inertial measurement unit 503 for electrical power and communication.

[0170] Specifically, the control device 5 includes a LIDAR sensor 501, an ultrasonic sensor 502, an inertial measurement unit 503, an air compressor 504, an industrial computer 505 and a power supply 506; the LIDAR sensor 501 is installed at the front end of the chassis 102 of the mobile body 1; the ultrasonic sensor 502 is fixed on both sides and the bottom of the chassis 102 of the mobile body 1; the power supply 506, the air compressor 504 and the industrial computer 505 are fixed at the rear end of the chassis 102 of the mobile body 1; the power supply 506 and the industrial computer 505 are respectively connected to the steering motor 105, the drive motor 107, the punching motor 202, the conveying motor 301, the bottom cover motor 304, the soil motor 401, the LIDAR sensor 501, the ultrasonic sensor 502, and the inertial measurement unit 503 for power connection and communication connection.

[0171] Furthermore, the industrial computer 505 of the control device 5 uses a three-dimensional extended Kalman filter to perform information fusion based on the environmental information measured by the LIDAR sensor 501, the ultrasonic sensor 502, and the inertial measurement unit 503, and drives the planting device to move precisely along the ridge under the control of the industrial computer 505, specifically:

[0172] First, a coordinate system is established with the center of gravity of the planting device as the origin, the ground as the XY plane, and the vertical upward as the Z axis, and the positions of the LIDAR sensor 501, the ultrasonic sensor 502, and the inertial measurement unit 503 are uniformly converted into the coordinate system;

[0173] Establish the state vector X of the three-dimensional extended Kalman filter k and the observation vector Z k :

[0174] X k =[x k y k z k θ k φ k Ψ k v k ω k ] T

[0175] Z k =[z l z u z i，a z i，b ] T

[0176] Among them, x k ,y k 、z k is the coordinate position of the center of gravity, that is (0, 0, 0); θ k is the yaw angle (rotation angle of the planting device around the Z axis); φk is the pitch angle (rotation angle of the planting device around the Y axis); k is the roll angle (rotation angle of the implant device around the X axis); v k is the speed (the moving speed of the implant device in three-dimensional space); ω k is the angular velocity (rotational speed of the center of gravity of the planting device);

[0177] The measurement data of LIDAR sensor 501 is: l =[z l，x z l，y z l，z ] T

[0178] The measurement data of ultrasonic sensor 502 is: u =[z u，x z u，y z u，z ] T

[0179] Among them, z l，x 、z l，y 、z l，z are the relative distances from the center of gravity of the planting device to the surrounding objects in the X, Y, and Z directions measured by the LIDAR sensor 501, respectively;

[0180] z u，x 、z u，y 、z u，z are the relative positions of the center of gravity of the planting device to the close-range obstacle in the X, Y, and Z directions measured by the ultrasonic sensor 502, respectively;

[0181] The accelerometer measurement data is: z i，a =[a i，x a i，y a i，z ] T

[0182] The gyroscope measurement data is: z i，b =[b i，x b i，y b i，z ] T

[0183] Among them, a i，x 、a i，y 、a i，z are the accelerations of the planting device in the X, Y, and Z directions respectively; b i，x 、b i，y 、b i，z are the rotation rates of the planting device in the X, Y, and Z directions, respectively;

[0184] Secondly, establish a prediction model (predict the next state) and state vector prediction (predict the next state based on the current state and control input):

[0185] State vector prediction:

[0186]

[0187] Among them, f(X k , U k ) is the state transfer function, U k is the control input, W k is the process noise, and W k ~N(0,Q k ), with covariance Q k ;

[0188] The state transfer function is:

[0189] Covariance prediction (predicting the uncertainty of the state at the next moment):

[0190]

[0191] Among them, F k is the Jacobian matrix of the state transfer function to the state vector, that is: is the prior covariance matrix at time k+1, P k is the posterior covariance matrix at time k;

[0192] Finally, measurement update is to use the measured value to correct the predicted state to obtain a more accurate state estimate;

[0193] The measurement model updates the state estimate:

[0194] in, is the measurement function, V k+1 is the measurement noise and is subject to V k+1 ~N(0,R k+1 ), with covariance R k+1 ;

[0195] Measurement function:

[0196] Kalman gain (measures the confidence of prediction and measurement, adjusts the state of prediction):

[0197]

[0198] Among them, H k is the Jacobian matrix of the measurement function to the state vector, that is: Rk is the measurement noise covariance matrix;

[0199] Status Update:

[0200] Covariance update: Where I is the identity matrix;

[0201] The industrial computer 505 controls the drive motor 107 and the steering motor 105 to drive the planting device to move according to the fused calculation update result.

