A cross-ridge strawberry intelligent variable variable-spraying-width spraying robot structure and a control method thereof

Abstract

The application discloses a cross-ridge type intelligent variable variable-spraying-width spraying robot structure and a control method thereof. The cross-ridge type intelligent variable variable-spraying-width spraying robot structure comprises a cross-ridge type moving chassis 1, wherein the cross-ridge type moving chassis is composed of a driving wheel group 11, a universal wheel group 12, a chassis support 13 and a support platform 14; ultrasonic sensors 21 and a battery 3 are installed on both sides of the cross-ridge type moving chassis 1; a central processing module 5, a GNSS navigation module 23 and a telescopic spraying system 6 are fixed on the support platform 14; the telescopic spraying system is composed of a water tank 61, a water pump 62, a nozzle 63, a working support 64, a telescopic spraying rod 65, an electric push rod 66 and a PVC transparent hose 67; the ultrasonic sensors 21, an image acquisition module 22 and the GNSS navigation module 23 form a sensing module 2; the central processing module 5 processes the sensed data and provides computing power for track tracking of the robot. The application can realize autonomous variable variable-spraying-width spraying operation, and realizes man-machine separation through wireless image transmission.

Description

Technical Field

[0001] This invention relates to a spraying robot, and more specifically, to a cross-ridge intelligent variable-width spraying robot structure and control method. Background Technology

[0002] Strawberries are a high-value-added economic crop. Greenhouse cultivation of strawberries is not limited by season and is conducive to management and standardized planting. However, strawberry cultivation is plagued by frequent pests and diseases throughout the entire growth cycle, requiring extensive pesticide application. Furthermore, the spread of pests and diseases is exacerbated in greenhouse environments. Currently, due to the limited space of greenhouses, established field and orchard spraying machines are difficult to operate. In practical production, manual handheld spraying remains the primary method, resulting in low efficiency, pesticide waste, and high labor intensity and safety concerns. In addition, greenhouse cultivation requires irrigation to promote growth while controlling pests and diseases. To address this issue, an autonomous spraying robot capable of variable spray width and variable spray pattern has been designed. Summary of the Invention

[0003] Based on the above requirements for spraying operations in strawberry greenhouses, this invention discloses a cross-row intelligent variable-width spraying robot structure for strawberries.

[0004] The purpose of this invention is to design a cross-row intelligent variable-width spray robot structure for strawberries, which can realize tasks such as manual remote control, automatic control of the amount of pesticide applied according to the scene, automatic completion of strawberry greenhouse operation, automatic control of the extension of the spraying mechanism according to the application scene, and continuous operation.

[0005] The technical solution of the present invention includes: a cross-row strawberry intelligent variable spray width spray robot structure, including a cross-row mobile chassis (1), an ultrasonic sensor (21), a battery (3), an image acquisition module (22), a central processing module (5), a telescopic spray system (6), a GNSS navigation module (23), and a support platform (14).

[0006] The telescopic spray system (6) includes an electric push rod (66), a water tank (61), a water pump (62), a working bracket (64), a telescopic spray bar (65), a nozzle (63), and a PVC transparent hose (67).

[0007] The cross-ridge mobile chassis (1) consists of a drive wheel assembly (11), a universal wheel assembly (12), a chassis support (13), and a support platform (14). The chassis support (13) is equipped with a support platform (14). One end of the chassis support (13) is movably connected to the left front and right front drive wheel assemblies (11), and the other end is movably connected to the left rear and right rear universal wheel assemblies (12). The ultrasonic sensor (21), image acquisition module (22), GNSS navigation module (23), drive wheel assembly (11), electric push rod (66), and water pump (62) are electrically connected to the central processing module (5) to process the acquired data. It provides computing power for motor control and related algorithms; the support platform (14) is equipped with a telescopic spray system (6); the telescopic spray system (6) is realized by the telescopic function of the telescopic spray bar (65), the spray bar is controlled by an electric push rod (66) to extend and retract, and a nozzle (63) is installed at the lower end of the spray bar; the nozzle (63) is connected to the water pump (62) and the water tank (61) through a PVC transparent hose (67), the water pump (62) adjusts the flow rate of the water pump (62) and the spray volume of the nozzle (63) in real time according to the robot's walking speed, and the working support (64) and the chassis support (13) are connected by metal corner fittings.

