A control method and system for the water spraying position of a water spraying robot

Abstract

The present invention relates to a control method and system for the water spraying position of a water spraying robot, comprising: obtaining the position and target water spraying position of the water spraying robot, establishing a three-dimensional space coordinate system with the position of the water spraying robot's nozzle as the origin, and determining the coordinates of the target water spraying position in the three-dimensional space coordinate system; starting the water spraying robot to spray water at the target position, and measuring the spray angle and spray pressure of the water spraying robot's nozzle; establishing a water spraying position control model, the goal of which is to calculate the required spray angle and spray pressure according to the coordinates of the target water spraying position; determining the position of the water spraying robot, inputting the target water spraying position relative to the coordinates of the water spraying robot into the water spraying position control model, obtaining the spray angle and spray pressure of the water spraying robot's nozzle, starting the water spraying robot with the spray angle and spray pressure, and realizing the water spraying of the target water spraying position by the water spraying robot. The present invention can automatically adjust the spray angle and spray pressure according to the target water spraying position.

Description

Technical Field

[0001] The present invention relates to the technical field of water spraying robots, and in particular to a method and system for controlling the water spraying position of a water spraying robot. Background Art

[0002] In the construction industry, water spray testing is an important step to ensure the waterproof performance of building facades, windows and other structural components. Traditional water spray testing usually relies on manual operation or fixed sprinkler systems, which have many limitations. For example, manual water spraying is not only inefficient, but also difficult to ensure the uniformity and consistency of water spraying; and although the fixed sprinkler system can provide a relatively stable water spraying effect, it has poor flexibility and cannot be adjusted for building structures of different shapes and heights.

[0003] With the advancement of technology, automated equipment such as sprinkler robots have been gradually introduced into the construction industry to improve the accuracy and efficiency of sprinkler testing. Sprinkler robots can move automatically according to a preset path and can perform sprinkler tests on building structures at different locations. However, existing sprinkler robots still face some challenges when controlling the sprinkler position, such as:

[0004] The watering plan cannot be automatically generated: it is necessary to manually perform the watering operation within the approximate range according to the watering task, and then adjust the watering parameters to achieve the target watering position;

[0005] Insufficient precision: Due to the lack of effective spatial positioning and angle adjustment mechanisms, the watering position of existing watering robots is often not precise enough, which may result in too much or too little watering in some areas;

[0006] Furthermore, the existing intelligent water spraying robots only adjust the water spraying position according to the feedback from the image acquisition when implementing position adjustment, but are unable to automatically determine the water spraying parameters according to the water spraying position. Summary of the invention

[0007] To this end, the technical problem to be solved by the present invention is to overcome the problem in the prior art that the water spraying robot cannot automatically generate a water spraying plan according to the water spraying task, and the water spraying accuracy at the target water spraying position is insufficient. A control method and system for the water spraying position of a water spraying robot are provided. The target water spraying position is accurately located by establishing a three-dimensional spatial coordinate system, and the necessary spray angle and spray pressure are calculated using a water spraying position control model. The spray angle and spray pressure of the nozzle can be automatically adjusted according to the target water spraying position to realize intelligent automatic water spraying, thereby improving the controllability and accuracy of the water spraying process.

[0008] In order to solve the above technical problems, the present invention provides a method for controlling the watering position of a watering robot, comprising:

[0009] Obtain the position of the water spraying robot and the target water spraying position, establish a three-dimensional space coordinate system with the position of the water spraying robot's nozzle as the origin, and determine the coordinates of the target water spraying position in the three-dimensional space coordinate system;

[0010] Start the water spraying robot to spray water at the target location, and measure the spraying angle and spraying pressure of the spraying robot's nozzle;

[0011] Establish a water spray position control model, the goal is to calculate the required spray angle and spray pressure according to the coordinates of the target water spray position;

[0012] Determine the position of the water spraying robot, input the coordinates of the target water spraying position relative to the water spraying robot into the water spraying position control model, obtain the spray angle and spray pressure of the water spraying robot's nozzle, start the water spraying robot with the spray angle and spray pressure, and realize water spraying by the water spraying robot on the target water spraying position.