[0202] The research on seedling retrieval mechanism of potted flower planters in domestic facility agriculture started late. Although some mechanical planting devices have been introduced into agricultural production, there are problems in target positioning, seedling retrieval accuracy, degree of automation, etc., the seedling retrieval success rate is low and the seedling injury rate is high, which cannot meet the actual production needs.

[0203] The control device 5 of the present invention includes a LIDAR sensor 501, an ultrasonic sensor 502, and an inertial measurement unit 503, which are used to sense external environmental information, use a three-dimensional extended Kalman filter to fuse the information obtained by the sensor, and accurately control the movement of the planting device, thereby avoiding damage to the seedlings caused by inaccurate movement of the planting device and improving the survival rate of the seedlings.

[0204] like Figure 7 As shown, the present invention also includes a method for automatically planting rose seedlings, comprising the following steps:

[0205] S1: Place the seedlings in the seedling tray 303 of the planting device, start the power supply 506, and the LIDAR sensor 501, the ultrasonic sensor 502 and the inertial measurement unit 503 perceive the environmental information in real time. The acquired environmental information is fused using a three-dimensional extended Kalman filter. The industrial computer 505 controls the drive motor 107 and the steering motor 105 to move the planting device according to the fused calculation update result.

[0206] More specifically, the industrial computer 505 controls the drive motor 107 and the steering motor 105 according to the fused calculation update result to enable the planting device to move precisely along the field ridges. Precise movement means that the planting device moves in a direction parallel to the field ridges.

[0207] S2: The industrial computer 505 controls the driving motor 107 and the steering motor 105 according to the environmental information to move the planting device to the target planting position, and the punching device 2 is started. The industrial computer 505 controls the punching motor 202 to operate. The punching motor 202 drives the nut screw 201 to rotate through the gear and the synchronous belt 204, and drives the spiral blade 208 to rotate to form the first planting hole on the planting bed. During the punching process, the multifunctional soil sensor 207 monitors the soil temperature, humidity and conductivity at the drilling position of the planting bed in real time. The control device 5 controls the punching device 2 to adjust the drilling depth according to the soil temperature, humidity and conductivity.

[0208] S3: The industrial computer 505 controls the driving motor 107 and the steering motor 105 according to the environmental information to move the planting device to the next target planting position. The punching device 2 and the seedling throwing device 3 are started at the same time. The punching device 2 punches holes on the planting bed to form a second planting hole. The conveying motor 301 of the seedling throwing device 3 drives the conveying screw module 302 to move the seedling tray 303 in a plane so that the hole of the seedling tray 303 is concentric with the seedling throwing tube 307. The bottom cover motor 304 controls the bottom cover 306 of the seedling tray to open by rotating the hinge 305. The seedlings are thrown into the first planting hole through the seedling throwing tube 307 due to gravity.

[0209] S4: The industrial computer 505 controls the driving motor 107 and the steering motor 105 according to the environmental information to move the planting device to the next target planting position, and the punching device 2, the seedling throwing device 3 and the soil compacting device 4 are started at the same time. The punching device 2 punches holes on the planting bed to form the third planting hole, and the seedling throwing device 3 throws the seedling into the previous planting hole. At the same time, the industrial computer 505 controls the soil motor 401 of the soil compacting device 4 to drive the soil screw module 402 to move the compacting plate 404 to fill the planting hole after the previous seedling was thrown, and then the cylinder 403 controls the compacting plate 404 to compact the soil.

[0210] S5: S4 is repeatedly executed until the punching device 2 completes the last punching, the punching device 2 stops working, the seedling device 3 stops working after running once more, and the soil compacting device 4 stops working after running twice more.

[0211] The present invention can monitor the temperature, humidity and conductivity of the soil in real time when drilling holes, and adjust the drilling depth in real time according to the soil conditions, so that the seedling planting depth is more reasonable and controllable. The drilling device 2, the seedling throwing device 3, and the soil compacting device 4 of the present invention are arranged on the mobile body 1 at equal intervals, and the three work together so that the planting spacing between the seedlings is also equal, and the seedling spacing is uniform and reasonable.

[0212] Furthermore, the control device 5 controls the drilling device 2 to adjust the drilling depth according to the soil temperature, humidity and conductivity:

[0213] The control device 5 establishes a state model, including a state equation and an output equation, sets an optimization function, solves the model according to the constraint conditions to obtain the drilling depth, and the control device 5 controls the drilling device 2 according to the solution result;

[0214] The state equation is: f(k+1)=Af(k)+Bu(k);

[0215] The output equation is: y(k) = Cf(k) + Du(k);

[0216] in f(k) is the current state vector, t(k), s(k) and e(k) are the soil temperature, moisture and conductivity at the kth moment, u(k) is the adjustment amount of the drilling depth, y(k) is the drilling depth at the kth moment, A, B, C and D are the state transfer matrix, control matrix, output matrix and direct transfer matrix respectively;

[0217] The optimization function is:

[0218]

[0219] Where y(k+Δk) is the predicted drilling depth, y i (k+Δk) is the expected perforation depth, N is the predicted time domain length, and m is the regularization parameter;

[0220] The constraints are: min ≤u(k)≤u max ;y min ≤y(k)≤y max .

