High-precision automatic leveling control method and system for heavy-load movable formwork robot

Abstract

The invention provides a high-precision automatic leveling control method and system for a heavy-load movable formwork robot, and relates to the technical field of robot automatic control. The method comprises the following steps: firstly, acquiring initial attitude information and initial load information of a heavy-load movable formwork robot formwork, secondly, comparing the initial attitude information with preset reference information, and calculating a current attitude error in combination with the initial load information; generating a cooperative leveling control instruction according to the current attitude error and the motion state of the heavy-load movable formwork robot, and finally driving a plurality of heavy-load lifting mechanisms of the heavy-load movable formwork robot to stretch out and draw back according to the cooperative leveling control instruction so as to eliminate the current attitude error. According to the technical scheme provided by the invention, the limitation that leveling decision is carried out only by depending on single attitude information in the prior art is overcome, and the fundamental problem of insufficient leveling precision caused by neglecting the load distribution influence is also solved.

Description

Technical Field

[0001] This application relates to the field of robot automation control technology, and in particular to a high-precision automatic leveling control method and system for a heavy-duty mobile template robot. Background Technology

[0002] In the construction of large-scale cast-in-place concrete structures, heavy-duty mobile formwork robots need to move and accurately position themselves on uneven construction sites while bearing tens of tons of formwork and concrete loads. This places extremely high demands on the leveling control of the formwork platform. It is necessary not only to quickly eliminate the initial tilt caused by uneven ground, but also to continuously maintain a high level of precision in the working plane of the formwork under dynamic working conditions such as robot movement, start-up, stop, and lifting operations, so as to ensure the quality of concrete forming and structural safety.

[0003] Currently, to achieve the above-mentioned leveling requirements, the technical solution adopted is an automatic leveling method based on a pre-programmed lifting sequence. This method first obtains the initial posture of the mold frame through a measurement system, and then drives multiple lifting mechanisms to perform extension and retraction actions in a fixed sequence and according to the preset leveling logic, thereby adjusting the mold frame to the target horizontal position. This solution realizes automated operation and reduces the reliance on human experience.

[0004] However, the existing solution has shortcomings in dealing with dynamic changes in actual construction. Because its leveling logic relies on a preset fixed program, it cannot adaptively adjust according to the robot's real-time motion state and the actual distribution of the load. Under heavy load conditions, the formwork structure itself may undergo slight deformation due to uneven stress, and the leveling action of the fixed program cannot sense and compensate for this structural deformation caused by the load, making it difficult to achieve the ideal leveling accuracy. Summary of the Invention

[0005] This application provides a high-precision automatic leveling control method and system for a heavy-duty mobile mold frame robot, which solves the problem of insufficient leveling accuracy under dynamic working conditions in the prior art, making it difficult to effectively adapt to the complex working state of heavy-duty mobile mold frame robots.

[0006] In a first aspect, this application provides a high-precision automatic leveling control method for a heavy-duty mobile mold frame robot, including: The tilt angle information of the heavy-duty mobile mold frame robot is obtained as the initial posture information, and the pressure information borne by the heavy-duty mobile mold frame robot at multiple independent support points is obtained as the initial load information. Based on the initial load information and the preset reference information, the load deviation of each independent support point is determined, the load difference characteristics are obtained based on the load deviation, and the current attitude error is calculated by combining the angle deviation and the load difference characteristics. The target adjustment amount of each heavy-duty lifting mechanism is determined based on the current attitude error to obtain the first leveling command sequence and the second leveling command sequence. Based on the first leveling command sequence and the second leveling command sequence, the action timing and extension amount of each heavy-duty lifting mechanism are arranged to generate a coordinated leveling control command. According to the coordinated leveling control command, during the extension and retraction of each heavy-duty lifting mechanism, the system monitors the changes in the posture and load information of the heavy-duty mobile module robot in real time. Based on the changes, the system adjusts the control of each heavy-duty lifting mechanism in real time to eliminate the current posture error.

[0007] Optionally, the tilt angle information of the heavy-duty mobile mold frame robot is obtained as initial posture information, and the pressure information borne by the heavy-duty mobile mold frame robot at multiple independent support points is obtained as initial load information, including: The tilt angle information of the mold frame during the movement of the heavy-duty mobile mold frame robot is collected in real time by the attitude sensor installed on the mold frame of the heavy-duty mobile mold frame robot to obtain the initial attitude information. During the process of the heavy-duty mobile formwork robot supporting the building formwork, load sensors installed at multiple independent support points of the heavy-duty mobile formwork robot synchronously collect the pressure information borne by each independent support point. The pressure information of each support point is integrated to generate initial load information.

