Robot balance adjustment methods, devices, electronic equipment and storage media

Abstract

This application relates to the field of robotics technology and discloses a robot balance adjustment method, device, electronic device, and storage medium. The method includes: collecting robot posture data and leg grounding state data; calculating the height adjustment amount of each leg based on the posture data and the leg grounding state data; and adjusting the lifting and lowering of each leg according to the height adjustment amount to keep the robot's loading surface level. This application dynamically adjusts the lifting and lowering of the legs by collecting robot posture data and leg grounding state data and calculating the height adjustment amount based on this data, keeping the loading surface level. This effectively copes with the inclination and drop of hilly and mountainous terrain, ensuring that the robot maintains dynamic balance during movement, and solves the problem in related technologies where robots cannot meet the dynamic balance requirements of complex terrain.

Description

Technical Field

[0001] This application relates to the field of robotics technology, specifically to robot balance adjustment methods, devices, electronic devices, and storage media. Background Technology

[0002] Currently, the proportion of machine-harvested tea is increasing year by year. The main machine-harvesting equipment relies on single / double-person lifting tea harvesters. These machines are mainly used by manual laborers to move the equipment forward for harvesting, which is labor-intensive, inefficient, and very inconvenient for collecting and transporting fresh leaves.

[0003] Tea-picking robots for hilly and mountainous terrain are an important application of agricultural intelligence, aiming to solve the problems of labor shortage and low efficiency in traditional tea picking. They are particularly suitable for tea gardens in hilly and mountainous areas with complex terrain, such as gentle slope tea gardens and terraced tea gardens. Dynamic stability control of the mobile platform is especially important for tea-picking robots in hilly and mountainous areas.

[0004] In related technologies, the application scenarios for the walking structure of tea-harvesting machines are mainly in flat tea gardens, mostly using tracked walking mechanisms, with a small number using four-wheel walking structures and rail walking mechanisms. Hilly and mountainous tea plantations are mostly distributed in hilly and mountainous areas with large slopes, and the difference in height between the tea bushes planted in front and behind is large, with a large inclination angle. Conventional tracked and wheeled walking structures cannot meet the needs of walking between bushes in hilly and mountainous areas. Rails can be used, but the laying cost is high, and the amount of work for moving and resetting is large, making it difficult to promote on a large scale. Summary of the Invention

[0005] This application provides a robot balance adjustment method, device, electronic device, and storage medium to solve the problem that tea-picking robots in related technologies cannot meet the stability requirements for walking on complex terrain.

[0006] In a first aspect, this application provides a robot balance adjustment method, comprising: collecting robot posture data and leg grounding state data; calculating the height adjustment amount of each leg based on the posture data and the leg grounding state data; and adjusting the lifting and lowering of each leg according to the height adjustment amount to maintain the robot's loading surface level.

[0007] Beneficial Effects: This application collects robot posture data and leg grounding status data, and calculates height adjustment based on this data to dynamically regulate leg lifting and lowering, keeping the loading surface level. This solution utilizes real-time data acquisition and a closed-loop adjustment mechanism to effectively cope with the tilt and elevation differences in hilly and mountainous terrain, ensuring the robot maintains dynamic balance during movement. This not only improves the robot's stability and anti-interference capabilities but also avoids decreased harvesting efficiency and energy loss caused by platform tilting. Furthermore, it extends equipment lifespan by balancing the load, solving the problem in related technologies where robots cannot achieve dynamic balance in complex terrains.

[0008] In one optional implementation, the acquisition of the robot's posture data and leg grounding status data includes: acquiring Euler angle data from a gyroscope at a preset frequency, the Euler angle data including heading angle, pitch angle and roll angle; and acquiring deformation data from strain gauge sensors on each leg to determine the wheel grounding status.

[0009] Beneficial effects: By acquiring Euler angle data from the gyroscope and deformation data from the strain gauge sensor to determine the landing status, accurate and real-time attitude and landing information is provided, improving the reliability and response speed of data acquisition. This ensures the accuracy of subsequent altitude adjustment calculations, avoids adjustment failures caused by sensor delays or errors, further enhances the system's adaptability and stability in dynamic environments, and lays a solid foundation for overall balance control.

[0010] In one optional implementation, calculating the height adjustment of each leg based on the posture data and grounding state data includes: calculating the height difference of each wheel using a rotation matrix based on the Euler angle data; wherein the rotation matrix is ​​calculated based on the robot's wheel spacing and orientation definition.