[0221] Among them, the constraint parameters are obtained through field performance testing of the device and material properties, min ,y max They are the minimum and maximum drilling depths that the device can achieve, ensuring that the design limit of the machine is not exceeded; min 、u max The minimum and maximum drilling depth adjustments are set based on the motor's operating limitations and safety requirements;

[0222] Furthermore, the LIDAR sensor 501, the ultrasonic sensor 502 and the inertial measurement unit 503 sense the environmental information in real time, and the acquired environmental information is fused using the three-dimensional extended Kalman filter. The industrial computer 505 controls the driving motor 107 and the steering motor 105 to move the planting device according to the fused calculation update result. Specifically:

[0223] First, a coordinate system is established with the center of gravity of the planting device as the origin, the ground as the XY plane, and the vertical upward as the Z axis, and the positions of the LIDAR sensor 501, the ultrasonic sensor 502, and the inertial measurement unit 503 are uniformly converted into the coordinate system;

[0224] Establish the state vector X of the three-dimensional extended Kalman filter k and the observation vector Z k :

[0225] X k =[x k y k z k θ k φ k Ψ k v k ω k ] T

[0226] Z k =[z l z u z i，a z i，b ] T

[0227] Among them, x k ,y k 、z k is the coordinate position of the center of gravity, the initial value is (0, 0, 0), θ k is the yaw angle, φ k is the pitch angle, Ψ k is the roll angle, v k is the speed, ω k is the angular velocity;

[0228] The measurement data of LIDAR sensor 501 is: l =[z l，x z l，y z l，z ] T

[0229] The measurement data of ultrasonic sensor 502 is: u =[z u，x z u，y z u，z ] T

[0230] Among them, z l，x 、z l，y 、z l，z are the relative distances from the center of gravity of the planting device to the surrounding objects in the X, Y, and Z directions measured by the LIDAR sensor 501, respectively;

[0231] z u，x 、z u，y 、z u，z are the relative positions of the center of gravity of the planting device to the close-range obstacle in the X, Y, and Z directions measured by the ultrasonic sensor 502, respectively;

[0232] The accelerometer measurement data is: z i，a =[a i，x a i，y a i，z ] T

[0233] The gyroscope measurement data is: z i，b =[b i，x b i，y b i，z ] T

[0234] Among them, a i，x 、a i，y 、a i，z are the accelerations of the planting device in the X, Y, and Z directions respectively; b i，x 、b i，y 、b i，z are the rotation rates of the planting device in the X, Y, and Z directions, respectively;

[0235] Secondly, a prediction model is established to predict the state and uncertainty at the next moment based on the current state and control input;

[0236] State vector prediction:

[0237]

[0238] Among them, f(X k , U k ) is the state transfer function, U k is the control input, W k is the process noise, and W k ~N(0,Q k ), with covariance Q k ;

[0239] The state transfer function is:

[0240] Covariance prediction:

[0241]

[0242] Among them, F k is the Jacobian matrix of the state transfer function to the state vector, is the prior covariance matrix at time k+1, P kis the posterior covariance matrix at time k;

[0243] Finally, measurement update is to use the measured value to correct the predicted state to obtain a more accurate state estimate;

[0244] The measurement model updates the state estimate:

[0245] in, is the measurement function, V k+1 is the measurement noise and is subject to V k+1 ~N(0,R k+1 ), with covariance R k+1 ;

[0246] The measurement function is:

[0247] Kalman gain:

[0248]

[0249] Among them, H k is the Jacobian matrix of the measurement function with respect to the state vector, R k is the measurement noise covariance matrix;

[0250] Status Update:

[0251] Covariance update: Wherein, I is the unit matrix; the industrial computer 505 controls the driving motor 107 and the steering motor 105 to drive the planting device to move according to the fused calculation update result.

[0252] The control device 5 of the present invention includes a LIDAR sensor 501, an ultrasonic sensor 502, and an inertial measurement unit 503, which are used to sense external environmental information, use a three-dimensional extended Kalman filter to fuse the information obtained by the sensor, and accurately control the movement of the planting device, thereby avoiding damage to the seedlings caused by inaccurate movement of the planting device.