[0008] Optionally, based on the initial load information and preset reference information, the load deviation of each independent support point is determined; based on the load deviation, a load difference feature is obtained; and by combining the angle deviation and the load difference feature, the current attitude error is calculated, including: The initial posture information is analyzed to obtain the tilt angle components of the mold frame in a first direction and a second direction that are perpendicular to each other. The tilt angle component in the first direction is compared with the corresponding first reference angle in the preset reference information to obtain the first angle deviation; The tilt angle component in the second direction is compared with the corresponding second reference angle in the preset reference information to obtain the second angle deviation; Based on the initial load information, identify the load difference between the actual load of each independent support point and the expected load corresponding to the preset benchmark information; Determine the load difference vector based on the load differences of all the independent support points; By combining the first angle deviation, the second angle deviation, and the load difference vector, the current posture error of the heavy-duty mobile frame robot is calculated.

[0009] Optionally, the current posture error of the heavy-duty mobile frame robot is calculated by combining the first angle deviation, the second angle deviation, and the load difference vector, including: The dynamic reference offset is determined based on the real-time motion state of the heavy-duty mobile mold robot. The dynamic reference offset is compensated to the first angle deviation and the second angle deviation respectively, to obtain the compensated first angle deviation and the compensated second angle deviation; The compensated first angle deviation and the compensated second angle deviation are combined to obtain the comprehensive angle deviation; The deformation error component is determined based on the projection of the load difference vector onto the plane of the mold frame; The current posture error of the heavy-duty mobile frame robot is obtained by superimposing the comprehensive angle deviation and the deformation error component.

[0010] Optionally, the target adjustment amount for each heavy-duty lifting mechanism is determined based on the current attitude error to obtain a first leveling command sequence and a second leveling command sequence. Based on the first and second leveling command sequences, the timing and extension / retraction of each heavy-duty lifting mechanism are arranged to generate coordinated leveling control commands, including: The current posture error is decomposed into target adjustment amounts corresponding to each heavy-duty lifting mechanism of the heavy-duty mobile scaffold robot; Identify whether the heavy-duty mobile template robot is in a moving state or a lifting operation state; When the state is identified as a moving state, the target adjustment amount of each heavy-duty lifting mechanism is dynamically corrected based on the moving direction and speed of the heavy-duty mobile frame robot to generate a first type of leveling instruction sequence, wherein the first type of leveling instruction sequence includes an advance adjustment amount for compensating for the inertia of movement. When the lifting operation is identified, the target adjustment amount of each heavy-duty lifting mechanism is corrected based on the load distribution reflected by the initial load information, and a second type of leveling instruction sequence is generated. The second type of leveling instruction sequence is used to coordinate the load relationship between each heavy-duty lifting mechanism. Based on the first type of leveling instruction sequence or the second type of leveling instruction sequence, the action timing and extension amount of each heavy-duty lifting mechanism are arranged to generate coordinated leveling control instructions.

[0011] Optionally, based on the first type of leveling instruction sequence or the second type of leveling instruction sequence, the timing and extension / retraction of the actions of each heavy-duty lifting mechanism are arranged to generate coordinated leveling control instructions, including: Based on the target adjustment amount of each heavy-duty lifting mechanism in the first type of leveling instruction sequence or the second type of leveling instruction sequence and the current extension and retraction state of each heavy-duty lifting mechanism, calculate the extension and retraction amount required for each heavy-duty lifting mechanism. Based on the structural layout of the heavy-duty mobile scaffold robot, the motion interference relationship between each heavy-duty lifting mechanism is determined; Based on the aforementioned action interference relationship, the action sequence of the heavy-duty lifting mechanisms that have interference is sorted, and the action timing is determined for all heavy-duty lifting mechanisms. Based on the telescoping amount and the timing of the actions determined for all heavy-duty lifting mechanisms, a coordinated leveling control command is generated.

[0012] Optionally, according to the coordinated leveling control command, during the extension and retraction of each heavy-duty lifting mechanism, the changes in the posture and load information of the heavy-duty mobile module robot are monitored in real time. Based on the changes, the control of each heavy-duty lifting mechanism is adjusted in real time to eliminate the current posture error, including: The coordinated leveling control command is analyzed to obtain the target extension and retraction amount and action timing of each heavy-duty lifting mechanism; According to the action sequence, drive signals are sent to each heavy-duty lifting mechanism in stages to control each heavy-duty lifting mechanism to start the telescopic action in sequence. During the extension and retraction movement of the heavy-duty lifting mechanism, the changes in the initial attitude information and the initial load information are monitored simultaneously. Based on the monitored changes, the residual amount of the current attitude error is calculated in real time. The driving signal being executed is adjusted based on the residual value until the residual value meets a preset threshold, thereby eliminating the current attitude error.

[0013] Secondly, this application provides a high-precision automatic leveling control system for a heavy-duty mobile mold frame robot, comprising: The acquisition module is used to acquire the tilt angle information of the heavy-duty mobile mold frame robot as initial posture information, and the pressure information borne by the heavy-duty mobile mold frame robot at multiple independent support points as initial load information. The calculation module is used to determine the load deviation of each independent support point based on the initial load information and the preset reference information, obtain the load difference characteristics based on the load deviation, and calculate the current attitude error by combining the angle deviation and the load difference characteristics. The generation module is used to determine the target adjustment amount of each heavy-duty lifting mechanism based on the current attitude error, so as to obtain a first leveling instruction sequence and a second leveling instruction sequence, and to arrange the action timing and extension amount of each heavy-duty lifting mechanism according to the first leveling instruction sequence and the second leveling instruction sequence, and generate a coordinated leveling control instruction. The drive module is used to control each heavy-duty lifting mechanism to monitor the changes in the posture and load information of the heavy-duty mobile frame robot in real time during the execution of the telescopic action according to the collaborative leveling control command. Based on the changes, the control of each heavy-duty lifting mechanism is adjusted in real time to eliminate the current posture error.