[0011] Beneficial effects: By calculating the height difference of each wheel using a rotation matrix and based on parameters such as Euler angles and wheel spacing, the derivation of height adjustment amounts in complex terrain is simplified. This mathematical modeling method improves computational efficiency, avoids errors from manual estimation, and ensures more scientific and consistent adjustment amounts. It not only accelerates the system's response speed but also enables the robot to quickly adapt to terrains with varying slopes, improving the accuracy and scalability of dynamic balance.

[0012] In one optional implementation, the calculation of the rotation matrix includes: rotating around the object coordinate system in the order of heading angle-pitch angle-roll angle, with the rotation angle determined based on the Euler angle data; and calculating the height data of each wheel in the robot height direction based on the coordinate points of each wheel and the rotation matrix.

[0013] Beneficial effects: This scheme further clarifies the calculation order of the rotation matrix and the coordinate transformation process, obtaining height data by multiplying the wheel coordinates by the left. This structured calculation method reduces algorithm complexity, ensures the repeatability and stability of the calculation results, enables the system to efficiently handle attitude changes in three-dimensional space, avoids adjustment deviations caused by calculation chaos, thereby enhancing the reliability and real-time performance of overall balance control, and is particularly suitable for the rapid adjustment needs of hilly and mountainous terrain.

[0014] In one optional implementation, acquiring deformation data from strain gauge sensors on each leg includes: measuring resistance changes using full-bridge strain gauges to quantify leg deformation; determining whether the wheel is on the ground based on the leg deformation data; and, if the wheel is not on the ground, controlling the lifting motor to extend so that the wheel is on the ground.

[0015] Beneficial effects: By using full-bridge strain gauges to measure resistance changes to quantify leg deformation, and controlling the lifting motor based on the leg deformation data, the robot ensures the wheels are on the ground. The full-bridge strain gauge design improves sensitivity, accurately detecting wheel contact and preventing energy loss and slippage caused by suspension. This solution ensures all wheels are in effective contact with the ground, providing reliable input for platform leveling, reducing power waste, and improving the robot's grip and stability on uneven terrain.

[0016] In one optional implementation, the method further includes: after adjusting the lifting of each leg, rereading the posture data and leg grounding status data to determine whether the platform is balanced and whether all wheels are in contact with the ground;

[0017] Beneficial effects: After adjustment, sensor data is reread to determine the balance state and adjustments are repeated until balance is achieved. This feedback mechanism forms a closed-loop control, avoiding the problem of incomplete adjustments in a single instance and improving the system's fault tolerance and adaptability. It enables the robot to continuously respond to terrain changes, ensuring the platform remains level and on all fours, thus enhancing overall operational stability and safety, and achieving dynamic balance.

[0018] In an optional implementation, the method further includes: in manual mode, displaying the sensor status via a remote control, and the user manually adjusting the lifting motor; after manual adjustment, automatically returning to the automatic balancing process.

[0019] Beneficial effects: Providing a manual mode, displaying sensor status via remote control, and allowing users to manually adjust the lifting motor before returning to the automatic process, increases the system's flexibility and fault tolerance. In case of automatic system malfunctions or special terrain conditions, users can intervene to ensure uninterrupted control. This not only improves operational convenience and user experience but also enhances system reliability as a backup solution, enabling the robot to handle more unexpected scenarios.

[0020] Secondly, this application provides a robot balance adjustment device, comprising: a sensor module for collecting robot posture data and leg grounding state data; a control module for calculating the height adjustment amount of each leg based on the posture data and the leg grounding state data; and an execution module for adjusting the lifting and lowering of each leg according to the height adjustment amount to maintain the loading surface of the robot horizontal.

[0021] Beneficial effects: Through the coordinated operation of the sensor module, control module, and execution module, real-time acquisition of robot posture data and leg grounding status data, calculation of height adjustment, and dynamic adjustment of leg lifting and lowering are achieved. This modular design enables the device to respond quickly to terrain changes and ensures that the loading surface remains level through a closed-loop control mechanism, thereby significantly improving the robot's dynamic stability and anti-interference ability in complex terrains such as hills and mountains.

[0022] In one alternative implementation, the sensor module includes: a gyroscope configured to acquire Euler angle data at a frequency of 100Hz; and a strain gauge sensor disposed on the robot's leg and configured to detect the wheel's ground contact status.

[0023] Beneficial effects: High-frequency data acquisition via gyroscope ensures the real-time nature and accuracy of attitude information, while the introduction of strain gauge sensors provides reliable physical deformation detection, accurately determining whether the wheels are effectively grounded. This approach enhances the integrity and reliability of data input, laying a solid foundation for subsequent control module calculations, thereby improving the overall system's response speed and adaptability. It avoids adjustment failures caused by sensor delays or errors, making it particularly suitable for rapid balancing requirements in dynamic environments.