[0013] In one embodiment of the present invention, a watering position control model is established, including:

[0014] Obtain historical data of the water spraying robot under different conditions;

[0015] The collected historical data are processed to extract features for model building as sample data sets, wherein the features include: the Euclidean distance d between the current position of the water spraying robot and the target position and the pitch angle α and yaw angle β of the target water spraying position relative to the nozzle of the water spraying robot;

[0016] Based on machine learning algorithms, the relationship between the spray angle and spray pressure and the watering position is predicted, and a prediction model is established;

[0017] The Euclidean distance d between the current position of the water spraying robot and the target position and the pitch angle α and yaw angle β of the target water spraying position relative to the water spraying robot's nozzle are used as input parameters, and the spray angle and spray pressure of the water spraying robot's nozzle are used as output parameters to train the prediction model and obtain the water spraying position control model.

[0018] In one embodiment of the present invention, the different conditions include: different position conditions, that is, the spray range of the spray robot is constructed with the position of the spray head of the spray robot as the origin and the maximum spray pressure of the spray head of the spray robot as the radius, and any position within the spray range is selected as the spray target position.

[0019] In one embodiment of the present invention, the different conditions include: different environmental conditions for simulating the natural environment that may affect the change of the watering position during the actual watering operation, including: the influence of wind speed, temperature, and precipitation.

[0020] In one embodiment of the present invention, in the process of establishing the water spraying position control model, when there are multiple corresponding relationships between spraying angles and spraying pressures for the same target water spraying position, different spraying parameters are selected according to the actual environmental conditions.

[0021] In one embodiment of the present invention, when there is no obstruction between the water spraying robot and the target water spraying position:

[0022] Taking the position of the water spraying robot as the origin, determining the coordinates of the target water spraying position, and using the coordinates to calculate the pitch angle α;

[0023] The spray parameter control model is established using historical data, with the minimum pitch angle as the optimization target, the coordinates of the target watering position as input parameters, and the spray angle and spray pressure parameters to achieve this position as output parameters to train the model.

[0024] In one embodiment of the present invention, when there is an obstruction between the water spraying robot and the target water spraying position:

[0025] Taking the position of the water spraying robot as the origin, determining the coordinates of the target water spraying position;

[0026] According to the shape of the obstruction, first determine a pitch angle α of the nozzle that can pass over the obstruction, take the coordinates of the target watering position as input parameters, and use the spray angle and spray pressure parameters to achieve this position as output parameters to train the model.

[0027] In one embodiment of the present invention, the method further comprises: feedback regulation, comprising:

[0028] Obtain the actual watering position, calculate the deviation by comparing the actual watering position after spraying with the preset target watering position, and generate a deviation feedback signal;

[0029] Design an adaptive controller based on the feedback signal to decide how to adjust the spray angle and pressure of the nozzle;

[0030] The actual watering position, the adaptive controller, the spray angle and the pressure of the sprinkler are associated to form a closed-loop control system to adjust the actual watering position.

[0031] In order to solve the above technical problems, the present invention also provides a control system for the water spraying position of a water spraying robot, comprising:

[0032] A position acquisition module, used to acquire the current position and target water spraying position of the water spraying robot;

[0033] A coordinate system establishment module, which establishes a three-dimensional space coordinate system with the location of the sprinkler head of the sprinkler robot as the origin, and determines the coordinates of the target sprinkler position in the coordinate system;

[0034] A parameter measurement module is used to start the water spraying robot to spray water at the target position and measure the spraying angle and spraying pressure of the spraying head of the water spraying robot;

[0035] The control model module is used to calculate the required spray angle and spray pressure according to the coordinates of the target spray position and establish a spray position control model;

[0036] A position confirmation module, used to determine the current position of the water spraying robot and input the coordinates of the target water spraying position relative to the water spraying robot into the control model module;

[0037] The execution control module starts the water spraying robot according to the spraying angle and spraying pressure calculated by the control model module, so that the spray head performs the water spraying operation according to the calculated angle and pressure.