[0253] The working principle of the present invention is as follows: the device is driven by a driving motor 107, and the chassis 102, the steering connecting frame 103, the steering shaft 104 and the steering motor 105 are used to accurately control the moving direction and position, so as to ensure the stability and flexibility of the device in the field. Subsequently, the punching device 2 is started, wherein the nut screw 201 and the spiral blade 208 are driven by the punching motor 202, and rotate into the soil to punch holes. At the same time, the multifunctional soil sensor 207 in the device monitors the soil temperature, humidity and conductivity in real time, and adjusts the punching depth in real time according to the soil conditions to ensure a suitable planting environment. Then, the seedling throwing device 3 accurately places the seedlings from the seedling tray 303 into the pre-punched holes through four sets of conveying screw modules 302. Finally, the soil compacting device 4 follows the operation, and its soil screw module 402 is driven by the soil motor 401, and the compacting plates 404 on both sides compact the soil to ensure that the seedlings are in close contact with the soil and promote the development of the root system. During the entire planting process, the LIDAR sensor 501, ultrasonic sensor 502 and inertial measurement unit 503 work together to fuse information through a three-dimensional extended Kalman filter, which is uniformly dispatched and controlled by an industrial computer 505 to ensure the continuity and high-precision execution of operations, thus realizing the automation and intelligence of planting.

[0254] The working process of the present invention is as follows: the seedlings are placed in the seedling tray 303 of the planting device, the power supply 506 supplies power to the entire device, the LIDAR sensor 501, the ultrasonic sensor 502 and the inertial measurement unit 503 perceive the environmental information in real time, the acquired information is fused using a three-dimensional extended Kalman filter, and the industrial computer 505 controls the drive motor 107 and the steering motor to move accurately to the target planting position according to the information.

[0255] After reaching the first designated position, the punching device 2 is started, and the industrial computer 505 controls the operation of the punching motor 202. The punching motor 202 drives the nut screw 201 to rotate through the gear and the synchronous belt 204, driving the spiral blade 208 to form the first planting hole on the planting bed. During the punching process, the multifunctional soil sensor 207 monitors the soil temperature, humidity and conductivity in real time, and adjusts the punching depth in real time according to the soil conditions.

[0256] After reaching the second designated position, the punching device 2 and the seedling throwing device 3 are started at the same time. The punching device 2 forms the second planting hole on the planting bed, and the conveying motor 301 of the seedling throwing device 3 drives the four sets of conveying screw modules 302 to move the seedling tray 303 in a plane, so that the holes of the seedling tray 303 are concentric with the seedling throwing tube 307, and the bottom cover motor 304 controls the seedling tray bottom cover 306 to open by rotating the hinge 305, and the seedlings are thrown into the first planting hole through the seedling throwing tube 307 due to gravity.

[0257] From the third to the last drilling, the drilling device 2, the seedling throwing device 3 and the soil compacting device 4 are started at the same time. The drilling device 2 makes a new hole, and the seedling throwing device 3 throws the seedling into the previous hole. At the same time, the industrial computer 505 controls the soil motor 401 of the soil compacting device 4 to drive the soil screw module 402 to move the compacting plate 404 to compact the soil in the hole after the previous seedling was thrown. Then the cylinder 403 controls the compacting plate 404 to compact the soil under the drive of the air compressor 504 to ensure that the soil at the root of the seedling fits tightly.

[0258] After the last drilling is completed, the drilling device 2 stops working, the seedling throwing device 3 operates once more, and the soil compacting device 4 operates twice more, and then stops working one after another.

[0259] In view of the shortcomings of the existing technology, the present invention provides an automatic planting device and method for rose seedlings, which solves the problems of unreasonable seedling spacing, high density, large mechanical damage to seedlings and low degree of automation in the existing technology, and combines modern automation technology, advanced sensor systems and three-dimensional extended Kalman filter information fusion mechanism to reduce mechanical damage to seedlings and achieve efficient and precise field planting operations.

[0260] The rose seedling automatic planting device provided by the present invention combines modern automation technology, advanced sensor systems, prediction models and three-dimensional extended Kalman filter information fusion mechanism to achieve efficient and accurate field planting operations, and has the following beneficial effects:

[0261] 1. The present invention uses a power supply to power the planting device, and the LIDAR sensor, ultrasonic sensor and inertial measurement unit sense the external environment information, and uses a three-dimensional extended Kalman filter to fuse the information obtained by the sensor to accurately control the movement of the planting device.

[0262] 2. The drilling device is equipped with a multifunctional soil sensor, which can monitor the soil temperature, humidity and electrical conductivity in real time during drilling, and adjust the drilling depth in real time according to the soil conditions; the drilling device, seedling planting device and soil compaction device are installed on the device at equal intervals, and the three are operated and stopped successively.

[0263] 3. The seedlings are transported and released using four sets of screw modules working together, and individual plants are transported in sequence; the seedling tray and seedling tube are made of silicone, and the surface of the silicone pipe is smooth, which reduces damage to the seedlings; the compaction plate has grooves to avoid damage to the seedlings during the soil-laying process.