[0024] In one optional implementation, the control module includes: a data processing unit configured to calculate the height difference of each wheel using a rotation matrix based on the Euler angle data; and a determination unit configured to determine the ground contact status of the wheel based on the deformation data of the strain gauge sensor, and, if the wheel is determined not to be on the ground, control the lifting motor to extend so that the wheel is on the ground.

[0025] Beneficial effects: The structured division of labor in this scheme improves computational efficiency; the application of the rotation matrix makes the derivation of height differences more scientific and consistent, avoiding the deviations of manual estimation; the decision unit ensures that the wheels can be adjusted in time when they are not on the ground, preventing idling and energy loss. Furthermore, this scheme optimizes the control process, improves the accuracy and fault tolerance of balance adjustment, enabling the device to better cope with the undulating terrain of hilly areas, and further enhances the stability and reliability of dynamic balance.

[0026] Thirdly, this application provides an electronic device, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the robot balance adjustment method of the first aspect or any corresponding embodiment described above.

[0027] Fourthly, this application provides a computer-readable storage medium storing computer instructions for causing a computer to execute the robot balance adjustment method described in the first aspect or any corresponding embodiment. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0029] Figure 1 This is a schematic flowchart of a first embodiment of a robot balance adjustment method according to this application.

[0030] Figure 2 This is a second flowchart illustrating the robot balance adjustment method according to an embodiment of this application;

[0031] Figure 3 This is a schematic diagram of the third process of the robot balance adjustment method according to the embodiments of this application;

[0032] Figure 4 This is a circuit diagram of a strain gauge according to an embodiment of this application;

[0033] Figure 5 This is a schematic diagram of the fourth process of the robot balance adjustment method according to the embodiments of this application;

[0034] Figure 6 This is a schematic diagram of the Euler angle rotation sequence according to an embodiment of this application;

[0035] Figure 7 This is a schematic diagram of the gyroscope control logic according to an embodiment of this application;

[0036] Figure 8 This is a flowchart illustrating the robot balance adjustment method according to an embodiment of this application;

[0037] Figure 9 This is a structural block diagram of a robot balance adjustment device according to an embodiment of this application;

[0038] Figure 10 This is a schematic diagram of the specific structure of the robot balance adjustment device according to an embodiment of this application;

[0039] Figure 11 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0041] It is understood that before using the technical solutions disclosed in the various embodiments of this application, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this application in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0042] Currently, tea gardens in hilly and mountainous areas account for a relatively high proportion, of which machine-harvested tea accounts for about 40% and is increasing year by year. The machine-harvesting equipment mainly relies on single / double-person lifting tea harvesters. These types of equipment are mainly carried out by manual labor to move the equipment forward for harvesting, which is labor-intensive, inefficient, and very inconvenient for collecting and transporting fresh leaves.

[0043] Tea-picking robots for hilly and mountainous areas are an important application of agricultural intelligence, aiming to solve problems such as labor shortage and low efficiency in traditional tea picking. They are especially suitable for tea gardens in hilly and mountainous areas with complex terrain, such as terraced tea gardens and gentle slope tea gardens.

[0044] Tea-picking robots in hilly and mountainous areas typically include a mobile platform for hilly and mountainous terrain, a visual recognition system, and a flexible picking robotic arm. Both the visual recognition system and the flexible picking robotic arm rely on the mobile platform for hilly and mountainous terrain. Therefore, the dynamic stability control of the mobile platform for hilly and mountainous terrain is particularly important for tea-picking robots in hilly and mountainous areas.

[0045] In related technologies, research on automated harvesting machinery for bulk tea mainly focuses on harvesting mechanism identification and guidance / obstacle avoidance systems, with less research on the locomotive mechanism. Currently, the application scenarios for the locomotive structure of tea harvesters are mainly in flat tea gardens, mostly using tracked locomotives, with a small number using four-wheeled locomotives and tracked locomotives. Hilly and mountainous tea plantations are mostly distributed in hilly and mountainous areas with large slopes and significant differences in the height and inclination between the tea bushes planted on both sides. Conventional tracked and wheeled locomotives cannot meet the needs of locomotive movement between bushes in hilly and mountainous areas. Tracks can be used, but the laying cost is high, and the workload of moving and resetting is large, making it difficult to promote on a large scale.

[0046] According to an embodiment of this application, a robot balance adjustment method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Also, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0047] This embodiment provides a robot balance adjustment method, which can be used in the aforementioned hilly and mountainous tea-picking robot. Figure 1 This is a flowchart of a robot balance adjustment method according to an embodiment of this application, with reference to... Figure 1 As shown, the process includes the following steps:

[0048] Step S100: Collect the robot's posture data and leg grounding status data.

