Intelligent quadruped robot paddy field subsidence condition equivalent test method and system
By using an elastic test pad and a nonlinear stiffness mapping model in the laboratory to simulate the paddy field environment, the problems of uncontrollable and poor reproducibility of the paddy field robot test environment were solved. This enabled efficient and low-cost calculation of subsidence depth and energy consumption, which is consistent with real working conditions.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-01-05
- Publication Date
- 2026-03-27
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
In existing technologies, the environmental parameters of field tests for paddy field robots are uncontrollable and data acquisition errors are large. Indoor soil test media preparation is complex and has poor reproducibility, making it difficult to conduct continuous tests.
A nonlinear stiffness mapping method was adopted to simulate the paddy field environment using a laboratory elastic test pad. A nonlinear stiffness mapping model was established to calculate the robot's sinking depth and energy consumption in the paddy field. The segmented stiffness mapping model was combined to adapt to the geological stratification characteristics of the paddy field.
This method enables efficient and low-cost testing of the sinking depth and energy consumption of paddy field robots. The test results are consistent and reflect real-world working conditions, reducing maintenance costs and improving testing efficiency.
Smart Images
Figure CN121733562A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of robot performance testing and evaluation technology, and in particular to a standardized indoor testing technology for robots in unstructured agricultural environments, especially to an equivalent testing method and system for intelligent quadruped robots in paddy field subsidence conditions based on nonlinear stiffness mapping. Background Technology
[0002] With the rapid development of smart agriculture, there is an urgent need for intelligent robots to enter paddy fields for phenotypic data collection and monitoring throughout the entire growth cycle. Therefore, paddy field operation robots have received widespread attention. When robots enter the soft mud environment of paddy fields, they are prone to irreversible deep subsidence, leading to a sharp increase in walking resistance and excessive energy consumption. Poor mobility can cause the robot to get stuck or even overturn, making it unable to complete its intended monitoring tasks. Currently, to ensure the robot's adaptability in the field, its subsidence depth and mobility in soils with different rheological properties must be rigorously tested. However, the application of field testing is limited due to the uncontrollable environment and difficulty in quantifying subsidence data, while indoor soil trough testing suffers from problems such as complex medium preparation, poor reproducibility, and difficult equipment cleaning. Therefore, using a laboratory elastic testing mat and a nonlinear stiffness mapping calculation method to equivalently calculate the irreversible subsidence depth of the robot under real paddy field conditions is an important technical means to solve the problem of low-cost, high-efficiency testing of paddy field robots. Summary of the Invention
[0003] To address the aforementioned technical problems of uncontrollable field testing environment parameters, large data acquisition errors, and complex preparation, poor reproducibility, and difficulty in continuous testing of indoor soil test media for existing paddy field robots, this invention provides an equivalent testing method and system for paddy field subsidence conditions using an intelligent quadruped robot based on nonlinear stiffness mapping.
[0004] The objective of this invention is achieved through the following technical solution: This invention discloses an equivalent testing method and system for paddy field subsidence conditions using an intelligent quadruped robot, comprising the following steps: Step 1: Determine the rheological properties of the target paddy field soil as the parameters of the Becker soil bearing capacity model for simulating the target paddy field environment, and set the motion parameters of the robot under test as its motion speed when inspecting between rice rows. Step 2: Collect real-time vertical compression data of the foot end of the robot under test on the test pad when it walks at the motion speed set in Step 1 on a laboratory elastic test pad with a known stiffness coefficient, and simultaneously collect the real-time output torque of the joint motor. Step 3: Based on the principle of force balance, establish the equivalent equation between the elastic reaction force of the test pad and the bearing capacity of the target paddy field soil, and generate a nonlinear stiffness mapping model; Step 4: Substitute the real-time vertical compression data collected in Step 2 into the nonlinear stiffness mapping model described in Step 3 to calculate the equivalent subsidence depth of the robot under test in the target paddy field subsidence condition, which is the virtual irreversible subsidence depth. ; Step 5: Calculate the equivalent operating energy consumption of the robot under the target paddy field subsidence condition. This is equal to the sum of the actual electrical energy consumed by the motor of the robot during its walking test distance on the laboratory elastic test pad, the energy consumption compensation item of the virtual elastic test pad, and the work done by the lateral mud discharge resistance calculated according to the virtual irrecoverable subsidence depth described in Step 4.