[0014] Thirdly, this application provides a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement a high-precision automatic leveling control method for a heavy-duty mobile scaffold robot as described in the first aspect above.

[0015] Fourthly, this application provides a computer storage medium storing a computer program, which, when executed by a computer, implements a high-precision automatic leveling control method for a heavy-duty mobile template robot as described in the first aspect.

[0016] This application overcomes the limitations of existing technologies that rely solely on single attitude information for leveling decisions by simultaneously acquiring the initial attitude information and initial load information of the mold frame and combining the two to calculate the current attitude error. In particular, by introducing a load difference vector to quantify the structural deformation of the mold frame caused by uneven load, the calculated attitude error can more realistically reflect the actual flatness of the mold frame's working plane. This directly solves the fundamental problem of insufficient leveling accuracy caused by ignoring the influence of load distribution.

[0017] Furthermore, based on the more accurate current posture error mentioned above, and combined with the robot's real-time motion state, collaborative leveling control commands are generated. This makes the leveling process no longer a simple, fixed program execution, but rather one with dynamic adaptability and intelligent decision-making capabilities. It can also adjust the control strategy in a targeted manner according to whether the robot is in a moving state or a lifting operation state, thereby effectively suppressing the interference of dynamic working conditions on the leveling process. This ensures that even during robot movement or load changes, the leveling system can quickly and stably converge to a high-precision level state.

[0018] These or other aspects of this application will become more apparent in the following description of the embodiments. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the 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 based on these drawings without creative effort.

[0020] Figure 1 A flowchart of a high-precision automatic leveling control method for a heavy-duty mobile template robot provided in this application is shown. Figure 2 This paper presents a schematic diagram of the structure of a high-precision automatic leveling control system for a heavy-duty mobile template robot provided in this application. Figure 3 A schematic diagram of the structure of a computing device provided in this application is shown. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present application, the technical solution of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0022] In some of the processes described in the specification, claims, and accompanying drawings of this application, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as 101, 102, etc., are merely used to distinguish different operations and do not themselves represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a chronological order, nor do they limit "first" and "second" to different types.

[0023] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and 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.

[0024] Figure 1 This application provides a flowchart of a high-precision automatic leveling control method for a heavy-duty mobile template robot, as shown below. Figure 1 As shown, the method includes: Step 101: Obtain the tilt angle information of the heavy-duty mobile mold frame robot as initial posture information, and the pressure information borne by the heavy-duty mobile mold frame robot at multiple independent support points as initial load information.

[0025] Optionally, step 101 may specifically include: Step 1011: The tilt angle information of the mold frame during the movement of the heavy-duty mobile mold frame robot is collected in real time by the attitude sensor installed on the mold frame of the heavy-duty mobile mold frame robot to obtain the initial attitude information.

[0026] Step 1012: During the process of the heavy-duty mobile formwork robot supporting the building formwork, load sensors installed at multiple independent support points of the heavy-duty mobile formwork robot synchronously collect the pressure information borne by each independent support point.

[0027] Step 1013: Integrate the pressure information of each support point to generate initial load information.

[0028] In this step, the heavy-duty mobile formwork robot refers to an automated device that can move and carry large building formwork on the construction site, used to support and precisely position the formwork during concrete pouring.

[0029] Initial attitude information refers to data reflecting the current tilt state of the robot mold frame, used to describe the angle between the mold frame plane and the horizontal plane, and is measured by attitude sensors installed on the mold frame.

[0030] Initial load information refers to data reflecting the current stress on each support point of the formwork, used to understand whether the load distribution is uniform, and is obtained by measuring load sensors installed on multiple independent support points.

[0031] The tilt angle information of the mold frame is specific data measured by the attitude sensor, which refers to the specific angle value of the mold frame tilting around two mutually perpendicular directions.

[0032] Construction formwork is a temporary formwork used to shape concrete structures.

[0033] Independent support points are the scattered points where the bottom of the robot mold base contacts the ground or structure and provides support.

[0034] A load sensor is a measuring device that converts pressure signals into electrical signals.

[0035] In this step, the dynamics of the mold frame are first monitored in real time by attitude sensors installed on the main body of the mold frame. When the robot moves or operates, the gyroscope inside the sensor continuously measures the angular velocity and the accelerometer measures the linear acceleration. These raw data are denoised and fused by the Kalman filter algorithm, and finally the tilt angle of the mold frame around the X-axis and Y-axis is calculated to form the initial attitude information.