[0049] It should be noted that posture data refers to the robot's orientation and angle information in three-dimensional space, used to describe its tilt degree; leg grounding status data refers to the detection information of the robot's legs in contact with the ground, used to determine whether the wheels are effectively in contact with the ground.

[0050] In this step S100, by continuously collecting posture data and leg grounding status data, the robot is able to capture terrain changes and avoid adjustment failures caused by data delays.

[0051] Step S200: Calculate the height adjustment amount of each leg based on posture data and leg grounding status data.

[0052] It should be noted that the height adjustment amount refers to the amount of leg extension required to keep the platform level.

[0053] In this step S200, the complex posture data and leg grounding status data are simplified into operable height adjustment values, which improves adjustment efficiency and helps the robot to quickly adapt to terrain undulations.

[0054] In step S300, the lifting and lowering of each leg is adjusted according to the height adjustment amount to keep the loading surface of the robot level.

[0055] It should be noted that the loading surface refers to the platform surface on the robot used to install operating equipment such as harvesting robotic arms, and its levelness directly affects the stability of operation; while the adjustment of the leg lifting is achieved through the actuators installed on the robot's legs, such as motor-driven lifting rods.

[0056] In step S300, the impact of terrain is offset by physical adjustment to ensure that the loading surface is level, and ultimately the robot achieves dynamic balance, thereby improving operational safety and efficiency.

[0057] This application collects robot posture data and leg grounding status data, and calculates height adjustment based on this data to dynamically regulate leg lifting and lowering, keeping the loading surface level. This solution utilizes real-time data acquisition and a closed-loop adjustment mechanism to effectively handle the tilt and elevation differences in hilly and mountainous terrain, ensuring the robot maintains dynamic balance during movement. This not only improves the robot's stability and anti-interference capabilities but also avoids decreased harvesting efficiency and energy loss caused by platform tilting. Furthermore, it extends equipment lifespan by balancing the load, solving the problem in related technologies where robots cannot achieve dynamic balance in complex terrains.

[0058] This embodiment provides a robot balance adjustment method, which can be used in the aforementioned hilly and mountainous tea-picking robots, etc. Figure 2 This is a flowchart of a robot balance adjustment method according to an embodiment of this application, with reference to... Figure 2 As shown, the process includes the following steps:

[0059] Step S100: Collect the robot's posture data and leg grounding status data.

[0060] Specifically, step S100 includes:

[0061] Step S110: Acquire Euler angle data from the gyroscope at a preset frequency.

[0062] It should be noted that Euler angles are an angle system that describes the rotational orientation of an object in three-dimensional space, consisting of yaw, pitch, and roll. The yaw angle represents the robot's rotation around the vertical axis (Z-axis) (e.g., 0° to 360°), the pitch angle represents the forward and backward tilt (e.g., -90° to 90°), and the roll angle represents the left and right tilt (e.g., -180° to 180°).

[0063] Optionally, in some embodiments of this application, the gyroscope can be controlled to continuously collect Euler angle data at a preset frequency of 100Hz, thereby ensuring the real-time nature of the data and enabling the system to respond quickly to terrain fluctuations.

[0064] Step S120: Obtain deformation data from the strain gauge sensors of each leg to determine the wheel's ground contact status.

[0065] It should be noted that a strain gauge is made by winding copper or nichrome wire with a diameter of Φ=0.02-0.05mm into a grid shape (or by etching a very thin metal foil into a grid shape) and sandwiching it between two layers of insulating sheets (substrate). Silver-plated copper wire is connected to the strain gauge grid as the resistance lead. It quantifies the minute deformation (strain) of an object's surface by measuring changes in resistance and is widely used in mechanics, engineering monitoring, and industrial automation. The strain gauge is attached to the object being measured, causing it to stretch or contract with the strain of the object. This causes the metal foil inside to lengthen or shorten with the strain. When a metal or semiconductor material is stretched or compressed by an external force, its geometric dimensions (length, cross-sectional area) and internal crystal structure change, resulting in a change in resistance: during stretching, the material length increases and the cross-sectional area decreases, thus increasing resistance; during compression, the length shortens and the cross-sectional area increases, thus decreasing resistance. The relationship between the relative change in resistance (ΔR / R) and strain (ε=ΔL / L) is as follows:

[0066] ΔR / R = Kε

[0067] Wherein, K is the sensitivity coefficient (typically 2~5 for metallic materials, and over 100 for semiconductor materials);

[0068] According to Hooke's Law, strain ε and stress σ (force per unit area) satisfy the following:

[0069] σ = Eε

[0070] Where E is the elastic modulus of the material, and stress can be indirectly calculated by measuring ε.