[0005] Furthermore, in step 3, the construction of the nonlinear stiffness mapping model specifically includes: Establish a mechanical model for the laboratory elasticity test pad: , in To test the reaction force of the pad, The linear stiffness coefficient of the test pad. This represents the real-time vertical compression amount. Establish a Becker bearing pressure model for the target paddy field soil: ,in The target is the bearing capacity per unit area of paddy field soil. It is the cohesive modulus. For friction modulus, The subsidence index, The width of the robot's foot. The depth of the subsidence; based on The equivalent conditions yield the nonlinear stiffness mapping model: , where A is the contact area of the robot's foot.
[0006] Furthermore, the stiffness mapping model in step 3 is a piecewise function, with a preset threshold for the thickness of the floating mud. When the depth of subsidence At that time, the parameters of the Becker soil bearing capacity model for the floating mud layer were used. When the depth of subsidence At that time, the parameters of the Becker soil bearing capacity model of the plow layer were used. To adapt to the geological stratification characteristics of the paddy field, which consists of an upper layer of floating mud and a lower layer of plow layer.
[0007] Furthermore, when the subsidence depth When the nonlinear stiffness mapping model is corrected, it becomes: , in To reach the subsidence depth The critical bearing capacity at that time is: , Furthermore, in step 5, the formula for calculating the equivalent operating energy consumption is: , in, This represents the equivalent energy consumption under real paddy field conditions. The electrical energy consumption of the motor of the robot under test was measured on a laboratory elastic test mat. The energy consumption compensation term for the elastic test pad is equal to the total work done by the target paddy soil during the loading process calculated based on the Becker model minus the elastic potential energy of the laboratory elastic test pad. The virtual lateral mud discharge resistance work is calculated using fluid dynamics formulas based on the virtual irrecoverable subsidence depth, the fluid viscosity coefficient of the paddy field mud, the robot's foot movement speed, and the robot's walking distance. , The average virtual non-recoverable subsidence depth during a single-step mud contact process.
[0008] Furthermore, the average virtual non-recoverable subsidence depth during the single-step mud contact process The value is the real-time subsidence depth obtained in step 4. The arithmetic mean of this foot-to-mud contact process. The distance traveled. The fluid viscosity coefficient of the target paddy field mud. The effective flow resistance width at the robot's foot end. The speed of motion.
[0009] Furthermore, the method also includes the step of generating a passability risk assessment report: If the virtual irrecoverable sinking depth calculated in step 4 is greater than the effective length of the robot's lower leg or causes the chassis to contact the virtual mud surface, then the robot is determined to be at risk of getting stuck in the target paddy field, and a risk alarm is output, generating a passability risk assessment report.
[0010] The equivalent testing system of the intelligent quadruped robot paddy field subsidence equivalent testing method of the present invention includes: The physical testing platform includes an elastic testing mat laid on the ground and motion capture units located around the elastic testing mat. The data acquisition module communicates with the motion capture unit and the control interface of the robot under test, respectively, and is used to collect data on the vertical compression of the robot's foot against the elastic test pad and to obtain the real-time output torque of the joint motor. The computing terminal is equipped with a nonlinear stiffness mapping model, which is used to perform virtual irreversible subsidence depth calculation and equivalent energy consumption calculation. A human-computer interaction interface is used to input target paddy field soil parameters and display the final subsidence depth, equivalent operational energy consumption, and / or risk assessment results.
[0011] Furthermore, the evaluation results displayed on the human-computer interaction interface include a safe zone, a warning zone, a risk zone, and a danger zone, presented in a visual form, and are marked with the virtual irreversible subsidence depth calculated in real time.