[0036] Secondly, during the formwork support operation, load sensors distributed at six support points are simultaneously activated to collect data. Each sensor senses pressure deformation through strain gauges, generating a weak voltage signal. This signal is processed by an amplifier circuit and an analog-to-digital converter, calibrated into a precise pressure value, and transmitted to the central controller in real time.

[0037] Finally, the central controller integrates and processes the pressure data from the six support points, and uses data packaging technology to arrange the discrete pressure values ​​in a preset order to generate a structured data packet containing timestamps and point identifiers, forming complete initial load information.

[0038] For example, at a concrete slab construction site of a high-rise building, Company A uses a heavy-duty mobile formwork robot B for automated construction. As robot B moves to a predetermined position and prepares for leveling, the attitude sensor C integrated on its formwork begins to work. The measurement unit inside sensor C continuously detects the slight swaying and tilting of the formwork, and runs a fusion algorithm through its built-in processor to calculate and output the tilt angle of the formwork in the longitudinal and lateral directions in real time, such as a longitudinal tilt of 0.5 degrees and a lateral tilt of 0.3 degrees. This data constitutes the initial attitude information. At the same time, six strain gauge load sensors D fixed to the top of the six support legs of robot B also begin to collect data. Each sensor D senses the weight pressure from the formwork and concrete above on its support leg and transmits the pressure signal to the robot's main controller E in real time. The controller E receives and reads the pressure values ​​of these six channels almost at the same time, such as 120 kN, 115 kN, and 118 kN respectively. Then, it integrates these discrete pressure values ​​into a set containing six pressure data points to generate complete initial load information.

[0039] Step 102: Determine the load deviation of each independent support point based on the initial load information and the preset reference information, obtain the load difference characteristics based on the load deviation, and calculate the current attitude error by combining the angle deviation and the load difference characteristics.

[0040] Optionally, step 102 may specifically include: Step 1021: Analyze the initial posture information to obtain the tilt angle components of the mold frame in a first direction and a second direction that are perpendicular to each other.

[0041] Step 1022: Compare the tilt angle component in the first direction with the corresponding first reference angle in the preset reference information to obtain the first angle deviation.

[0042] Step 1023: Compare the tilt angle component in the second direction with the corresponding second reference angle in the preset reference information to obtain the second angle deviation.

[0043] Step 1024: Based on the initial load information, identify the load difference between the actual load of each independent support point and the expected load corresponding to the preset benchmark information.

[0044] Step 1025: Determine the load difference vector based on the load difference of all the independent support points.

[0045] Step 1026: Calculate the current posture error of the heavy-duty mobile frame robot by combining the first angle deviation, the second angle deviation, and the load difference vector.

[0046] Optionally, step 1026 may specifically include: Based on the real-time motion state of the heavy-duty mobile mold frame robot, a dynamic reference offset is determined; the dynamic reference offset is compensated to the first angle deviation and the second angle deviation respectively to obtain the compensated first angle deviation and the compensated second angle deviation; the compensated first angle deviation and the compensated second angle deviation are combined to obtain a comprehensive angle deviation; based on the projection of the load difference vector onto the plane of the mold frame, a deformation error component is determined; the comprehensive angle deviation and the deformation error component are superimposed to calculate the current posture error of the heavy-duty mobile mold frame robot.

[0047] In this step, the preset reference information refers to a set of standard reference data pre-stored in the system, which describes the angle and load distribution that the mold frame should have when it is in an ideal horizontal state.

[0048] Current attitude error is an indicator used to quantify the overall difference between the current actual state and the ideal state of the model, and is used to guide subsequent precise adjustments.

[0049] The tilt angle components in the first direction and the tilt angle components in the second direction refer to the specific tilt angle values ​​in two mutually perpendicular directions in space obtained by parsing the initial attitude information, such as the tilt angle in the forward and backward direction and the tilt angle in the left and right direction.

[0050] The first reference angle and the second reference angle are ideal angle reference values ​​corresponding to the first direction and the second direction, respectively, in the preset reference information, and are usually zero degrees.

[0051] The first angle deviation and the second angle deviation are the differences obtained by subtracting the actual measured tilt angle component from the corresponding reference angle, and are used to quantify the degree of tilt in a single direction.

[0052] Load difference refers to the difference between the actual load measurement value of each independent support point and the expected load value of that point set in the preset reference information.

[0053] The load difference vector is a mathematical vector whose direction and magnitude are determined by the load difference of all independent support points. It is used to comprehensively characterize the uneven load distribution of the entire formwork.

[0054] In this step, the initial attitude information is first parsed. By calling the coordinate transformation program, the initial attitude information measured by the attitude sensor is decomposed into two predefined, mutually perpendicular coordinate axes, such as the longitudinal axis and the transverse axis of the machine, thereby obtaining the tilt angle component in the first direction and the tilt angle component in the second direction.

[0055] Next, the first reference angle is read from the preset reference information. Then, by subtraction, the first reference angle is subtracted from the tilt angle component in the first direction to obtain the first angle deviation. Then, the same subtraction operation logic is used to subtract the second reference angle read from the preset reference information from the tilt angle component in the second direction to obtain the second angle deviation.