[0071] During the robot's movement, deformation data is acquired from strain gauges on each leg. For example, the strain gauge on the first leg shows an increase in resistance, while the resistance on the second leg decreases. Based on this data, the system determines that the wheel on the first leg is fully on the ground, while the wheel on the second leg is partially suspended in the air. After this determination, the system can trigger subsequent adjustments, such as extending the suspended leg, to ensure stability.

[0072] This step S120 uses deformation data to reflect the force on the legs, thereby confirming the grounding status and ensuring that all wheels are in effective contact with the ground, which helps to avoid idling or energy loss.

[0073] In steps S110 and S120 above, Euler angle data is acquired from the gyroscope, and deformation data is acquired from the strain gauge sensor to determine the landing state. This provides accurate and real-time attitude and landing information, enhancing the reliability and response speed of data acquisition. This ensures the accuracy of subsequent altitude adjustment calculations, avoids adjustment failures caused by sensor delays or errors, further improves the system's adaptability and stability in dynamic environments, and lays a solid foundation for overall balance control.

[0074] Reference Figure 3 As shown, in some optional embodiments, step S120 above includes:

[0075] Step S121: Quantify the leg deformation by measuring the resistance change using a full-bridge strain gauge.

[0076] Reference Figure 4 As shown, optionally, in some embodiments of this application, the strain gauge sensor employs a full-bridge strain gauge, consisting of four resistors R1, R2, R3, and R4 connected in a rhomboid structure. One diagonal of the bridge is connected to the excitation voltage U0, and the other diagonal is the output voltage Ui. The main function of this full-bridge strain gauge is to improve sensitivity and suppress temperature errors. The output voltage Ui of the bridge is given by the following general formula:

[0077]

[0078] When the bridge circuit satisfies R1R3=R2R4, the output voltage Ui is zero. At this time, the bridge circuit is in a balanced state, or it is equivalent to R1 / R4=R2 / R3.

[0079] When the resistance values ​​of the four resistors change slightly (ΔR1, ΔR2, ΔR3, and ΔR4), the approximate formula for calculating the change in output voltage ΔUi is as follows:

[0080]

[0081] It should be noted that the ratio of the relative change in strain gauge resistance to the relative change in material length, i.e., the sensitivity coefficient of the strain gauge, can be expressed by the following formula:

[0082]

[0083] In step S121, the resistance change of the robot's leg caused by the force is measured using a full-bridge strain gauge sensor, and the deformation data is quantified by outputting the circuit, which improves the measurement sensitivity and anti-interference ability, and helps to ensure that the data accurately reflects the degree of extension or bending of the leg.

[0084] Step S122: Determine whether the wheel is on the ground based on the deformation data. If it is determined that the wheel is not on the ground, control the lifting motor to extend so that the wheel is on the ground.

[0085] It should be noted that in some embodiments of this application, the hilly tea-picking robot has four independently controlled "leg"-shaped structures. Each "leg" is equipped with a lifting motor and a strain gauge sensor. By collecting data from the gyroscope and the four strain gauge sensors, the controller can determine the ground clearance of each "leg" and the angle of the loading surface. By adjusting each lifting motor, the loading surface can be kept level, thus achieving a self-balancing effect.

[0086] In step S122, deformation data (such as changes in resistance or deformation) is first analyzed to determine the wheel's ground contact status (fully on the ground, partially suspended, or completely off the ground). If the wheel is determined not to be on the ground, a control signal is triggered to drive the lifting motor to extend the legs, causing the wheel to contact the ground. This step forms a closed-loop feedback, which helps ensure the robot's stability.

[0087] In steps S121 and S122 above, Euler angle data is acquired from the gyroscope, and deformation data is acquired from the strain gauge sensor to determine the landing state. This provides accurate and real-time attitude and landing information, enhancing the reliability and response speed of data acquisition. This ensures the accuracy of subsequent height adjustment calculations, avoids adjustment failures caused by sensor delays or errors, further improves the system's adaptability and stability in dynamic environments, and lays a solid foundation for overall balance control.

[0088] Step S200: Based on posture data and leg ground contact data, calculate the height adjustment amount for each leg. For details, please refer to [link to relevant documentation]. Figure 1 Step S200 of the illustrated embodiment will not be described again here.

[0089] Step S300: Adjust the lifting of each leg according to the height adjustment amount to keep the robot's loading surface level. See details below. Figure 1 Step S300 of the illustrated embodiment will not be described again here.