[0012] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a computing processing terminal, implements the steps of the equivalent test method as described in any one of claims 1 to 6.
[0013] The beneficial effects of this invention are as follows: 1. This invention achieves standardization and reproducibility of the testing environment: It abandons the traditional mud medium and instead uses a stable elastic testing pad. Through a nonlinear stiffness mapping model algorithm, it eliminates the interference of random variables such as mud moisture content and thixotropy on the test results, ensuring high consistency and comparability of test data from different times and locations, thus meeting the data credibility requirements of third-party testing institutions.
[0014] 2. This invention improves testing efficiency and reduces maintenance costs: It eliminates the need to dig trenches or prepare mud in the laboratory, avoiding tedious soil turning, leveling, and cleaning work. The testing process is clean and pollution-free, and can quickly simulate paddy field environments from different regions, such as southern red mud and northern black soil, by adjusting software parameters, significantly shortening the testing cycle.
[0015] 3. This invention solves the problem of physical distortion in simulating plastic settlement using elastic media: This invention goes beyond simple physical simulation; it rapidly derives the virtual irreversible settlement depth and equivalent operational energy consumption through a nonlinear stiffness mapping model algorithm. Furthermore, considering the stratified characteristics of real paddy field environments, a piecewise stiffness mapping model and an elastic test pad deformation energy consumption compensation term are introduced. This effectively addresses the fundamental differences in mechanical properties between laboratory elastic materials and real paddy field soil, making the calculated settlement depth and operational energy consumption closer to real field conditions, filling the technological gap in low-cost indoor equivalent testing. Attached Figure Description
[0016] Figure 1 This is a flowchart illustrating the implementation of the present invention; Figure 2 This is a schematic diagram of the equivalent testing system of the present invention.
[0017] Figure 3This is a diagram showing the risk assessment results of paddy field subsidence using an intelligent quadruped robot generated according to the method of this invention. Detailed Implementation
[0018] To make the objectives, technical solutions, and advantages of this invention clearer and easier for those skilled in the art to understand, the invention will be described in detail below with reference to the accompanying drawings and embodiments. However, it should be understood that these descriptions are merely exemplary and not intended to limit the scope of the invention. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.
[0019] Example 1: This example details the basic technical solution of the present invention, mainly targeting an idealized homogeneous paddy field soil environment, such as... Figure 1 As shown, the present invention provides an equivalent testing method for paddy field subsidence conditions using an intelligent quadruped robot based on nonlinear stiffness mapping. The specific implementation process is as follows: S1. Physical test environment setup and parameter initialization First, an elastic testing mat is laid on a flat surface in the laboratory. In this embodiment, the testing mat is made of closed-cell EVA foam material, with dimensions of 10 meters long and 3 meters wide. The average linear stiffness coefficient of this testing mat has been calibrated at the factory. The material rebound hysteresis rate is less than 5%.
[0020] The object being tested is a quadruped rice monitoring robot, with each leg having a disc-shaped end and a diameter of... .
[0021] The parameters include the rheological properties of the target paddy field soil and the standard motion parameters of the robot under test: The rheological properties of the target paddy field soil to be simulated are input into the computer of the testing system. These parameters are obtained through field sampling tests. Three representative sampling points are selected in the target paddy field area, and the bearing capacity per unit area at different settlement depths is measured using a soil bearing capacity meter. The results are then obtained through least squares fitting. , , Parameters. This embodiment simulates the soft mud conditions in paddy fields during the tillering stage of rice in southern China. Bekker soil bearing capacity model parameters: cohesive modulus. Friction modulus Subsidence Index .
[0022] Setting the standard motion parameters for the robot under test: In this example, the quadruped robot is controlled to inspect the rice rows during the tillering stage. The movement speed is used to perform a straight-line walking motion on the aforementioned elastic test pad.