[0056] Simultaneously, based on the acquired initial load information, the expected load value corresponding to each independent support point is retrieved from the preset benchmark information. Then, the actual load measurement value of each point in the initial load information is subtracted from its corresponding expected load value to calculate the load difference of each support point.

[0057] Next, the load difference vector is calculated based on the load difference of all support points. The load difference of each support point and its position coordinates on the mold plane are used as input to calculate a comprehensive vector that can reflect the direction and magnitude of the unbalanced load distribution.

[0058] Then, based on the robot's real-time motion state parameters, a dynamic reference offset is determined. The dynamic reference offset is then added to the first angle deviation and the second angle deviation for compensation, resulting in the compensated first angle deviation and the compensated second angle deviation. Next, using a mathematical method of vector synthesis, such as the Pythagorean theorem, the two compensated angle deviations are combined into a comprehensive angle deviation. Simultaneously, the load difference vector is projected onto the mold plane, and the deformation error component is determined by calculating the magnitude of the projected vector. Finally, the comprehensive angle deviation is added to the deformation error component through addition to obtain the current posture error of the heavy-duty mobile mold robot.

[0059] For example, following the previous embodiment, after robot B of company A obtains the initial posture information and initial load information, the main controller E begins to perform error calculation. First, controller E parses the initial posture information from sensor C and separates the longitudinal tilt angle component as 0.5 degrees and the lateral tilt angle component as 0.3 degrees. Then, controller E reads the preset reference information, wherein the first reference angle and the second reference angle are both 0 degrees. Subsequently, the main controller E compares 0.5 degrees with 0 degrees to obtain a first angular deviation of positive 0.5 degrees; it compares 0.3 degrees with 0 degrees to obtain a second angular deviation of positive 0.3 degrees; at the same time, the controller E processes the initial load information, reads that the expected load of each support point in the preset is 120 kN, and then calculates the load difference using the actual measured value. For example, the difference for point 1 is 125 minus 120 equals 5 kN, and the difference for point 2 is 115 minus 120 equals negative 5 kN. Next, controller E determines the load difference vector through vector operation based on the load difference and position of all six support points. This load difference vector points to the side with larger load. Considering that robot B is currently in a low-speed movement state, controller E determines a small dynamic reference offset, such as 0.05 degrees, based on its motion state and compensates for the two previously calculated angle deviations. Then, controller E combines the two compensated angle deviations into a comprehensive angle deviation, and projects the load difference vector onto the mold plane to obtain the deformation error component. Finally, controller E adds the comprehensive angle deviation and the deformation error component to obtain the current attitude error value that fully reflects the actual unevenness of the mold.

[0060] Step 103: Determine the target adjustment amount of each heavy-duty lifting mechanism based on the current attitude error to obtain the first leveling command sequence and the second leveling command sequence. Based on the first leveling command sequence and the second leveling command sequence, arrange the action timing and extension amount of each heavy-duty lifting mechanism to generate a coordinated leveling control command.

[0061] Optionally, step 103 may specifically include: Step 1031: Decompose the current posture error into target adjustment amounts corresponding to each heavy-duty lifting mechanism of the heavy-duty mobile frame robot.

[0062] Step 1032: Identify whether the heavy-duty mobile template robot is in a moving state or a lifting operation state.

[0063] Step 1033: When the state is identified as moving, the target adjustment amount of each heavy-duty lifting mechanism is dynamically corrected based on the moving direction and speed of the heavy-duty mobile frame robot to generate a first type of leveling instruction sequence, wherein the first type of leveling instruction sequence includes an advance adjustment amount for compensating for the inertia of movement.

[0064] Step 1034: When the lifting operation state is identified, the target adjustment amount of each heavy-duty lifting mechanism is corrected based on the load distribution reflected by the initial load information, and a second type of leveling instruction sequence is generated. The second type of leveling instruction sequence is used to coordinate the load relationship between each heavy-duty lifting mechanism.

[0065] Step 1035: Based on the first type of leveling instruction sequence or the second type of leveling instruction sequence, arrange the action timing and extension amount of each heavy-duty lifting mechanism to generate a coordinated leveling control instruction.

[0066] Optionally, step 1035 may specifically include: Based on the target adjustment amount of each heavy-duty lifting mechanism in the first type of leveling instruction sequence or the second type of leveling instruction sequence and the current extension / retraction state of each heavy-duty lifting mechanism, the required extension / retraction amount of each heavy-duty lifting mechanism is calculated; according to the structural layout of the heavy-duty mobile scaffold robot, the motion interference relationship between each heavy-duty lifting mechanism is determined; based on the motion interference relationship, the motion sequence of the heavy-duty lifting mechanisms with interference is sorted, and the motion timing is determined for all heavy-duty lifting mechanisms; according to the extension / retraction amount and the motion timing determined for all heavy-duty lifting mechanisms, a collaborative leveling control instruction is generated.