[0090] This embodiment provides a robot balance adjustment method, which can be used in the aforementioned hilly and mountainous tea-picking robot. Figure 5 This is a flowchart of a robot balance adjustment method according to an embodiment of this application, with reference to... Figure 5 As shown, the process includes the following steps:

[0091] Step S100: Collect the robot's posture data and leg ground contact data. For details, please refer to [link to relevant documentation]. Figure 1 Step S100 of the illustrated embodiment will not be described again here.

[0092] Step S200: Calculate the height adjustment amount of each leg based on posture data and leg grounding status data.

[0093] Specifically, step S200 includes: calculating the height difference of each wheel using a rotation matrix based on Euler angle data; wherein the rotation matrix is ​​calculated based on the robot's wheel spacing and orientation definition.

[0094] More specifically, in step S200, the steps for calculating the rotation matrix include:

[0095] Step S210: Rotate around the object coordinate system in the order of heading angle-pitch angle-roll angle, with the rotation angle determined based on Euler angle data.

[0096] Reference Figure 6 As shown, and more specifically, in some embodiments of this application, the robot uses a front-left-top (FLU) coordinate system, and the geographic coordinate system uses an east-north-sky (ENU) coordinate system. The Euler angle rotation sequence is sky (Z) – north (Y) – east (X) (rotating along the Z-axis first, then the Y-axis, and finally the X-axis). The specific definitions are as follows:

[0097] Rotation around the Z-axis: Yaw range: [-PI, PI];

[0098] Rotation around the Y-axis: Pitch range: [-PI / 2, PI / 2];

[0099] Rotation around the X-axis: Roll angle range: [-PI, PI].

[0100] Step S220: Calculate the height data of each wheel in the robot height direction based on the coordinate points and rotation matrix of each wheel.

[0101] Combination Figure 6 and Figure 7 As shown, in some embodiments of this application, the controller acquires Euler angle (yaw / pitch / roll) data from the gyroscope at a frequency of 100Hz. In three-dimensional space, the z-axis (i.e., the height direction when the robot is in a horizontal state) / Yaw rotation matrix is:

[0102]

[0103] The y-axis / Pitch rotation matrix is:

[0104]

[0105] The x-axis / Roll rotation matrices are as follows:

[0106]

[0107] In three-dimensional space, rotating an object around its coordinate system by angles α, β, θ in the Yaw-Pitch-Roll order, the final rotation matrix is:

[0108]

[0109] Substituting the above formula and expanding it, we get...

[0110]

[0111] Given the length L and width W of the wheel spacing between the four "legs" of the tea-picking robot, and based on the definition of direction, since the heading angle Yaw is the same before and after rotation, α=0. Therefore, its rotation matrix is ​​as follows:

[0112]

[0113] The coordinates of the wheels in the rotated coordinate system are defined as (L / 2, W / 2, 0), (L / 2, -W / 2, 0), (-L / 2, -W / 2, 0), and (-L / 2, W / 2, 0) respectively, in the order of left front, right front, right rear, and left rear. Multiplying these coordinates by the rotation matrix to the left yields the Z-axis data for the four wheels as follows:

[0114]

[0115] The height difference of the four wheels is calculated above. Sending this height difference to the respective lifting motors will achieve the overall self-balancing effect.

[0116] In steps S210 and S220 above, the calculation order of the rotation matrix and the coordinate transformation process are clearly defined, and the height data is obtained by multiplying the wheel coordinate points by left. This structured calculation method reduces the algorithm complexity, ensures the repeatability and stability of the calculation results, enables the system to efficiently handle attitude changes in three-dimensional space, avoids adjustment deviations caused by calculation chaos, thereby enhancing the reliability and real-time performance of overall balance control, and is particularly suitable for the rapid adjustment needs of hilly and mountainous terrain.

[0117] Step S300: Adjust the lifting of each leg according to the height adjustment amount to keep the robot's loading surface level. See details below. Figure 1 Step S300 of the illustrated embodiment will not be described again here.

[0118] Optionally, in some embodiments of this application, the robot balance adjustment method of this application further includes:

[0119] Step S400: After adjusting the lifting of each leg, reread the posture data and leg grounding status data to determine whether the platform is balanced and whether all wheels are on the ground; if the platform is determined to be unbalanced, repeat the calculation and adjustment steps.

[0120] In these embodiments, sensor data is reread after adjustment to determine the balance state and adjustments are repeated until balance is achieved. This feedback mechanism forms a closed-loop control, avoiding the problem of incomplete adjustments in a single operation and improving the system's fault tolerance and adaptability. This enables the robot to continuously respond to terrain changes, ensuring the platform remains level and on all fours, thereby enhancing the overall stability and safety of operations and achieving dynamic balance.