[0023] S2: Measure the real-time compression and driving torque of the robot's feet when it performs walking movements on a laboratory elastic test pad; During the walking process, a global coordinate system O-XYZ is constructed using motion capture units (infrared cameras) arranged around the test pad. The origin O is set at a corner vertex of the elastic test pad, and the Z-axis is defined as perpendicular to the surface of the test pad and upward, while the XY plane is parallel to the stationary surface of the test pad. At least four ground reference reflective points are attached to the four corners and the center of the edge of the effective walking area of the test pad. The system uses the coordinates of these reference points to fit a reference plane describing the undeformed surface of the test pad, thus eliminating ground flatness errors. Foot tracking reflective points are attached to the geometric center or rigid connection of the robot's foot shell. The motion capture unit tracks the three-dimensional coordinates of the marker points in real time at a sampling frequency of 200Hz, and calculates the following using the relative displacement difference method: First, at the instant when the robot lightly touches the surface of the test pad without compression, the vertical height of the foot tracking marker point relative to the reference plane is recorded; second, during the walking and stepping process, the current vertical height of the marker point relative to the reference plane is obtained in real time; finally, the high-precision real-time vertical compression of the test pad by the foot is obtained by calculating the difference between the two vertical heights. For example, in At a certain moment, the compression of the right forefoot on the test pad was measured. .
[0024] The robot's joint motors are synchronously acquired in real time, and the vertical compression data collected by the motion capture unit is synchronized using a unified timestamp. The data is time-domain aligned with the torque data recorded internally by the robot to ensure the vertical compression at every moment. With driving torque (i.e., the real-time output torque data of the robot joint motors) (Accurate correspondence)
[0025] S3: Construct a stiffness mapping model between the linear stiffness of the laboratory elastic test pad and the nonlinear bearing capacity model of real paddy field soil; Based on the principle of force balance, an equivalent equation is established between the elastic reaction force of the test pad and the bearing capacity of the target paddy soil. The equivalent condition is that the elastic reaction force of the test pad is equal to the product of the contact area of the robot foot and the bearing capacity per unit area of the target paddy soil, and a nonlinear stiffness mapping model is generated. Specifically as follows: 1. Calculate the elastic reaction force of the test pad: According to Hooke's Law, calculate the actual supporting force of the test pad on the foot end under the current vertical compression of the robot, as the mechanical model of the laboratory elastic test pad: ;in To test the elastic reaction force of the pad, The linear stiffness coefficient of the test pad, and the real-time vertical compression. ; 2. Establish a Bekker bearing capacity model for the target paddy field soil: ,in The target is the bearing capacity per unit area of paddy field soil. It is the cohesive modulus. For friction modulus, The subsidence index, The width of the robot's foot. The depth of the subsidence; 3. Constructing equivalent equations and generating a nonlinear stiffness mapping model: Generating the same support force in a real paddy field as at the current moment in the laboratory. The corresponding virtual irrecoverable subsidence depth is Based on the principle of force balance, the equivalent condition is: the elastic reaction force of the test pad is equal to the product of the contact area of the robot's foot and the bearing capacity per unit area of the target paddy field soil, that is: Combining the above Bekker pressure model and equivalent condition formula, the equivalent equation is obtained as follows: Thus, the nonlinear stiffness mapping model is obtained. .
[0026] S4: Determine the virtual irreversible subsidence depth of the tested robot in the target paddy field soil. The real-time vertical compression amount collected in step S2 Substituting into the nonlinear stiffness mapping model generated in step S3, the equivalent subsidence depth of the robot under the target paddy field condition is calculated as a virtual, irrecoverable subsidence depth: .
[0027] By physically compressing the data by only 15mm, the calculation showed that the subsidence depth corresponding to this force in a real paddy field could reach 80mm, meaning that the foot of the robot being tested would sink into the mud 80mm deep in a real paddy field.