[0067] In this step, the coordinated leveling control command refers to a set of commands used to coordinate and control the synchronous action of multiple heavy-duty lifting mechanisms, in order to achieve precise leveling of the formwork.

[0068] The target adjustment amount of the heavy-duty lifting mechanism refers to the specific adjustment value that is allocated to each lifting mechanism according to a specific rule based on the current attitude error, and is calculated through an error allocation algorithm.

[0069] The first type of leveling instruction sequence refers to the set of leveling instructions generated for the moving state, which includes advance compensation to counteract motion inertia.

[0070] The second type of leveling instruction sequence refers to the set of leveling instructions generated in response to the lifting operation status, which focuses on maintaining the load balance among the various lifting mechanisms.

[0071] The timing and extension / retraction of the heavy-duty lifting mechanism refer to the time sequence and specific extension / retraction length that control the start of each lifting mechanism's action, which are determined through motion planning algorithms.

[0072] The current extension and retraction status of the heavy-duty lifting mechanism is obtained in real time through displacement sensors.

[0073] Motion interference relationship refers to the mutual influence relationship that may occur between various lifting mechanisms during spatial movement, which is determined through kinematic analysis of the mechanisms.

[0074] In this step, the current attitude error is first decomposed through spatial coordinate mapping relationship, and a geometric correspondence model between the mold plane and the position of each lifting mechanism is established. At the same time, an error allocation algorithm is used to allocate the overall error proportionally to each heavy-duty lifting mechanism to generate the corresponding target adjustment amount. Secondly, the current working condition is determined by analyzing the robot's motion sensor data and actuator status. By monitoring parameters such as wheel speed and cylinder pressure, and using a state recognition algorithm, the robot can distinguish between the movement state and the lifting operation state. When the movement is detected, the dynamic compensation mechanism is activated. Based on the movement direction and speed parameters, the influence of motion inertia is calculated through the inertial prediction model. This influence is then added to the target adjustment of each lifting mechanism as an advance adjustment amount, generating the first type of leveling instruction sequence. When the lifting operation is identified, a load balancing strategy is executed. Based on the initial load information, the load distribution of each support point is analyzed, and the target adjustment amount of each lifting mechanism is redistributed through the load balancing algorithm to ensure smooth load transfer during the leveling process and generate a second type of leveling instruction sequence. Finally, the required extension amount is calculated based on the current extension state of the lifting mechanism and the target adjustment amount. Then, based on the mechanism layout, the motion interference relationship is analyzed, and the motion of the interfering mechanism is sorted using a collision avoidance algorithm. Finally, a collaborative leveling control command containing precise timing and extension amount is generated.

[0075] For example, following the previous embodiment, after the main controller E obtains the current attitude error value, the controller E first decomposes the error into the target adjustment amount of each of the six lifting mechanisms through the coordinate mapping model. For example, mechanism 1 needs to be extended by 10 mm and mechanism 2 needs to be shortened by 8 mm. At the same time, by monitoring the wheel speed sensor, it is found that robot B is moving forward at a speed of 5 m / min, and thus it is determined to be in a moving state. Based on this state, the controller E calls the inertial prediction model to calculate that an additional 2 mm of advance adjustment needs to be added to the front lifting mechanism to compensate for the inertial effect, and generates the first type of leveling instruction sequence. Next, controller E reads the current extension and retraction status of each lifting mechanism, calculates the precise extension and retraction amount in combination with the target adjustment amount, and analyzes and finds that mechanism 1 and mechanism 2 have motion interference. Therefore, the start time of their actions is staggered by 0.5 seconds, and finally generates a coordinated leveling control command that includes the action sequence and extension and retraction amount of all mechanisms.

[0076] Step 104: According to the coordinated leveling control command, control each heavy-duty lifting mechanism to monitor the changes in the posture and load information of the heavy-duty mobile module robot in real time during the extension and retraction action. Based on the changes, adjust the control of each heavy-duty lifting mechanism in real time to eliminate the current posture error.

[0077] Optionally, step 104 may specifically include: Step 1041: parse the coordinated leveling control command to obtain the target extension and retraction amount and action timing corresponding to each heavy-duty lifting mechanism.

[0078] Step 1042: According to the action sequence, drive signals are sent to each heavy-duty lifting mechanism in stages to control each heavy-duty lifting mechanism to start the telescopic action in sequence.

[0079] Step 1043: During the extension and retraction action of the heavy-duty lifting mechanism, the changes in the initial posture information and the initial load information are monitored simultaneously.

[0080] Step 1044: Based on the monitored change information, calculate the residual amount of the current attitude error in real time.

[0081] Step 1045: Adjust the driving signal being executed according to the residual amount until the residual amount meets the preset threshold, so as to complete the elimination of the current attitude error.

[0082] In this step, the drive signal refers to the current or voltage command sent by the control system to the electro-hydraulic proportional valve of the heavy-duty lifting mechanism, which is used to precisely control the extension and retraction speed and position of the hydraulic cylinder.

[0083] The changes in initial attitude information and initial load information refer to the real-time data sequence continuously collected by attitude sensors and load sensors during the leveling operation, reflecting the dynamic fluctuations of the mold frame angle and pressure at various points.