[0121] Optionally, in some embodiments of this application, the robot balance adjustment method of this application further includes:

[0122] In manual mode, the sensor status is displayed via remote control, and the user can manually adjust the lifting motor; after manual adjustment, it automatically returns to the automatic balancing process.

[0123] These embodiments provide a manual mode, displaying sensor status via remote control and allowing users to manually adjust the lifting motor before returning to the automatic process. This approach increases the system's flexibility and fault tolerance; in case of automatic system malfunctions or special terrain conditions, users can intervene to ensure uninterrupted control. This not only improves operational convenience and user experience but also enhances system reliability as a backup solution, enabling the robot to handle more unexpected scenarios.

[0124] Reference Figure 8 As shown, in conjunction with the above embodiments, the robot balance adjustment method of this application determines whether the robot's wheels are on the ground by reading and calculating the deformation pressure difference of the strain gauges on the robot's "legs". The determination process is as follows:

[0125] First determine whether automatic balancing needs to be activated. If automatic balancing is not required, please inform us how to perform manual balancing.

[0126] Determine whether the wheels are on the ground, because a four-legged robot may have three legs on the ground and one leg suspended in the air, which affects the height difference calculation.

[0127] Adjusting the lifting motor to bring the wheels to the ground directly drives the suspended foot to extend the lifting rod to the ground. After the suspended foot touches the ground, it is necessary to read the strain gauge parameters again to determine whether the other feet are suspended after the suspended foot is extended. This is a unique setting for quadruped robots when adjusting their height.

[0128] After calculating the height difference using the rotation matrix and adjusting the lifting motor to achieve balance, four scenarios will exist:

[0129] State (1): All wheels are on the ground, and the platform is balanced;

[0130] State (2) All wheels are on the ground, and the platform is unbalanced;

[0131] State (3): One foot is suspended in the air, and the platform is balanced;

[0132] In state (4), one foot is suspended in the air, and the platform is unbalanced;

[0133] In all of the above situations, it is necessary to reread the strain gauge parameters, determine whether there is a suspended foot, adjust the suspended foot, and then determine whether the platform is balanced again.

[0134] After the above adjustments, the desired result is that the platform is balanced and has all four legs on the ground, so as to provide stable and solid support for the tea picking platform in hilly and mountainous areas.

[0135] In addition, it's necessary to explain the manual balancing step in the above process. Manual balancing serves as a system anomaly handling method; when this mode is entered, the automatic control system will no longer control the equipment. Simultaneously, the strain gauge and gyroscope status can be displayed on the remote control's built-in screen, serving as data for adjusting the equipment's status. Specifically, the process is as follows: Activate manual operation – manually adjust the lifting motor – read strain gauge parameters – determine if the wheels are on the ground – feed back the wheel contact information to the remote control, which displays it in real-time – read gyroscope parameters – determine if the platform is balanced, with the remote control displaying the levelness in real-time.

[0136] This embodiment also provides a robot balance adjustment device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0137] This embodiment provides a robot balance adjustment device, referring to... Figure 9 As shown, it includes:

[0138] Sensor module 10 is used to collect the robot's posture data and leg ground contact status data;

[0139] Control module 20 is used to calculate the height adjustment amount of each leg based on posture data and leg grounding status data;

[0140] The execution module 30 is used to adjust the lifting of each leg according to the height adjustment amount to keep the robot's loading surface level.

[0141] The robot balance adjustment device of this application achieves real-time acquisition of robot posture data and leg grounding status data, calculation of height adjustment, and dynamic adjustment of leg lifting and lowering through the coordinated work of sensor module, control module, and execution module. This modular design enables the device to respond quickly to terrain changes and ensures that the loading surface remains level through a closed-loop control mechanism, thereby significantly improving the robot's dynamic stability and anti-interference ability in complex terrains such as hills and mountains.

[0142] In some alternative implementations, refer to Figure 10 As shown, the sensor module 10 includes:

[0143] The gyroscope is configured to acquire Euler angle data at a frequency of 100Hz;

[0144] Strain gauge sensors are mounted on the robot's legs and configured to detect the wheel's ground contact status.

[0145] In these embodiments, high-frequency data acquisition via gyroscopes ensures the real-time nature and accuracy of attitude information, while the introduction of strain gauge sensors provides reliable physical deformation detection, accurately determining whether the wheels are effectively grounded. This approach enhances the integrity and reliability of data input, laying a solid foundation for subsequent control module calculations, thereby improving the overall system's response speed and adaptability. It avoids adjustment failures caused by sensor delays or errors, making it particularly suitable for rapid balancing requirements in dynamic environments.