[0038] In one embodiment of the present invention, it further includes: a feedback adjustment module for monitoring the deviation between the actual water spraying position and the target position in real time, and dynamically adjusting the spray angle and spray pressure of the spray head according to the deviation.

[0039] The above technical solution of the present invention has the following advantages compared with the prior art:

[0040] The control method and system for the water sprinkling position of the sprinkling robot described in the present invention accurately locates the target water sprinkling position by establishing a three-dimensional spatial coordinate system, and uses a water sprinkling position control model to calculate the necessary spray angle and spray pressure. It can automatically adjust the spray angle and spray pressure of the sprinkler according to the target water sprinkling position, thereby realizing intelligent automatic water sprinkling without manual intervention, greatly improving work efficiency. In particular, in the water sprinkling test of large-scale construction projects, automated operation can significantly shorten the test cycle and reduce labor costs.

[0041] Specifically, by establishing a three-dimensional spatial coordinate system with the location of the sprinkler robot's nozzle as the origin, the specific coordinates of each target sprinkler position in space can be accurately determined. This high-precision positioning method ensures the accuracy of the sprinkler operation and reduces the problem of uneven sprinkler caused by position error.

[0042] Moreover, based on the water spraying position control model, the system can calculate the optimal spraying angle and spraying pressure required for each target position, which not only improves the accuracy of water spraying, but also ensures that building surfaces of different heights and angles can be fully and evenly sprayed. The spraying angle and spraying pressure of the sprinkler can be automatically adjusted according to the specific shape and size of the building structure. It is suitable for various types of building exterior walls, windows and other structural components, and accurate water spraying tests can be carried out on both straight and curved building surfaces. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below according to specific embodiments of the present invention in conjunction with the accompanying drawings, wherein:

[0044] Figure 1 is a flow chart of the steps of the method for controlling the water spraying position of the water spraying robot of the present invention;

[0045] Figure 2 It is the water spraying trajectory map generated when there is no obstruction between the water spraying robot and the target water spraying position;

[0046] Figure 3 It is the water spraying trajectory map generated when there is an occlusion between the water spraying robot and the target water spraying position;

[0047] Figure 4 It is a structural schematic diagram of a control system for the water spraying position of the water spraying robot of the present invention. DETAILED DESCRIPTION

[0048] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention. Embodiment 1

[0049] Reference Figure 1 As shown, the present invention provides a method for controlling the watering position of a water spraying robot, comprising:

[0050] S1. Obtain the position of the water spraying robot and the target water spraying position, establish a three-dimensional space coordinate system with the position of the water spraying robot's nozzle as the origin, and determine the coordinates of the target water spraying position in the three-dimensional space coordinate system.

[0051] Specifically, by using the sprinkler robot's nozzle as the origin of the three-dimensional coordinate system, it can be ensured that all measurements and calculations are based on a fixed and clear reference point. The three-dimensional coordinate system can fully describe the X, Y, and Z coordinates of the target sprinkler position, allowing the sprinkler robot to accurately find each target position in a complex spatial environment.

[0052] The three-dimensional coordinate system provides a unified mathematical framework, which makes it easier to calculate the watering position control model. No matter how the target position changes, the system can convert it into relative coordinates relative to the sprinkler head through simple geometric transformation, thus simplifying the design and implementation of the control algorithm.

[0053] It should be noted that in actual applications, the position of the water spraying robot may change (for example, moving to a new test area). After each movement, the target water spraying position is repositioned and the coordinates are updated in real time so that the system can quickly adapt to the new position and ensure the accuracy of each water spraying operation.

[0054] Specifically, in actual operation, the position of the sprinkler robot and the target sprinkler position can be obtained through a combination of one or more existing technologies such as global positioning system, laser ranging, three-dimensional scanning and building information modeling, which will not be elaborated here.