[0008] Furthermore, the support platform (14) is made of acrylic material and is equipped with corresponding mounting holes according to the design requirements, so that the image acquisition module (22), water pump (62), water tank (61) and central processing module (5) are tightly fixed on the support platform (14); the support platform (14) is made of aluminum profiles and aluminum plates connected by metal feet, which provides support and load-bearing for the entire system while reducing the weight of the platform.

[0009] Furthermore, the cross-ridge mobile chassis (1) is used for the steering and attitude and position adjustment of the spraying robot, and provides a platform for the operation system; the cross-ridge mobile chassis (1) is driven by the drive wheel group (11) to drive the universal wheel group (12), and the environment is perceived by the ultrasonic sensor (21), the image acquisition module (22), and the GNSS navigation module (23). The drive wheel group (11) is controlled by the central control module (5) to change the forward speed and steering.

[0010] Furthermore, the water tank (61) is fixed on the support platform (14), and there are two water pumps (62), each of which controls the flow rate of a set of nozzles (63) connected to it. The water tank (61) is connected to the water pump (62) and the nozzles (63) through a PVC transparent hose (67). The nozzles (63) are fixed to the lower end of the telescopic spray bar (65) through pipe clamps. There are 26 nozzles (63) in total, which are arranged at equal intervals in the horizontal direction.

[0011] Furthermore, the battery (3) is a lithium battery, which is fixed in the support structure of the cross-ridge mobile chassis (1) to provide power to the water pump (62), electric push rod (66), drive wheel set (11), central control module (5), ultrasonic sensor (21), image acquisition module (22) and GNSS navigation module (23).

[0012] Furthermore, the telescopic spray bar (65) adopts a scissor-type telescopic structure. Considering strength and weight factors, the telescopic spray bar (65) adopts a structure combining double-layer and single-layer structures. Ultrasonic sensors (21) are fixed at both ends of the telescopic spray bar. The telescopic spray bar (65) is connected to an electric push rod (66). The central processing module (5) issues instructions to control the electric push rod (66) to perform push-pull actions based on the feedback from the ultrasonic sensors (21), thereby driving the telescopic spray bar (65) to extend and retract. The nozzle (63) is fixed to the lower end of the telescopic spray bar (65), and changes the robot spray width according to the extension and retraction of the telescopic spray bar (65).

[0013] Furthermore, the central processing module (5) is fixed on the support platform (14); the central processing module (5) is an STM32F103C8, which is electrically connected to the drive wheel group (11), water pump (62), and electric push rod (66) through the drive module; the image acquisition module (22) performs wireless image transmission through the WIFI function module of the central processing module (5).

[0014] The technical solution of the present invention is as follows: a control method for a cross-row strawberry intelligent variable spray width spray robot structure, using a GNSS navigation module (23) to obtain the longitude, latitude and altitude position information and robot posture information of the spray robot, using a pure tracking algorithm to track the path planned according to the actual situation of the orchard, using an RGBD camera to identify the strawberry plants, and combining the robot motion model to perform variable spraying;

[0015] Using the GNSS navigation module (23), the location information of the spraying robot's longitude, latitude, and altitude, as well as the robot's attitude information, are obtained. The following steps are taken to track the path planned according to the actual situation of the orchard using a pure tracking algorithm:

[0016] Step 1: Select the trajectory equation of the target being tracked or a given sequence of target points;

[0017] Step 2: Based on the robot's current state, calculate the lateral deviation and heading angle error of the vehicle from the target point;

[0018] Step 3: Calculate the forward sight distance based on the current lateral deviation and heading angle error;

[0019] Step 4: Calculate the vehicle's steering angle and speed command based on the forward sight distance and the vehicle's motion state;

[0020] Step 5: Convert the steering angle and speed commands into speed commands for the left and right wheels to achieve control;

[0021] The following method utilizes an RGBD camera to identify strawberry plants and combines this with a robot motion model for variable spraying:

[0022] Step 6: Acquire RGBD images. Use an RGBD camera to acquire image data of the strawberry greenhouse ridges, including RGB images and depth images, and perform image preprocessing.