[0264] 4. The overall design structure of the present invention is simple, which is convenient for equipment maintenance and component replacement.

[0265] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0266] It is not difficult for those skilled in the art to understand that the present invention includes any combination of the invention content and specific implementation methods of the above specification and the various parts shown in the drawings. Due to the limited space and to make the specification concise, the various schemes composed of these combinations are not described one by one. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0267] Although the embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. Those skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention without departing from the principles and purpose of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A rose seedling automatic planting device, comprising a mobile body, characterized in that: The mobile vehicle body is provided with a punching device, a seedling throwing device, a soil compacting device and a control device, wherein the punching device is placed in the middle of the front end of the mobile vehicle body; the seedling throwing device and the soil compacting device are located on the same axis as the punching device and are placed on the mobile vehicle body in sequence at equal intervals; the punching device includes a multifunctional soil sensor, which detects soil temperature, humidity and conductivity in real time; The control device controls the drilling device to adjust the drilling depth in real time according to the soil temperature, humidity and conductivity as follows: The control device establishes a state model, including a state equation and an output equation, sets an optimization function and constraint conditions to solve the model to predict the state and output at N moments in the future, optimizes the model prediction according to the soil temperature, humidity and conductivity, and adjusts the drilling depth; The state equation is: f(k+1)=Af(k)+Bu(k); The output equation is: y(k)=Cf(k)+Du(k); in f(k) is the current state vector, t(k), s(k) and e(k) are the soil temperature, moisture and conductivity at the kth moment, u(k) is the adjustment amount of the drilling depth, y(k) is the drilling depth at the kth moment, A, B, C and D are the state transfer matrix, control matrix, output matrix and direct transfer matrix respectively; The state at the kth moment is known and the state vector is x(k): The transfer state matrix A describes the influence of the state at time k on the state at time k+1: a 11 、a 12 、a 13 They represent the influence coefficients of soil temperature t(k) at the kth moment, soil moisture s(k) at the kth moment, and electrical conductivity e(k) at the kth moment on soil temperature t(k+1) at the k+1th moment respectively; a 21 、a 22 、a 23 They represent the influence coefficients of soil temperature t(k) at the kth moment, soil moisture s(k) at the kth moment, and electrical conductivity e(k) at the kth moment on soil moisture s(k+1) at the k+1th moment respectively; a 31 、a 32 , a 33 The influence coefficients of soil temperature t(k) at the kth moment, soil moisture s(k) at the kth moment, and electrical conductivity e(k) at the kth moment on soil electrical conductivity e(k+1) at the k+1th moment respectively; The control matrix B describes the influence of the drilling depth adjustment u(k) at the kth moment on the state at the k+1th moment: B=[b 11 b 21 b 31 ] Τ ; b 11 , b 21 , b 31 They are respectively expressed as the influence coefficients of the drilling depth adjustment u(k) at the kth moment on the soil temperature t(k+1), soil moisture s(k+1), and soil conductivity e(k+1) at the k+1th moment; The output matrix C describes the influence of the state at the kth moment on the perforation depth y(k) at the kth moment: C=[C 11 C 12 C 13 ]; C 11 , C 12 , C 13 are the influence coefficients of soil temperature t(k), soil moisture s(k) and electrical conductivity e(k) at the kth moment on the drilling depth y(k) at the kth moment; The direct transfer matrix D describes the direct impact of the drilling depth adjustment u(k) at the kth moment on the drilling depth y(k) at the kth moment. In the system, the drilling depth is mainly adjusted indirectly by the changes in soil temperature, humidity, and conductivity, and is not directly determined by the drilling depth adjustment. Therefore, the matrix D = 0. The optimization function is: Where y(k+Δk) is the predicted drilling depth, y i (k+Δk) is the expected perforation depth, N is the predicted time domain length, and m is the regularization parameter; The constraints are: min ≤u(k)≤u max ;y min ≤y(k)≤y max ; Among them, y min ,y max are the minimum and maximum drilling depths that the device can achieve, u min 、u max They are the minimum and maximum drilling depth adjustment amounts respectively; Solve the optimization problem and obtain the optimal drilling depth adjustment sequence for the next N moments as follows: {u(k),u(k+1),…,u(k+N-1)}; Real-time control: Control input calculation: Solve the optimization problem, the optimal drilling depth adjustment sequence for the next N moments: {u(k),u(k+1),…,u(k+N-1)}; Real-time adjustment: Apply the first drilling depth adjustment u(k) to the system and adjust the drilling depth in real time: y(k)=Cf(k)+Du(k); Update system status: Update the system status based on the latest status and control input: f(k+1)=Af(k)+Bu(k); The time step is k, and the above steps are repeated. The sensor continuously collects data, performs model prediction optimization, and adjusts the drilling depth.