[0084] The residual amount of the current attitude error refers to the remaining error value that has not yet been eliminated, which is recalculated based on real-time monitoring data during the leveling process and is obtained through real-time iterative calculation.

[0085] In this step, the received collaborative leveling control command is first parsed by the command decoding module, and the target extension amount and the programmed action sequence for each heavy-duty lifting mechanism are extracted from the collaborative leveling control command. Secondly, based on the parsed action sequence, phased drive control is executed. According to the time nodes specified in the coordinated leveling control command, drive signals are sent to the electro-hydraulic servo drives of the corresponding heavy-duty lifting mechanisms in sequence, thereby driving each lifting mechanism to start its extension and retraction actions in a predetermined order. Immediately following the movement of the lifting mechanism, synchronous monitoring is initiated. The acquisition unit continuously reads the outputs of the attitude sensor and all load sensors at a high frequency to obtain a series of initial attitude information and initial load information that change continuously over time. Then, based on the monitored change information, a real-time error assessment is performed. The same error calculation logic as in step 102 is used, but the input data is replaced with the latest monitored real-time sensor data. The attitude error that still exists at this moment is quickly calculated, that is, the residual amount of the current attitude error. Finally, closed-loop correction is performed based on the calculated residual amount. The residual amount is compared with a preset threshold. If the residual amount is greater than the threshold, the intensity or direction of the output drive signal is dynamically adjusted through a proportional-integral control algorithm until the sensor feedback indicates that the residual amount continues to decrease and stabilizes within the preset threshold. At this point, it is determined that the current attitude error has been eliminated and the leveling process is completed.

[0086] For example, following the previous embodiment, the instruction is first parsed to determine that lifting mechanism 1 needs to extend by 12 mm and start at 0 seconds, and mechanism 2 needs to shorten by 8 mm and start at 0.5 seconds; then, controller E sends the corresponding drive current to the electro-hydraulic proportional valve of mechanism 1 at 0 seconds to make it start to extend; after 0.5 seconds, a drive signal is sent to mechanism 2. While the mechanism was in motion, controller E continuously read data from sensors C and D, detecting that the mold frame angle was slowly changing and the pressure at each point was being redistributed. Based on this real-time data, controller E quickly calculated the residual error and found that the rapid elongation of mechanism 1 had caused a new minor deviation. Therefore, it immediately fine-tuned the drive current output to mechanism 1 to slow down its elongation speed. After several such monitoring, calculations, and fine-tunings, when the sensor data indicated that the mold frame was completely level and the load at each point was balanced, and the residual error was below the threshold of 0.01 degrees, controller E stopped all drive signals, and the leveling operation was successfully completed.

[0087] Figure 2 This application provides a structural schematic diagram of a high-precision automatic leveling control system for a heavy-duty mobile mold frame robot, as shown below. Figure 2 As shown, the system includes: The acquisition module 21 is used to acquire the tilt angle information of the heavy-duty mobile mold frame robot as initial posture information, and the pressure information borne by the heavy-duty mobile mold frame robot at multiple independent support points as initial load information. The calculation module 22 is used to determine the load deviation of each independent support point based on the initial load information and the preset reference information, obtain the load difference feature based on the load deviation, and calculate the current attitude error by combining the angle deviation and the load difference feature. The generation module 23 is used to determine the target adjustment amount of each heavy-duty lifting mechanism based on the current attitude error, so as to obtain the first leveling instruction sequence and the second leveling instruction sequence, and to arrange the action timing and extension amount of each heavy-duty lifting mechanism according to the first leveling instruction sequence and the second leveling instruction sequence, and generate a coordinated leveling control instruction. The drive module 24 is used to control each heavy-duty lifting mechanism to monitor the changes in the posture and load information of the heavy-duty mobile frame robot in real time during the extension and retraction action according to the coordinated leveling control command, and to adjust the control of each heavy-duty lifting mechanism in real time according to the changes in the information to eliminate the current posture error.

[0088] Figure 2 The high-precision automatic leveling control system for a heavy-duty mobile mold frame robot can perform... Figure 1 The implementation principle and technical effects of the high-precision automatic leveling control method for a heavy-duty mobile mold frame robot described in the illustrated embodiment will not be repeated here. The specific operation methods of each module and unit in the high-precision automatic leveling control system for a heavy-duty mobile mold frame robot in the above embodiments have been described in detail in the embodiments related to this method, and will not be elaborated upon here.

[0089] In one possible design, Figure 2 The high-precision automatic leveling control system for a heavy-duty mobile template robot shown in the embodiment can be implemented as a computing device, such as... Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32; The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are invoked and executed by the processing component 32.

[0090] The processing component 32 is used for the above Figure 1 The embodiment describes a high-precision automatic leveling control method for a heavy-duty mobile template robot.

[0091] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above-described method. Alternatively, the processing component may be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described method.

[0092] Storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0093] Of course, computing devices may also include other components, such as input / output interfaces, display components, communication components, etc.