[0055] S2. Start the water spraying robot to spray water toward the target position, and measure the spraying angle and spraying pressure of the spraying robot's nozzle.

[0056] Start the water spraying robot and measure the spraying angle to ensure that the spraying robot's nozzle can accurately point to each target position. By adjusting the spraying pressure, the amount of water sprayed and the location of the spraying point can be controlled to ensure that each test point is properly sprayed. By adjusting the spraying angle and spraying pressure of the nozzle, the spraying range of the water spraying robot can be determined, and the water spraying experiment can be carried out within this range. By measuring and adjusting the spraying angle and pressure in real time as historical data for model learning, the spraying position can be controlled through the model to achieve automatic operation without manual intervention. This not only improves work efficiency, but also reduces the possibility of human error.

[0057] S3, establishing a water spraying position control model, wherein the goal of the water spraying position control model is to calculate the required spraying angle and spraying pressure according to the coordinates of the target water spraying position;

[0058] Specifically, by establishing a water spraying position control model, the required spraying angle and spraying pressure can be accurately calculated according to the coordinates of the target water spraying position, ensuring that the water spraying robot can complete the water spraying task efficiently and accurately.

[0059] Establish a watering position control model, including:

[0060] S31. Obtain historical data of the water spraying robot under different conditions as the basis for model training. Collect the operation data of the water spraying robot from actual tests, including:

[0061] The coordinates of the nozzle position of the water spraying robot. Since the position of the nozzle of the water spraying robot is taken as the origin, the coordinates of the nozzle position are (0, 0, 0);

[0062] The three-dimensional coordinates of the target watering position (x t ,y t , z t );

[0063] The spray angle of the nozzle, namely: pitch angle α and yaw angle β;

[0064] Injection pressure P;

[0065] The data of each watering operation is recorded in real time using sensors and control systems and stored in a database as historical data.

[0066] S32. Process the collected historical data and extract features for model building as sample data sets. The features include:

[0067] Calculate the Euclidean distance d between the current position of the water spraying robot and the target position:

[0068] ;

[0069] This distance expresses the spatial distance from the nozzle to the target position;

[0070] Calculate the pitch angle α and yaw angle β:

[0071] ;

[0072] The pitch angle α represents the angle of the nozzle in the vertical direction;

[0073] ;

[0074] The yaw angle β represents the angle of the nozzle in the horizontal direction.

[0075] The features (d, α, β) calculated above are combined with the corresponding injection angle (θ, φ) and injection pressure P into a sample data set. Each sample contains the following fields:

[0076] Input features: Euclidean distance d, pitch angle α, yaw angle β;

[0077] Output tags: injection angle θ, φ and injection pressure P.

[0078] S33. Based on the machine learning algorithm, the relationship between the spray angle, spray pressure and the watering position is predicted, and a prediction model is established.

[0079] S34. Use the Euclidean distance d between the current position of the water spraying robot and the target position and the pitch angle α and yaw angle β of the target water spraying position relative to the water spraying robot nozzle as input parameters, and use the spray angle and spray pressure of the water spraying robot nozzle as output parameters to train the prediction model to obtain the water spraying position control model.

[0080] Specifically, in this embodiment, a neural network algorithm is used for modeling, and the input features are normalized or standardized to ensure that the numerical ranges of different features are consistent to avoid excessive influence of certain features on the model. The sample data set is divided into a training set and a test set, and the training set is used to train the selected machine learning algorithm. The hyperparameters of the model are adjusted to obtain optimal performance, and the test set is used to evaluate the performance of the model.

[0081] S4. Determine the position of the water spraying robot, input the coordinates of the target water spraying position relative to the water spraying robot into the water spraying position control model, obtain the spray angle and spray pressure of the water spraying robot's nozzle, start the water spraying robot with the spray angle and spray pressure, and realize water spraying by the water spraying robot on the target water spraying position.