[0023] Step 7: Object detection. Use the YOLOv4 algorithm to perform object detection on the RGB image, identify the strawberry target in the image, and obtain its bounding box, class label, and confidence score;

[0024] Step 8: Depth image processing. Using the depth image and target detection results, extract and process the strawberry target in the depth image.

[0025] Step 9: Edge detection. The Sobel edge detection algorithm is used to detect the edges of the strawberry target in the depth image to obtain the edge information of the strawberry target.

[0026] Step 10: Extract contours based on edge information;

[0027] Step 11: Calculate the width w and height h of the contour based on the object detection results and the contour information of the depth image;

[0028] Step 12, based on the speed at which the robot moves forward after detecting the target. Calculate the spray volume of each nozzle (63). If the width of the greenhouse is The length of the ridge is , row spacing is The number of nozzles on the telescopic spray boom (65) is The width of the strawberry plant is w, and the height of the strawberry plant is h.

[0029] Therefore, the calculation yields: (1);

[0030] Further results were obtained: (2);

[0031] Where k is a constant coefficient in the spray model, representing the distribution characteristics of strawberry plants, the performance of the nozzle, etc.

[0032] Meanwhile, considering the distance between the image acquisition module (22) and the nozzle (63), it is necessary to control the telescopic spray system (6) to perform delayed spraying on the processed spray control information, and the delay time t can be obtained: (3);

[0033] The distance between the image acquisition module (22) and the nozzle (63) in the robot's forward direction is x;

[0034] Step 13, based on the calculated spray volume of nozzle (63) The flow rate of the water pump (62) is controlled, thereby controlling the amount of spray from the robot. Based on the characteristics of the pure tracking algorithm, spraying needs to stop when turning; therefore, a spraying stop threshold needs to be set. When the robot's heading angle deviates from the straight line by more than Stop spraying when the time is right.

[0035] Traditional manual spraying mainly uses inefficient backpack sprayers, requiring workers to carry heavy sprayers. The enclosed, high-temperature environment of greenhouses further exacerbates the labor intensity. Compared to the drawbacks of manual spraying, such as overspraying, missed areas, and accidental spraying, this solution is characterized by "intelligent efficiency, high efficiency, and environmental friendliness." Based on real-time measurement data, it precisely controls the spray volume and spray range, improving spray uniformity. It automatically adjusts the spray volume according to the size and growth status of the strawberry plants, preventing leaf and root rot caused by overspraying. The cross-row mobile chassis structure enhances the robot's adaptability to the greenhouse environment, while the telescopic variable-width spray system is accurate and efficient. Wireless image transmission enables truly autonomous operation with separation of human and machine. Attached Figure Description

[0036] Figure 1 This is a side view of the present invention;

[0037] Figure 2 This is a schematic diagram of the cross-ridge mobile chassis structure of the present invention;

[0038] Figure 3 This is a schematic diagram of the telescopic spray boom structure of the present invention.

[0039] Figure 4 This is a schematic diagram of a scissor-type telescopic linkage structure;

[0040] Figure 5 This is a schematic diagram of ultrasonic ranging calculation;

[0041] Figure 6 This is a schematic diagram of the pure tracking algorithm calculation;

[0042] Figure 7 Flowchart for target recognition using an RGBD camera;

[0043] Figure 8 This is a flowchart of the robot control process.