[0028] If the calculated virtual irreversible subsidence depth exceeds the effective length of the robot's lower leg or causes the robot's chassis to contact the virtual mud surface, the robot is deemed to be at risk of getting stuck in the target paddy field, and a risk alarm is output; a passability risk assessment report is generated; details are as follows: The system monitors and calculates the virtual, irreversible subsidence depth in real time. ,like (The effective length of the robot's lower leg, for example, 250mm), or If the ground clearance of the vehicle exceeds the limit, causing the chassis to bottom out, the system will immediately generate a high-risk vehicle stuck alarm on the display interface and mark that the gait parameters are not suitable for the current paddy field environment.
[0029] S5: Equivalent energy consumption of robot operation under real paddy field conditions: Based on the virtual irreversible subsidence depth, calculate the energy consumption compensation term for the deformation of the virtual elastic test pad caused by the robot walking in the target paddy field soil. With virtual lateral sludge discharge resistance work The two values mentioned above are superimposed on the measured energy consumption collected on the laboratory elastic test mat to obtain the equivalent total energy consumption of the tested robot in a real paddy field environment. : , in: 1. The measured electrical energy consumption of the motor of the robot under test on the laboratory elastic test mat is the actual electrical energy consumed by the motor within the walking test distance.
[0030] 2. The deformation energy consumption compensation term for the virtual elastic test pad is equal to the total work done by the target paddy soil during the loading process calculated based on the Bekker bearing model minus the elastic potential energy of the laboratory elastic test pad. , This represents the maximum virtual, irreversible settlement depth during this single-step mud contact process. The vertical bearing capacity function of the target paddy field soil is constructed based on the Bekker model, and its expression is as follows: This represents a subsidence depth of... The instantaneous reaction force of the soil on the feet, The linear stiffness coefficient of the test pad. This is the maximum vertical compression measured during this single-step mud contact process, corresponding to... Laboratory measured values at any given time.
[0031] 3. The virtual lateral mud discharge resistance work is calculated using fluid dynamics formulas based on the virtual irrecoverable subsidence depth, the fluid viscosity coefficient of the paddy field mud, the robot's foot speed, and the robot's walking distance. The fluid viscosity coefficient of the target paddy field mud is set as follows: The robot's movement speed is Based on simplified fluid dynamics formulas, the virtual lateral sludge discharge resistance work is calculated as follows: , in, This represents the average virtual non-recoverable subsidence depth during a single-step mud contact process; its value is the real-time subsidence depth. The arithmetic mean of this foot-to-mud contact process. The distance traveled. The effective flow resistance width at the robot's foot.
[0032] Ultimately, the system output report showed that although the measured energy consumption... Only However, based on equivalent calculations, the total energy consumption of the robot in a real paddy field is... .
[0033] like Figure 2 As shown in the figure, an intelligent quadruped robot paddy field subsidence equivalent testing system of this embodiment includes a physical testing platform 21, a data acquisition module 22, a computing and processing terminal 23, and a human-machine interface 24. The physical testing platform 21 includes an elastic testing mat laid on the ground and motion capture units disposed around the elastic testing mat; in this example, the motion capture unit is an infrared camera.
[0034] The data acquisition module 22 communicates with the motion capture unit and the control interface of the robot under test, respectively, and is used to collect the vertical compression of the robot's foot against the elastic test pad. Data and acquisition of real-time output torque of joint motors .
[0035] The computing terminal 23 is equipped with a nonlinear stiffness mapping model, which is used to perform virtual irrecoverable subsidence depth calculation and equivalent energy consumption calculation.
[0036] The human-computer interaction interface 24 is used to input the target paddy field soil parameters and display the final subsidence depth, equivalent operating energy consumption, and risk assessment results.
[0037] like Figure 3 As shown, the final system interface will display a risk assessment result map. This result map includes a subsidence depth scale marked with levels of safety, warning, risk, and danger, corresponding to different colored or patterned areas, as well as a real-time calculated subsidence depth indicator.
[0038] Example 2: Based on Example 1, this example further considers the layered characteristics of the actual paddy field geological structure and optimizes the stiffness mapping model.