2. The rose seedling automatic planting device according to claim 1, characterized in that: The mobile vehicle body includes a chassis, which is connected to a plurality of wheels via a steering shaft and a connecting frame, and the wheels are provided with tracks. A steering motor and a drive motor are provided on the chassis, and the steering motor is used to control the steering shaft, and the drive motor is used to drive the wheels.

3. The rose seedling automatic planting device according to claim 2, characterized in that: The punching device includes a nut screw and a punching motor, the punching motor is connected to a driving gear, the nut screw is installed with a driven gear through a bearing, the driving gear and the driven gear are connected through a synchronous belt, one end of the nut screw is provided with a spiral blade, and the multifunctional soil sensor is arranged in the center axis groove of the spiral blade.

4. The rose seedling automatic planting device according to claim 3, characterized in that: The seedling throwing device includes a conveying screw module and a seedling throwing tube, the conveying screw module is connected to a conveying motor and a seedling tray, the conveying motor provides power to the conveying screw module to drive the seedling tray to move, the seedling tray is provided with a bottom cover, and the bottom cover is connected to a bottom cover motor through a rotating hinge, the seedling throwing tube is arranged under the seedling tray and is fixedly connected to the chassis of the mobile vehicle body, the center of the seedling throwing tube is on the same straight line as the spiral blade of the punching device and is 20 cm apart, the seedling tray and the seedling throwing tube are made of silicone material and have smooth inner walls.

5. The rose seedling automatic planting device according to claim 4, characterized in that: The soil compacting device comprises a soil screw module and a compacting plate, wherein the soil screw module is connected to a soil motor, the compacting plate is connected to the soil screw module via a connecting rod, a cylinder is arranged on the compacting plate, and a groove is arranged on the compacting plate.

6. The rose seedling automatic planting device according to claim 5, characterized in that: The control device includes a LIDAR sensor, an ultrasonic sensor, an inertial measurement unit, an air compressor, an industrial computer and a power supply arranged on the chassis of the mobile vehicle body. The inertial measurement unit includes an accelerometer and a gyroscope. The power supply and the industrial computer are respectively electrically connected and communicatively connected to the steering motor, the drive motor, the punching motor, the conveying motor, the bottom cover motor, the soil-carrying motor, the LIDAR sensor, the ultrasonic sensor and the inertial measurement unit.

7. The rose seedling automatic planting device according to claim 6, characterized in that: The industrial computer of the control device uses a three-dimensional extended Kalman filter to perform information fusion according to the environmental information measured by the LIDAR sensor, the ultrasonic sensor, and the inertial measurement unit, and drives the planting device to move under the control of the industrial computer, specifically: First, a coordinate system is established with the center of gravity of the planting device as the origin, the ground as the XY plane, and the vertical upward as the Z axis, and the positions of the LIDAR sensor, the ultrasonic sensor, and the inertial measurement unit are uniformly converted into the coordinate system; Establish the state vector X of the three-dimensional extended Kalman filter k and the observation vector Z k : X k =[x k y k z k i k f k P k v k oh k ] Τ WITH k =[of l With u With i，a With i，b ] Τ Among them, x k ,y k 、z k is the coordinate position of the center of gravity, the initial value is (0, 0, 0), θ k is the yaw angle, φ k is the pitch angle, Ψ k is the roll angle, v k is the speed, ω k is the angular velocity; The LIDAR sensor measurement data is: l =[z l，x z l，y z l，z ] Τ The ultrasonic sensor measurement data is: u =[z u，x z u，y z u，z ] Τ Among them, z l，x 、z l，y 、z l，z are the relative distances from the center of gravity of the planting device to the surrounding objects in the X, Y, and Z directions measured by the LIDAR sensor, respectively; z u，x 、z u，y 、z u，z are the relative positions of the center of gravity of the planting device to the close-range obstacle in the X, Y, and Z directions measured by the ultrasonic sensor, respectively; The accelerometer measurement data is: z i，a =[a i，x a i，y a i，z ] Τ The gyroscope measurement data is: z i，b =[b i，x b i，y b i，z ] Τ Among them, a i，x 、a i，y 、a i，z are the accelerations of the planting device in the X, Y, and Z directions respectively; b i，x , b i，y , b i，z are the rotation rates of the planting device in the X, Y, and Z directions, respectively; Secondly, a prediction model is established to predict the state and uncertainty at the next moment based on the current state and control input; State vector prediction: Among them, f(X k ,U k ) is the state transfer function, U k is the control input, W k is the process noise, and W k ~N(0,Q k ), with covariance Q k ; The state transfer function is: Covariance prediction: Among them, F k is the Jacobian matrix of the state transfer function to the state vector, is the prior covariance matrix at time k+1, P k is the posterior covariance matrix at time k; Finally, measurement update is to use the measured value to correct the predicted state to obtain a more accurate state estimate; The measurement model updates the state estimate: in, is the measurement function, V k+1 is the measurement noise and is subject to V k+1 ~N(0,R k+1 ), with covariance R k+1 ; Kalman gain: Among them, H k is the Jacobian matrix of the measurement function with respect to the state vector, R k is the measurement noise covariance matrix; Status Update: Covariance update: Where I is the identity matrix; The industrial computer controls the drive motor and steering motor according to the fused calculation update results to drive the planting device to move.