[0044] The components are: 1-Cross-ridge mobile chassis, 11-Drive wheel set, 12-Universal wheel set, 13-Chassis support, 14-Support platform, 2-Data acquisition module, 21-Ultrasonic sensor, 22-Image acquisition module, 23-GNSS navigation module, 3-Battery, 5-Central processing module, 6-Telescopic spray system, 61-Water tank, 62-Water pump, 63-Nozzle, 64-Working support, 65-Telescopic spray boom, 66-Electric push rod, 67-PVC transparent hose, 111-Drive wheel, 112-Gear motor, 121-Small wheel, 122-Support structure, 651-Linkage node, 652-Beam arm, 653-End movable node, 654-End fixed node. Detailed Implementation

[0045] The following diagram illustrates the invention of a wheeled strawberry variable-width spray robot.

[0046] like Figure 1 The diagram shows the overall structure of a cross-row strawberry variable spray width spraying robot, which mainly consists of a cross-row mobile chassis (1), a telescopic spraying system (6), and a data acquisition module 2. The data acquisition module 2 includes an ultrasonic sensor (21), an image acquisition module (22), and a GNSS navigation module (23). The central processing module (5) processes the data and provides computing power for the algorithm.

[0047] like Figure 2 The drive of the cross-row mobile chassis (1) shown comes from two identical drive wheel sets (11), and steering is achieved by the differential speed of the two wheels. Two ultrasonic sensors (21) are installed on each side of the cross-row mobile chassis (1), located at the front and rear ends respectively. The drive wheels (111) are connected to a reduction motor (112), which is controlled by PWM. The central processing module further controls the wheel speed by controlling the duty cycle of the PWM. The drive wheel sets (11) are fixed to the chassis bracket (13) by bolts. The universal wheel set (12) is installed on the other side of the chassis. The universal wheel set (12) consists of a support structure (122) and small wheels (121). The small wheels (121) are connected to the support structure (122) through a wheel axle and can roll in multiple directions. The differential wheels are used to control the forward and backward and left and right movements of the vehicle, while the universal wheels are used to increase the flexibility of the vehicle, so that this cross-row mobile chassis structure has flexible movement and good suspension ability, which is suitable for strawberry greenhouse spraying operations and most orchard road scenarios.

[0048] like Figure 3 and Figure 4The diagram shows the unfolded structure of the telescopic spray boom (65) and the scissor-type telescopic linkage structure of the present invention. The telescopic spray boom (65) adopts a scissor-type telescopic structure, including a beam arm (652), a connecting rod node (651), and a driving device electric push rod (66). Through the fixed end node (654) of the beam, the electric push rod (66) drives the movable end node (653) of the beam to move, and the beam arm swings and rotates accordingly. The scissor structure is composed of any even number of identical beam arms (652), and each beam arm (652) is connected in parallel by a hinge at the connecting rod node (651). The scissor-type telescopic linkage can be driven by the swinging motion of any beam or by moving the end of a beam that can slide within the supporting structure. The core advantage of the telescopic spray boom (65) is its range of motion. It is stable and compact in structure, and is a very efficient mechanical mechanism, so it is easy to expand; the lower end of the telescopic spray bar (65) is fixed with a nozzle (63) by a nut, and the nozzle (63) is connected to the water pump (62) through a PVC transparent water pipe (67); the water pump (62) is connected to the water tank (61) through a PVC transparent hose (67) and electrically connected to the central processing module (5) to realize the water pressure of the water pump (62) and thus realize the flow rate of the nozzle (63); the electric push rod (66) is electrically connected to the central processing module (5) through the drive module. According to the actual situation of the operation scenario, the telescopic spray bar (65) is driven to extend and retract through the distance feedback of the ultrasonic sensors (21) installed at both ends of the telescopic spray bar (65), thereby realizing the variable spray width spray.