[0039] Real paddy field environments typically consist of an upper layer of soft, loose mud and a lower, hard, plow-substrate layer, with vastly different mechanical properties. To accurately simulate this characteristic, this embodiment employs a piecewise function to construct a stiffness mapping model.
[0040] The specific implementation steps are as follows: S1: Set the parameters for the stratified soil: First, preset the mud thickness threshold. (In this embodiment, it is set) (That is, after a depth exceeding 150mm, it enters the lower soil layer); then, the Bekker soil bearing capacity model parameters for the two soil layers are set respectively: Parameters of the floating mud layer (parameters of the Becker soil bearing capacity model for the floating mud layer): cohesive modulus Friction modulus Subsidence Index .
[0041] Plow pan parameters (Plow pan Becker soil bearing capacity model parameters): Cohesive modulus Friction modulus Subsidence Index .
[0042] S2: The system calculates the irreversible subsidence depth in real time. Dynamically select the corresponding piecewise stiffness mapping model.
[0043] Stage 1: Settlement of the floating mud layer ( ), When the robot's foot is in shallow submersion, the parameters for the floating mud layer are used. At this time, the real-time vertical compression in the laboratory is... Virtual Unrecoverable Depth of Sinking The relationship follows the parameters of the mud layer: , Phase Two: Reaching the Plowshare ( ), When the robot penetrates the loose mud layer and reaches the plowshare, the resistance increases dramatically. At this point, the plowshare parameters are used. Due to the extremely high stiffness of the plowshare, the same amount of compression increases with increasing resistance. Corresponding subsidence depth increment This will be significantly reduced; therefore, the nonlinear stiffness mapping model is revised as follows: , in To reach the subsidence depth The critical bearing capacity at that time is: , For example, when a robot performs a walking operation, the real-time vertical compression is measured. The system detected that the virtual irrecoverable subsidence depth corresponding to this compression amount had exceeded the floating mud thickness threshold, indicating that the robot's foot had penetrated the floating mud layer and contacted the plowshare layer. The system automatically switched to the plowshare layer parameters for correction calculation. Substituting the parameters calculated in this embodiment, the correction term is approximately 12mm, which is the corrected virtual subsidence depth. The results show that, under the segmented model, the rate of increase in subsidence depth slows down significantly after the robot enters the plow pan, which is consistent with the physical characteristics of obtaining hard bottom support after trampling through the floating mud in real paddy fields.
[0044] Components not described in detail in this application are all existing conventional technologies and will not be described further here.
[0045] It is understood that the above specific description of the present invention is only for illustrating the present invention and is not limited to the technical solutions described in the embodiments of the present invention. Those skilled in the art should understand that modifications or equivalent substitutions can still be made to the present invention to achieve the same technical effect; as long as the use needs are met, they are all within the protection scope of the present invention.
Claims
1. A method and system for equivalent testing of paddy field subsidence conditions using an intelligent quadruped robot, characterized in that, Includes the following steps: Step 1: Determine the rheological properties of the target paddy field soil as the parameters of the Becker soil bearing capacity model for simulating the target paddy field environment, and set the motion parameters of the robot under test as its motion speed when inspecting between rice rows. Step 2: Collect real-time vertical compression data of the foot end of the robot under test on the test pad when it walks at the motion speed set in Step 1 on a laboratory elastic test pad with a known stiffness coefficient, and simultaneously collect the real-time output torque of the joint motor. Step 3: Based on the principle of force balance, establish the equivalent equation between the elastic reaction force of the test pad and the bearing capacity of the target paddy field soil, and generate a nonlinear stiffness mapping model; Step 4: Substitute the real-time vertical compression data collected in Step 2 into the nonlinear stiffness mapping model described in Step 3 to calculate the equivalent subsidence depth of the robot under test in the target paddy field subsidence condition, which is the virtual irreversible subsidence depth. ; Step 5: Calculate the equivalent operating energy consumption of the robot under the target paddy field subsidence condition. This is equal to the sum of the actual electrical energy consumed by the motor of the robot during its walking test distance on the laboratory elastic test pad, the energy consumption compensation item of the virtual elastic test pad, and the work done by the lateral mud discharge resistance calculated according to the virtual irrecoverable subsidence depth described in Step 4.