8. A method for automatically planting rose seedlings, characterized in that: The following steps are involved: S1: Place the seedlings in the seedling tray of the planting device, start the power supply, and the LIDAR sensor, ultrasonic sensor and inertial measurement unit perceive the environmental information in real time. The acquired environmental information is fused using a three-dimensional extended Kalman filter. The industrial computer controls the drive motor and steering motor according to the fused calculation update result to make the planting device move accurately along the ridge. S2: The industrial computer controls the driving motor and the steering motor according to the environmental information to move the planting device to the target planting position, the drilling device starts, and the industrial computer controls the drilling motor to operate. The drilling motor drives the nut screw to rotate through the gear and the synchronous belt, and drives the spiral blade to rotate to form the first planting hole on the planting bed. During the drilling process, the multifunctional soil sensor monitors the soil temperature, humidity and conductivity at the drilling position of the planting bed in real time. The control device controls the drilling device to adjust the drilling depth according to the soil temperature, humidity and conductivity. S3: The industrial computer controls the driving motor and the steering motor according to the environmental information to move the planting device to the next target planting position. The punching device and the seedling throwing device are started at the same time. The punching device punches holes on the planting bed to form a second planting hole. The conveying motor of the seedling throwing device drives the conveying screw module to move the seedling tray in a plane so that the hole of the seedling tray is concentric with the seedling throwing tube. The bottom cover motor controls the bottom cover of the seedling tray to open by rotating the hinge. The seedlings are thrown into the first planting hole through the seedling throwing tube due to gravity. S4: The industrial computer controls the driving motor and the steering motor according to the environmental information to move the planting device to the next target planting position, and the punching device, the seedling throwing device and the soil compacting device are started at the same time. The punching device punches holes on the planting bed to form a third planting hole, and the seedling throwing device throws seedlings into the previous planting hole. At the same time, the industrial computer controls the soil motor of the soil compacting device to drive the soil screw module to move the compacting plate to fill the planting hole after the previous seedling is thrown, and then the cylinder controls the compacting plate to compact the soil; S5: Repeat S4 until the punching device completes the last punching, then stops working, the seedling throwing device stops working after running once again, and the soil compacting device stops working after running twice again; The control device controls the punching device to adjust the punching depth according to the soil temperature, humidity and conductivity: The control device establishes a state model, including a state equation and an output equation, sets an optimization function, solves the model according to the constraint conditions to obtain the drilling depth, and the control device controls the drilling device according to the solution result; The state equation is: f(k+1)=Af(k)+Bu(k); The output equation is: y(k)=Cf(k)+Du(k); in f(k) is the current state vector, t(k), s(k) and e(k) are the soil temperature, moisture and conductivity at the kth moment, u(k) is the adjustment amount of the drilling depth, y(k) is the drilling depth at the kth moment, A, B, C and D are the state transfer matrix, control matrix, output matrix and direct transfer matrix respectively; The state at the kth moment is known and the state vector is x(k): The transfer state matrix A describes the influence of the state at time k on the state at time k+1: a 11 、a 12 、a 13 They represent the influence coefficients of soil temperature t(k) at the kth moment, soil moisture s(k) at the kth moment, and electrical conductivity e(k) at the kth moment on soil temperature t(k+1) at the k+1th moment respectively; a 21 、a 22 、a 23 They represent the influence coefficients of soil temperature t(k) at the kth moment, soil moisture s(k) at the kth moment, and electrical conductivity e(k) at the kth moment on soil moisture s(k+1) at the k+1th moment respectively; a 31 、a 32 , a 33 The influence coefficients of soil temperature t(k) at the kth moment, soil moisture s(k) at the kth moment, and electrical conductivity e(k) at the kth moment on soil electrical conductivity e(k+1) at the k+1th moment respectively; The control matrix B describes the influence of the drilling depth adjustment u(k) at the kth moment on the state at the k+1th moment: B=[b 11 b 21 b 31 ] Τ ; b 11 , b 21 , b 31 They are respectively expressed as the influence coefficients of the drilling depth adjustment u(k) at the kth moment on the soil temperature t(k+1), soil moisture s(k+1), and soil conductivity e(k+1) at the k+1th moment; The output matrix C describes the influence of the state at the kth moment on the perforation depth y(k) at the kth moment: C=[C 11 C 12 C 13 ]; C 11 , C 12 , C 13 are the influence coefficients of soil temperature t(k), soil moisture s(k) and electrical conductivity e(k) at the kth moment on the drilling depth y(k) at the kth moment; The direct transfer matrix D describes the direct impact of the drilling depth adjustment u(k) at the kth moment on the drilling depth y(k) at the kth moment. In the system, the drilling depth is mainly adjusted indirectly by the changes in soil temperature, humidity, and conductivity, and is not directly determined by the drilling depth adjustment. Therefore, the matrix D = 0. The optimization function is: Where y(k+Δk) is the predicted drilling depth, y i (k+Δk) is the expected perforation depth, N is the predicted time domain length, and m is the regularization parameter; The constraints are: min ≤u(k)≤u max ;y min ≤y(k)≤y max ; Among them, y min ,y max are the minimum and maximum drilling depths that the device can achieve, u min 、u max They are the minimum and maximum drilling depth adjustment amounts respectively; Solve the optimization problem and obtain the optimal drilling depth adjustment sequence for the next N moments as follows: {u(k),u(k+1),…,u(k+N-1)}; Real-time control: Control input calculation: Solve the optimization problem, the optimal drilling depth adjustment sequence for the next N moments: {u(k),u(k+1),…,u(k+N-1)}; Real-time adjustment: Apply the first drilling depth adjustment u(k) to the system and adjust the drilling depth in real time: y(k)=Cf(k)+Du(k); Update system status: Update the system status based on the latest status and control input: f(k+1)=Af(k)+Bu(k); The time step is k, and the above steps are repeated. The sensor continuously collects data, performs model prediction optimization, and adjusts the drilling depth.