[0049] like Figure 5 The diagram shown illustrates ultrasonic ranging calculation. and The images show the ultrasonic ranging results before and after measurement. The distance between the drive wheels of the mobile chassis. The vehicle length is assumed to be the total vehicle length; the distance between the front and rear ultrasonic sensors on the sides is assumed to be equal to the total vehicle length. Assume the ultrasonic sensor measures distance at a frequency of 10 Hz. Calculate the angle between the vehicle and the ridge based on the ultrasonic ranging results. With distance The following relationship exists:

[0050] (4);

[0051] The pose of the trolley was calculated using ultrasonic ranging, and the angle between the vehicle and the ridge was obtained. With distance .

[0052] The cross-ridge mobile chassis (1) uses PID control to control its motion trajectory. Steering and speed control are achieved by controlling the rotational speed of the two drive wheel sets (11) of the cross-ridge mobile chassis, which further controls the motion trajectory of the cross-ridge mobile chassis. The cross-ridge mobile chassis has strong passability and can turn on the spot, and can operate in environments with relatively tight space.

[0053] like Figure 6 The diagram shown illustrates the calculation of the pure tracking algorithm. For a path point on the path, This indicates the center point. Click The distance between points, i.e., the forward-looking distance. The turning radius is R, and the robot's instantaneous linear velocity is... , The linear velocity of the left wheel, The linear velocity of the right wheel is [value], and its instantaneous angular velocity is [value]. . This indicates the current robot pose and target path point. The included angle between them. Based on the principle of pure tracking algorithms: (5);

[0054] The forward look-ahead distance is constrained by using maximum and minimum forward look-ahead distances. A larger forward look-ahead distance means smoother trajectory tracking, while a smaller forward look-ahead distance makes tracking more accurate, but it also introduces oscillations. To better determine the forward look-ahead distance, adaptive parameters are introduced. The forward look-ahead distance is calculated by adjusting the weights of turning radius, path error, lateral deviation, desired vehicle speed, and robot mass to achieve the best control effect.

[0055] like Figure 7 The flowchart shown is for the target recognition process of the RGBD camera. First, the image data of the strawberry greenhouse ridges is acquired through the image acquisition module (22), including RGB images and depth images. Then, the acquired RGBD images are preprocessed to eliminate distortion and convert the data format. Then, the YOLOv4 algorithm is used to detect the target in the RGB images and identify the strawberry plant target in the image. Then, the strawberry plant target is extracted and processed in the depth image using the depth image and the target detection results. Then, the Sobel edge detection algorithm is used to detect the edge of the strawberry plant in the depth image to obtain the edge information of the strawberry plant target. Then, the contour information of the strawberry target is obtained through the contour extraction method. Then, by comparing the contour area and shape, it is calculated whether the detected contour is complete. If it is complete, the next step of calculation is performed. Otherwise, the step of acquiring RGBD image information is returned. Then, the width and height of the strawberry plant are calculated based on the acquired strawberry plant target contour information. and Indicates the strawberry in the outline The maximum and minimum coordinates in the axial direction, if and Indicates the strawberry in the outline The maximum and minimum coordinates along the axis, W and H represent the width and height of the strawberry outline. The width and height of the strawberry outline are calculated using the following formula: (6);

[0056] Furthermore, the width and height in the image coordinate system can be transformed to the world coordinate system using camera intrinsic and extrinsic parameters, as shown in the following formula: (7);

[0057] Where depth represents the depth value of the strawberry in the depth image, and fx and fy represent the focal lengths of the camera on the x and y axes, respectively, obtained from the camera intrinsic parameter matrix.

[0058] like Figure 8 The diagram shown is a control flowchart for a cross-row strawberry variable spray width spraying robot. First, the robot's current pose information is determined using GNSS positioning and ultrasonic ranging. The system is updated to determine whether the destination has been reached or if the path is on a ridge. Further tracking is performed using a pure tracking algorithm based on the planned path, according to the constraints: A motion controller is constructed using a PID controller, with the distance difference as the input. The forward sight distance can also be... As input, to ensure the continuity of speed, the PID output needs to be limited and then smoothed. The linear velocity is then calculated using the algorithm described above. and angular velocity Then, the rotational speeds of the left and right wheels are calculated and sent to the drive wheel motors. The controller will then control the robot to continuously move towards the target, while simultaneously feeding back the robot's current speed through the drive wheel motors. To update the pure tracking algorithm and adjust the water pump flow rate. Perform calculations based on the current speed. The spray volume of the nozzle is changed by altering the water pump flow rate, and ultrasonic ranging is used to determine whether the robot is currently on the ridge, thereby controlling the spraying operation.