[0082] Specifically, the trained model is deployed to the control system of the water spraying robot, so that it can predict the spray angle θ, φ and the spray pressure P in real time according to the input d, α, β in actual application. Before each water spraying operation, the determined values ​​of d, α, β are obtained by measurement. The system will calculate the required spray angle and spray pressure according to the current d, α, β values, and pass these parameters to the sprinkler control system to ensure that the sprinkler can accurately spray water at the target position; by establishing a three-dimensional spatial coordinate system to accurately locate the target water spraying position, and using the water spraying position control model to calculate the necessary spray angle and spray pressure, the spray angle and spray pressure of the sprinkler can be automatically adjusted according to the target water spraying position, realizing intelligent automatic water spraying without human intervention, which greatly improves work efficiency. Especially in the water spraying test of large-scale construction projects, automated operation can significantly shorten the test cycle and reduce labor costs.

[0083] In order to more comprehensively simulate various situations in actual water sprinkling operations, this embodiment also considers two main different conditions when establishing the water sprinkling position control model: different position conditions and different environmental conditions, and compensates the water sprinkling position control model under these two conditions.

[0084] Under different position conditions, with the position of the sprinkler robot's nozzle as the origin, a spray range is constructed, and any position within the range is selected as the sprinkler target position;

[0085] Specifically, let the maximum spray pressure of the sprinkler robot's nozzle be Pmax. According to the maximum spray pressure Pmax, determine the maximum distance Rmax at which the nozzle can effectively spray. This distance can be obtained through experiments or data provided by the manufacturer. Through the maximum distance Rmax, with the nozzle position (0,0,0) as the center of the sphere and Rmax as the radius, construct a spherical spray range, which is the effective spray range of the sprinkler robot. When constructing the model, it is limited that the target sprinkler position cannot exceed this range, and the boundary conditions are determined:

[0086] .

[0087] Under different environmental conditions, simulate the natural environment that may affect the change of the watering position during the actual watering operation, including wind speed, temperature, precipitation and other factors:

[0088] Specifically, a wind speed sensor is used to monitor the wind speed in the environment in real time. The wind speed will change the injection path, resulting in changes in the injection angle and injection pressure. The injection parameters can be adjusted by introducing a wind speed correction term. For example, when the wind speed is high, the injection pressure can be appropriately increased to overcome the influence of wind force, or the injection angle can be adjusted to compensate for wind deviation.

[0089] Specifically, a temperature sensor is used to monitor the ambient temperature. The temperature may affect the evaporation rate and spraying effect of water. The spraying pressure can be adjusted by introducing a temperature correction coefficient. For example, in a high temperature environment, the spraying pressure can be appropriately increased to ensure sufficient watering volume.

[0090] Specifically, rain sensors are used to monitor precipitation. Precipitation will affect the wetness of the building surface, which in turn affects the test results. A precipitation correction term can be introduced into the model to ensure that consistent watering effects can be obtained under different precipitation conditions.

[0091] On the basis of the original features, environmental parameters are added as additional input features and the model is retrained. In this way, the model can learn the relationship between the spray parameters and the target position under different environmental conditions. In actual applications, the system can dynamically adjust the spray angle and spray pressure according to the real-time monitored environmental parameters to ensure that each watering operation can achieve the best effect.

[0092] Specifically, in the process of establishing the water spraying position control model, when determining a target water spraying position, there will be a variety of corresponding relationships between spray angles and spray pressures for the same target water spraying position. In order to solve this problem, different spray parameters are selected according to the actual environmental conditions to ensure that the system can select the most appropriate spray parameters according to the actual situation, thereby achieving precise water spraying operation.