9. The method for automatically planting rose seedlings according to claim 8, characterized in that: The LIDAR sensor, ultrasonic sensor and inertial measurement unit sense environmental information in real time. The acquired environmental information is fused using a three-dimensional extended Kalman filter. The industrial computer controls the drive motor and the steering motor to move the planting device according to the fused calculation update result. Specifically: First, a coordinate system is established with the center of gravity of the planting device as the origin, the ground as the XY plane, and the vertical upward as the Z axis, and the positions of the LIDAR sensor, the ultrasonic sensor, and the inertial measurement unit are uniformly converted into the coordinate system; Establish the state vector X of the three-dimensional extended Kalman filter k and the observation vector Z k : X k =[x k y k z k i k f k P k v k oh k ] Τ WITH k =[of l With u With i，a With i，b ] Τ Among them, x k ,y k 、z k is the coordinate position of the center of gravity, the initial value is (0, 0, 0), θ k is the yaw angle, φ k is the pitch angle, Ψ k is the roll angle, v k is the speed, ω k is the angular velocity; The LIDAR sensor measurement data is: l =[z l，x z l，y z l，z ] Τ The ultrasonic sensor measurement data is: u =[z u，x z u，y z u，z ] Τ Among them, z l，x 、z l，y 、z l，z are the relative distances from the center of gravity of the planting device to the surrounding objects in the X, Y, and Z directions measured by the LIDAR sensor, respectively; z u，x 、z u，y 、z u，z are the relative positions of the center of gravity of the planting device to the close-range obstacle in the X, Y, and Z directions measured by the ultrasonic sensor, respectively; The accelerometer measurement data is: z i，a =[a i，x a i，y a i，z ] Τ The gyroscope measurement data is: z i，b =[b i，x b i，y b i，z ] Τ Among them, a i，x 、a i，y 、a i，z are the accelerations of the planting device in the X, Y, and Z directions respectively; b i，x , b i，y , b i，z are the rotation rates of the planting device in the X, Y, and Z directions, respectively; Secondly, a prediction model is established to predict the state and uncertainty at the next moment based on the current state and control input; State vector prediction: Among them, f(X k ,U k ) is the state transfer function, U k is the control input, W k is the process noise, and W k ~N(0,Q k ), with covariance Q k ; The state transfer function is: Covariance prediction: Among them, F k is the Jacobian matrix of the state transfer function to the state vector, is the prior covariance matrix at time k+1, P k is the posterior covariance matrix at time k; Finally, measurement update is to use the measured value to correct the predicted state to obtain a more accurate state estimate; The measurement model updates the state estimate: in, is the measurement function, V k+1 is the measurement noise and is subject to V k+1 ~N(0,R k+1 ), with covariance R k+1 ; Kalman gain: Among them, H k is the Jacobian matrix of the measurement function with respect to the state vector, R k is the measurement noise covariance matrix; Status Update: Covariance update: Where I is the identity matrix; The industrial computer controls the drive motor and steering motor according to the fused calculation update results to drive the planting device to move.

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