[0059] The PID algorithm controls the controlled variable through the error signal, and the controller itself is the sum of the proportional, integral, and derivative components.

Claims

1. A control method of a cross-row strawberry intelligent variable variable-spray-width spraying robot structure, characterized by, The structure comprises a cross-ridge moving chassis (1), an ultrasonic sensor (21), a battery (3), an image acquisition module (22), a central processing module (5), a telescopic spraying system (6), a GNSS navigation module (23), and a support platform (14); The telescopic spraying system (6) comprises an electric push rod (66), a water tank (61), a water pump (62), a working support (64), a telescopic spraying rod (65), a nozzle (63), and a PVC transparent hose (67); The cross-ridge moving chassis (1) is composed of a driving wheel group (11), a universal wheel group (12), a chassis support (13), and a support platform (14), the support platform (14) is arranged on the chassis support (13), the left front and right front driving wheel groups (11) are movably connected to one end of the chassis support (13), and the left rear and right rear universal wheel groups (12) are movably connected to the other end of the chassis support (13); the ultrasonic sensor (21), the image acquisition module (22), the GNSS navigation module (23), the driving wheel group (11), the electric push rod (66), and the water pump (62) are electrically connected to the central processing module (5), the collected data is processed, and computing power is provided for motor control and related algorithms; the telescopic spraying system (6) is arranged on the support platform (14); the telescopic spraying system (6) is realized through the telescopic function of the telescopic spraying rod (65), the telescopic spraying rod (65) is controlled to be telescopic by the electric push rod (66), and the lower end of the telescopic spraying rod (65) is provided with the nozzle (63); the nozzle (63) is connected with the water pump (62) and the water tank (61) through the PVC transparent hose (67), the water pump (62) adjusts the flow of the water pump (62) and the spraying amount of the nozzle (63) in real time according to the speed of the robot, and the working support (64) and the chassis support (13) are connected through a metal corner piece; The control method comprises: The longitude, latitude, and height position information and the robot attitude information of the spraying robot are obtained by using the GNSS navigation module (23), the path planned according to the actual situation of the orchard is tracked by using a pure tracking algorithm, the strawberry plants are identified by using an RGBD camera, and variable spraying is performed in combination with a robot motion model; The longitude, latitude, and height position information and the robot attitude information of the spraying robot are obtained by using the GNSS navigation module (23), and the path planned according to the actual situation of the orchard is tracked by using a pure tracking algorithm, and the steps are as follows: Step 1: selecting a trajectory equation of a tracking target or giving a target point sequence; Step 2: calculating the lateral deviation and the heading angle error of the vehicle to the target point based on the current state of the robot; Step 3: calculating the forward distance according to the current lateral deviation and the heading angle error; Step 4: calculating the steering angle and the speed command of the vehicle according to the forward distance and the motion state of the vehicle; Step 5: converting the steering angle and the speed command into the speed commands of the left and right wheels to realize control; The strawberry plants are identified by using an RGBD camera, and variable spraying is performed in combination with a robot motion model, and the method is as follows: Step 6: Obtain RGBD images, use RGBD camera to collect image data on the strawberry ridge, including RGB images and depth images, and perform image preprocessing; Step 7: Target detection, use YOLOv4 algorithm to detect the target in the RGB image, identify the strawberry target in the image, and get its bounding box, class label and confidence score; Step 8: Depth image processing, use depth image and target detection result to extract and process strawberry target in depth image; Step 9: Edge detection, use Sobel edge detection algorithm to detect the edge of the strawberry target in the depth image, and get the edge information of the strawberry target; Step 10: Extract the contour according to the edge information; Step 11: Calculate the width w and height h of the contour based on the target detection result and the contour information of the depth image; Step 12, the speed of the robot advancing according to the detection of the target , the spray amount of each nozzle (63) is calculated , if the greenhouse width is , the length of the ridge is , the distance between the ridges is , the number of nozzles on the telescopic spray bar (65) is , the width of the strawberry plant is w, and the height of the strawberry plant is h Thus, the following is calculated: ; Wherein, k is a constant in the spray model, representing the dispersion characteristics of strawberry plants and the performance of the nozzle; At the same time, considering that there is a distance between the image acquisition module (22) and the nozzle (63), it is necessary to control the telescopic spraying system (6) to spray the processed spraying control information with a delay, and the delay time t can be obtained: ; Wherein, the distance between the image acquisition module (22) and the nozzle (63) in the forward direction of the robot is x; Step 13, according to the calculated nozzle (63) spray amount , the water pump (62) flow control, and then control the robot spray amount, according to the characteristics of pure tracking algorithm, when turning, need to stop spraying, so need to set a stop spraying threshold When the robot heading angle deviates from the straight line direction more than , stop spraying.