[0093] Specifically, in this embodiment, the watering position control model is optimized and screened in two cases:

[0094] Reference Figure 2 As shown in the figure, when there is no obstruction between the water spraying robot and the target water spraying position:

[0095] Taking the position of the water spraying robot as the origin, determining the coordinates of the target water spraying position, and using the coordinates to calculate the pitch angle α;

[0096] The spray parameter control model is established using historical data, with the minimum pitch angle as the optimization target, the coordinates of the target watering position as input parameters, and the spray angle and spray pressure parameters to achieve this position as output parameters to train the model.

[0097] Specifically, during the model training process, the minimum pitch angle α is introduced as the optimization target, which can be achieved in the following ways:

[0098] Loss function design: Add a penalty term for the pitch angle α to the loss function to encourage the model to choose a smaller pitch angle. For example, a penalty term proportional to the pitch angle can be added to the mean square error (MSE):

[0099]

[0100] in, The injection parameters predicted by the model, is the preset target injection parameter, and λ is a weight parameter used to balance the accuracy of the injection angle and the size of the pitch angle.

[0101] During the optimization process, an upper limit of the pitch angle α is set to ensure that it does not exceed a reasonable value, and the maximum allowable pitch angle is set according to the actual situation.

[0102] By taking the minimum pitch angle as the optimization target and combining historical data to establish a spray parameter control model, it is possible to achieve precise spray angle and spray pressure control when there is no obstruction between the spray robot and the target spray position, making the spray trajectory between the spray robot and the target spray position as short as possible. This not only improves the stability and accuracy of the spray, but also reduces the impact of environmental factors on the spray effect.

[0103] Reference Figure 3 As shown in the figure, when there is an obstruction between the water spraying robot and the target water spraying position:

[0104] Taking the position of the water spraying robot as the origin, determining the coordinates of the target water spraying position;

[0105] According to the shape of the obstruction, first determine a pitch angle α of the nozzle that can pass over the obstruction, take the coordinates of the target watering position as input parameters, and use the spray angle and spray pressure parameters to achieve this position as output parameters to train the model.

[0106] Specifically, when there is an obstruction between the sprinkler robot and the target sprinkler position, the spray path will be affected by the obstruction, resulting in direct spraying failing to reach the target position. This situation is relatively common in practical applications, for example: obstruction by trees in front of a building. Therefore, the spray angle and spray pressure need to be adjusted to ensure that the water can pass over the obstruction and accurately reach the target position.

[0107] Specifically, let the height of the highest point of the obstruction relative to the nozzle be h, and calculate the minimum pitch angle αmin that can pass over the obstruction based on the height h of the obstruction and the distance d of the target position:

[0108] ;

[0109] The injection parameter control model is established using historical data. During the model training process, the minimum pitch angle αmin to cross the obstruction is introduced as a constraint to ensure that the pitch angle selected by the model is greater than or equal to αmin. For example, a penalty term proportional to the pitch angle can be added on the basis of the mean square error (MSE):

[0110] ;

[0111] in, are the injection parameters predicted by the model, is the preset target injection parameter, and λ is a weight parameter used to balance the accuracy of the injection angle and the size of the pitch angle.

[0112] During the optimization process, a lower limit of the pitch angle α is set to ensure that it is not lower than αmin.

[0113] By considering the geometric information of the obstruction, adjusting the spray angle to ensure that the water can pass over the obstruction and accurately reach the target position, and combining historical data to establish a spray parameter control model, precise spray angle and spray pressure control can be achieved when there is an obstruction between the water spraying robot and the target water spraying position.

[0114] Specifically, in order to further improve the method implemented in this embodiment, make the spray position more accurate and facilitate adjustment according to actual conditions, when actually used, it can also be combined with existing technologies to perform real-time feedback adjustment on the spray angle and spray pressure, including:

[0115] Obtain the actual watering position, calculate the deviation by comparing the actual watering position after spraying with the preset target watering position, and generate a deviation feedback signal;

[0116] Among them: the actual water spraying position can be acquired through the sensor, and the two-dimensional or three-dimensional coordinates of the actual water spraying position are converted into the same coordinate system as the target water spraying position to ensure that the two can be directly compared. According to the calculated deviation, a feedback signal is generated. The feedback signal can be a vector, indicating the offset direction and size of the actual water spraying position relative to the target position.