2. The method according to claim 1, characterized in that, In step 3, the construction of the nonlinear stiffness mapping model specifically includes: Establish a mechanical model for the laboratory elasticity test pad: , in To test the reaction force of the pad, The linear stiffness coefficient of the test pad. This represents the real-time vertical compression amount. Establish a Becker bearing pressure model for the target paddy field soil: ,in The target is the bearing capacity per unit area of paddy field soil. It is the cohesive modulus. For friction modulus, The subsidence index, The width of the robot's foot. The depth of the subsidence; based on The equivalent conditions yield the nonlinear stiffness mapping model: , where A is the contact area of the robot's foot.
3. The method according to claim 2, characterized in that, The stiffness mapping model in step 3 is a piecewise function with a preset mud thickness threshold. When the depth of subsidence At that time, the parameters of the Becker soil bearing capacity model for the floating mud layer were used. When the depth of subsidence At that time, the parameters of the Becker soil bearing capacity model of the plow layer were used. To adapt to the geological stratification characteristics of the paddy field, which consists of an upper layer of floating mud and a lower layer of plow layer.
4. The method according to claim 3, characterized in that, When the depth of subsidence When the nonlinear stiffness mapping model is corrected, it becomes: ， in To reach the subsidence depth The critical bearing capacity at that time is: 。 5. The method according to claim 1, characterized in that, In step 5, the formula for calculating the equivalent operating energy consumption is: ， in, This represents the equivalent energy consumption under real paddy field conditions. The electrical energy consumption of the motor of the robot under test was measured on a laboratory elastic test mat. The energy consumption compensation term for the elastic test pad is equal to the total work done by the target paddy soil during the loading process calculated based on the Becker model minus the elastic potential energy of the laboratory elastic test pad. The virtual lateral mud discharge resistance work is calculated using fluid dynamics formulas based on the virtual irrecoverable subsidence depth, the fluid viscosity coefficient of the paddy field mud, the robot's foot movement speed, and the robot's walking distance. , The average virtual non-recoverable subsidence depth during a single-step mud contact process.
6. The method according to claim 5, characterized in that, The average virtual irrecoverable subsidence depth during the single-step mud contact process The value is the real-time subsidence depth obtained in step 4. The arithmetic mean of this foot-to-mud contact process. The distance traveled. The fluid viscosity coefficient of the target paddy field mud. The effective flow resistance width at the robot's foot end. The speed of motion.
7. The method according to claim 1, characterized in that, The method also includes the step of generating a passability risk assessment report: If the virtual irrecoverable sinking depth calculated in step 4 is greater than the effective length of the robot's lower leg or causes the chassis to contact the virtual mud surface, then the robot is determined to be at risk of getting stuck in the target paddy field, and a risk alarm is output, generating a passability risk assessment report.
8. An equivalent testing system for implementing the method of any one of claims 1 to 7, characterized in that, include: The physical testing platform includes an elastic testing mat laid on the ground and motion capture units located around the elastic testing mat. The data acquisition module communicates with the motion capture unit and the control interface of the robot under test, respectively, and is used to collect data on the vertical compression of the robot's foot against the elastic test pad and to obtain the real-time output torque of the joint motor. The computing terminal is equipped with a nonlinear stiffness mapping model, which is used to perform virtual irreversible subsidence depth calculation and equivalent energy consumption calculation. A human-computer interaction interface is used to input target paddy field soil parameters and display the final subsidence depth, equivalent operational energy consumption, and / or risk assessment results.
9. The system according to claim 8, characterized in that, The evaluation results displayed on the human-computer interaction interface include a safe zone, a warning zone, a risk zone, and a danger zone, presented in a visual format, and are marked with the virtual irreversible subsidence depth calculated in real time.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the computing processing terminal, it implements the steps of the equivalent test method as described in any one of claims 1 to 6.