2. The method of claim 1, wherein, The support platform (14) is made of acrylic material and has corresponding mounting holes according to the design requirements, so that the image acquisition module (22), the water pump (62), the water tank (61) and the central processing module (5) are fixed tightly on the support platform (14); The support platform (14) is made of aluminum profile and aluminum plate connected by metal foot pieces, which provides support and bearing for the whole system while reducing the weight of the platform.

3. The method of claim 1, wherein, The cross-ridge mobile chassis (1) is used for steering, posture and position adjustment of the spraying robot, and provides a carrying platform for the working system; The cross-ridge mobile chassis (1) is driven by the drive wheel group (11) and the universal wheel group (12), and the environment is perceived by the ultrasonic sensor (21), the image acquisition module (22) and the GNSS navigation module (23); The differential PID control of the drive wheel group (11) is carried out by the central control module (5), and the forward speed and steering are changed.

4. The method of claim 1, wherein, The water tank (61) is fixed on the support platform (14), and the water pump (62) is provided with two water pumps, each of which controls the flow of a group of nozzles (63) connected thereto; The water tank (61) is connected with the water pump (62) and the nozzle (63) through the PVC transparent hose (67); The nozzle (63) is fixed to the lower end of the telescopic spray rod (65) by a pipe clamp; The nozzle (63) is arranged equidistantly in the horizontal direction.

5. The method of claim 1, wherein, The battery (3) is a lithium battery, which is fixed in the support structure of the cross-ridge mobile chassis (1), and provides power for the water pump (62), the electric push rod (66), the drive wheel group (11), the central control module (5), the ultrasonic sensor (21), the image acquisition module (22) and the GNSS navigation module (23).

6. The method of claim 1, wherein, The telescopic spray rod (65) adopts a scissor type telescopic structure, the telescopic spray rod (65) adopts a structure combining double layers and single layers in consideration of strength and weight factors; the telescopic spray rod is fixed with ultrasonic sensors (21) at both ends; the telescopic spray rod (65) is connected with an electric push rod (66), a central processing module (5) sends out instructions, controls the electric push rod (66) to perform a push-pull action according to the feedback of the ultrasonic sensors (21) to drive the telescopic spray rod (65) to expand or contract; the nozzle (63) is fixed at the lower end of the telescopic spray rod (65), and the spraying range of the robot is changed according to the expansion or contraction of the telescopic spray rod (65).

7. The method of claim 1, wherein, The central processing module (5) is fixed on the support platform (14); the central processing module (5) is an STM32F103C8, and is electrically connected with the driving wheel set (11), the water pump (62) and the electric push rod (66) through a driving module; the image acquisition module (22) performs wireless image transmission through the WIFI function module of the central processing module (5).

Images