[0117] Design an adaptive controller based on the feedback signal to decide how to adjust the spray angle and pressure of the nozzle;

[0118] Specifically, combined with real-time feedback data, the controller can continuously optimize its parameters to ensure that each adjustment can achieve the best effect; for example, the most commonly used PID controller can be used, and the P, I, and D parameters of the PID controller can be dynamically adjusted through an adaptive algorithm to adapt to different environmental conditions and target positions.

[0119] The actual watering position, the adaptive controller, the spray angle and the pressure of the sprinkler are associated to form a closed-loop control system to adjust the actual watering position.

[0120] The specific adjustment process is: the system obtains the coordinates of the actual water spraying position through the sensor in real time, compares the actual water spraying position with the target water spraying position, calculates the deviation, and generates new spray angle and spray pressure control instructions based on the deviation signal. The nozzle adjusts the spray angle and spray pressure according to the new control instructions to ensure that the next spray can be closer to the target position.

[0121] The system repeats the above process until the deviation between the actual watering position and the target watering position is within the allowable range or the predetermined accuracy requirement is met. Embodiment 2

[0122] On the basis of the above-mentioned embodiment 1, the present invention further discloses a control system for the water spraying position of a water spraying robot, comprising:

[0123] A position acquisition module, used to acquire the current position and target water spraying position of the water spraying robot;

[0124] A coordinate system establishment module, which establishes a three-dimensional space coordinate system with the location of the sprinkler head of the sprinkler robot as the origin, and determines the coordinates of the target sprinkler position in the coordinate system;

[0125] A parameter measurement module is used to start the water spraying robot to spray water at the target position and measure the spraying angle and spraying pressure of the spraying head of the water spraying robot;

[0126] The control model module is used to calculate the required spray angle and spray pressure according to the coordinates of the target spray position and establish a spray position control model;

[0127] A position confirmation module, used to determine the current position of the water spraying robot and input the coordinates of the target water spraying position relative to the water spraying robot into the control model module;

[0128] The execution control module starts the water spraying robot according to the spraying angle and spraying pressure calculated by the control model module, so that the spray head performs the water spraying operation according to the calculated angle and pressure.

[0129] The control method described in the first embodiment can be implemented by the control system of the water spraying position of the water spraying robot disclosed in this embodiment.

[0130] Specifically, in order to achieve feedback regulation, the control system of this embodiment further includes: a feedback adjustment module for real-time monitoring of the deviation between the actual watering position and the target position, and dynamically adjusting the spray angle and spray pressure of the spray head according to the deviation.

[0131] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0132] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0133] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0134] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0135] Obviously, the above embodiments are merely examples for the purpose of clear explanation and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the present invention.

Claims

1. A method for controlling the watering position of a watering robot, characterized in that: include: Obtain the position of the water spraying robot and the target water spraying position, establish a three-dimensional space coordinate system with the position of the water spraying robot's nozzle as the origin, and determine the coordinates of the target water spraying position in the three-dimensional space coordinate system; Start the water spraying robot to spray water at the target location, and measure the spraying angle and spraying pressure of the spraying robot's nozzle; Establish a watering position control model, the goal is to calculate the required spray angle and spray pressure according to the coordinates of the target watering position, including: obtaining the historical data of the watering robot under different conditions; processing the collected historical data, extracting features for model establishment as a sample data set, the features including: the Euclidean distance d between the current position of the watering robot and the target position and the pitch angle α and yaw angle β of the target watering position relative to the watering robot nozzle; based on the machine learning algorithm, predict the relationship between the spray angle and the spray pressure and the watering position, and establish a prediction model; use the Euclidean distance d between the current position of the watering robot and the target position and the pitch angle α and yaw angle β of the target watering position relative to the watering robot nozzle as input parameters, and use the spray angle and spray pressure of the watering robot nozzle as output parameters to train the prediction model, and obtain a watering position control model; Determine the position of the water spraying robot, input the coordinates of the target water spraying position relative to the water spraying robot into the water spraying position control model, obtain the spray angle and spray pressure of the water spraying robot's nozzle, start the water spraying robot with the spray angle and spray pressure, and realize water spraying by the water spraying robot on the target water spraying position.