[0146] In some alternative implementations, the control module includes:

[0147] The data processing unit is configured to calculate the height difference of each wheel using a rotation matrix based on Euler angle data;

[0148] The determination unit is configured to determine the ground contact status of the wheel based on the deformation data of the strain gauge sensor. If the wheel is not in contact with the ground, the lifting motor is controlled to extend so that the wheel is in contact with the ground.

[0149] In these embodiments, structured division of labor improves computational efficiency, the application of rotation matrices makes the derivation of height differences more scientific and consistent, avoiding the biases of manual estimation; the decision unit ensures that the wheels can be adjusted in time when not on the ground, preventing idling and energy loss. Furthermore, this scheme optimizes the control process, improves the accuracy and fault tolerance of balance adjustment, enabling the device to better cope with the undulating terrain of hilly areas, further enhancing the stability and reliability of dynamic balance.

[0150] The robot balance adjustment device provided in this application embodiment can execute the robot balance adjustment method provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0151] Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0152] The following is a detailed reference. Figure 11 The diagram illustrates a structural schematic suitable for implementing the electronic device described in the embodiments of this application. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 501, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from memory 508 into random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of the electronic device. The processor 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0153] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 508 including, for example, magnetic tapes, hard disks, etc.; and communication devices 509. Communication device 509 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 11 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0154] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a memory 508, or installed from a ROM 502. When the computer program is executed by the processor 501, it performs the functions defined in the robot balance adjustment method of embodiments of this application.

[0155] Figure 11The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0156] This application also provides a computer-readable storage medium. The methods described in this application can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the robot balance adjustment method shown in the above embodiments is implemented.

[0157] A portion of this application can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to this application through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0158] Although embodiments of this application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of this application, and all such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A method for adjusting robot balance, characterized in that, include: Collect robot posture data and leg ground contact data; Based on the posture data and the leg grounding status data, the height adjustment amount of each leg is calculated; Adjust the lifting and lowering of each leg according to the height adjustment amount to keep the loading surface of the robot level; The robot's posture data and leg landing status data include: Euler angle data is acquired from a gyroscope at a preset frequency, and the Euler angle data includes heading angle, pitch angle and roll angle; Deformation data is obtained from strain gauge sensors on each leg to determine the wheel's ground contact status; The calculation of the height adjustment amount for each leg based on the posture data and leg grounding status data includes: Based on the Euler angle data, the height difference of each wheel is calculated using a rotation matrix; The rotation matrix is ​​calculated based on the robot's wheel spacing and orientation. The calculation of the rotation matrix includes: The object coordinate system is rotated in the order of heading angle-pitch angle-roll angle, and the rotation angle is determined based on the Euler angle data. The height data of each wheel in the robot's height direction is calculated based on the coordinates of each wheel and the rotation matrix. The deformation data acquired from the strain gauge sensors of each leg includes: Leg deformation is quantified by measuring resistance changes using full-bridge strain gauges. Based on the leg deformation data, it is determined whether the wheel is on the ground. If it is determined that the wheel is not on the ground, the lifting motor is controlled to extend so that the wheel is on the ground. The method further includes: After adjusting the lifting of each leg, the posture data and leg ground contact data are reread to determine whether the loading surface is balanced and whether all wheels are in contact with the ground. If it is determined that the loading surface has not reached a balanced state, repeat the calculation and adjustment steps.

2. The robot balance adjustment method according to claim 1, characterized in that, The method further includes: In manual mode, the sensor status is displayed via remote control, and the user can manually adjust the lifting motor. After manual adjustment, it automatically returns to the automatic balancing process.

3. A robot balance adjustment device for implementing the robot balance adjustment method according to claim 1 or 2, characterized in that, include: The sensor module is used to collect the robot's posture data and leg ground contact data; The control module is used to calculate the height adjustment amount of each leg based on the posture data and the leg grounding state data; An execution module is used to adjust the lifting and lowering of each leg according to the height adjustment amount to keep the loading surface of the robot level.

4. The robot balance adjustment device according to claim 3, characterized in that, The sensor module includes: The gyroscope is configured to acquire Euler angle data at a frequency of 100Hz; A strain gauge sensor is installed on the robot's leg and configured to detect the wheel's ground contact status.

5. The robot balance adjustment device according to claim 4, characterized in that, The control module includes: The data processing unit is configured to calculate the height difference of each wheel using a rotation matrix based on the Euler angle data. The determination unit is configured to determine the ground contact status of the wheel based on the deformation data of the strain gauge sensor, and if it determines that the wheel is not on the ground, control the lifting motor to extend so that the wheel is on the ground.

6. An electronic device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the robot balance adjustment method according to claim 1 or 2.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the robot balance adjustment method according to claim 1 or 2.

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