2. The method for controlling the water spraying position of the water spraying robot according to claim 1, characterized in that: The different conditions include: different position conditions, that is, the spray range of the spray robot is constructed with the position of the spray head of the spray robot as the origin and the maximum spray pressure of the spray head of the spray robot as the radius, and any position within the spray range is selected as the spray target position.

3. The method for controlling the water spraying position of the water spraying robot according to claim 1, characterized in that: The different conditions include: different environmental conditions, which are used to simulate the natural environment that may affect the change of the watering position during the actual watering operation, including: the influence of wind speed, temperature, and precipitation.

4. The method for controlling the water spraying position of the water spraying robot according to claim 1, characterized in that: In the process of establishing the water spraying position control model, when there are multiple corresponding relationships between spraying angles and spraying pressures at the same target water spraying position, different spraying parameters are selected according to the actual environmental conditions.

5. The method for controlling the water spraying position of the water spraying robot according to claim 4, characterized in that: When there is no obstruction between the water spraying robot and the target water spraying position: Taking the position of the water spraying robot as the origin, determining the coordinates of the target water spraying position, and using the coordinates to calculate the pitch angle α; The spray parameter control model is established using historical data, with the minimum pitch angle as the optimization target, the coordinates of the target watering position as input parameters, and the spray angle and spray pressure parameters to achieve this position as output parameters to train the model.

6. The method for controlling the water spraying position of the water spraying robot according to claim 4, characterized in that: When there is an obstruction between the water spraying robot and the target water spraying position: Taking the position of the water spraying robot as the origin, determining the coordinates of the target water spraying position; According to the shape of the obstruction, first determine a pitch angle α of the nozzle that can pass over the obstruction, take the coordinates of the target watering position as input parameters, and use the spray angle and spray pressure parameters to achieve this position as output parameters to train the model.

7. The method for controlling the water spraying position of the water spraying robot according to claim 1, characterized in that: Also includes: Feedback regulation, including: Obtain the actual watering position, calculate the deviation by comparing the actual watering position after spraying with the preset target watering position, and generate a deviation feedback signal; Design an adaptive controller based on the feedback signal to decide how to adjust the spray angle and pressure of the nozzle; The actual watering position, the adaptive controller, the spray angle and the pressure of the sprinkler are associated to form a closed-loop control system to adjust the actual watering position.

8. A control system for the water spraying position of a water spraying robot, used to execute the control method according to any one of claims 1 to 7, characterized in that: include: A position acquisition module, used to acquire the current position and target water spraying position of the water spraying robot; A coordinate system establishment module, which establishes a three-dimensional space coordinate system with the location of the sprinkler head of the sprinkler robot as the origin, and determines the coordinates of the target sprinkler position in the coordinate system; A parameter measurement module is used to start the water spraying robot to spray water at the target position and measure the spraying angle and spraying pressure of the spraying head of the water spraying robot; The control model module is used to calculate the required spray angle and spray pressure according to the coordinates of the target spray position and establish a spray position control model; A position confirmation module, used to determine the current position of the water spraying robot and input the coordinates of the target water spraying position relative to the water spraying robot into the control model module; The execution control module starts the water spraying robot according to the spraying angle and spraying pressure calculated by the control model module, so that the spray head performs the water spraying operation according to the calculated angle and pressure.

9. The control system for the water spraying position of the water spraying robot according to claim 8, characterized in that: Also includes: The feedback adjustment module is used to monitor the deviation between the actual water spraying position and the target position in real time, and dynamically adjust the spray angle and spray pressure of the nozzle according to the deviation.

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