[0094] Input / output interfaces provide interfaces between processing components and peripheral interface modules, which can be output devices, input devices, etc.

[0095] The communication components are configured to facilitate wired or wireless communication between computing devices and other devices.

[0096] The computing device can be a physical device or an elastic computing host provided by a cloud computing platform. In this case, the computing device can refer to a cloud server, and the aforementioned processing components, storage components, etc., can be basic server resources rented or purchased from the cloud computing platform.

[0097] This application also provides a computer storage medium storing a computer program, which, when executed by a computer, can perform the above-described functions. Figure 1 The embodiment shown illustrates a high-precision automatic leveling control method for a heavy-duty mobile template robot.

[0098] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0099] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0100] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0101] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A high-precision automatic leveling control method for a heavy-duty mobile template robot, characterized in that, include: The tilt angle information of the heavy-duty mobile mold frame robot is obtained as the initial posture information, and the pressure information borne by the heavy-duty mobile mold frame robot at multiple independent support points is obtained as the initial load information. Based on the initial load information and the preset reference information, the load deviation of each independent support point is determined, the load difference characteristics are obtained based on the load deviation, and the current attitude error is calculated by combining the angle deviation and the load difference characteristics. The target adjustment amount of each heavy-duty lifting mechanism is determined based on the current attitude error to obtain the first leveling command sequence and the second leveling command sequence. Based on the first leveling command sequence and the second leveling command sequence, the action timing and extension amount of each heavy-duty lifting mechanism are arranged to generate a coordinated leveling control command. According to the coordinated leveling control command, during the extension and retraction of each heavy-duty lifting mechanism, the system monitors the changes in the posture and load information of the heavy-duty mobile module robot in real time. Based on the changes, the system adjusts the control of each heavy-duty lifting mechanism in real time to eliminate the current posture error.

2. The method according to claim 1, characterized in that, The tilt angle information of the heavy-duty mobile mold frame robot is obtained as initial posture information, and the pressure information borne by the heavy-duty mobile mold frame robot at multiple independent support points is obtained as initial load information, including: The tilt angle information of the mold frame during the movement of the heavy-duty mobile mold frame robot is collected in real time by the attitude sensor installed on the mold frame of the heavy-duty mobile mold frame robot to obtain the initial attitude information. During the process of the heavy-duty mobile formwork robot supporting the building formwork, load sensors installed at multiple independent support points of the heavy-duty mobile formwork robot synchronously collect the pressure information borne by each independent support point. The pressure information of each support point is integrated to generate initial load information.

3. The method according to claim 1, characterized in that, Based on the initial load information and preset reference information, the load deviation of each independent support point is determined. Based on the load deviation, a load difference characteristic is obtained. Combining the angle deviation and the load difference characteristic, the current attitude error is calculated, including: The initial posture information is analyzed to obtain the tilt angle components of the mold frame in a first direction and a second direction that are perpendicular to each other. The tilt angle component in the first direction is compared with the corresponding first reference angle in the preset reference information to obtain the first angle deviation; The tilt angle component in the second direction is compared with the corresponding second reference angle in the preset reference information to obtain the second angle deviation; Based on the initial load information, identify the load difference between the actual load of each independent support point and the expected load corresponding to the preset benchmark information; Determine the load difference vector based on the load differences of all the independent support points; By combining the first angle deviation, the second angle deviation, and the load difference vector, the current posture error of the heavy-duty mobile frame robot is calculated.

4. The method according to claim 3, characterized in that, Combining the first angle deviation, the second angle deviation, and the load difference vector, the current posture error of the heavy-duty mobile frame robot is calculated, including: The dynamic reference offset is determined based on the real-time motion state of the heavy-duty mobile mold robot. The dynamic reference offset is compensated to the first angle deviation and the second angle deviation respectively, to obtain the compensated first angle deviation and the compensated second angle deviation; The compensated first angle deviation and the compensated second angle deviation are combined to obtain the comprehensive angle deviation; The deformation error component is determined based on the projection of the load difference vector onto the plane of the mold frame; The current posture error of the heavy-duty mobile frame robot is obtained by superimposing the comprehensive angle deviation and the deformation error component.

5. The method according to claim 1, characterized in that, Based on the current attitude error, the target adjustment amount for each heavy-duty lifting mechanism is determined to obtain a first leveling command sequence and a second leveling command sequence. Then, based on the first and second leveling command sequences, the timing and extension / retraction of each heavy-duty lifting mechanism are arranged to generate coordinated leveling control commands, including: The current posture error is decomposed into target adjustment amounts corresponding to each heavy-duty lifting mechanism of the heavy-duty mobile scaffold robot; Identify whether the heavy-duty mobile template robot is in a moving state or a lifting operation state; When the state is identified as moving, the target adjustment amount of each heavy-duty lifting mechanism is dynamically corrected based on the moving direction and speed of the heavy-duty mobile frame robot to generate a first type of leveling instruction sequence, wherein the first type of leveling instruction sequence includes an advance adjustment amount for compensating for the inertia of movement. When the lifting operation is identified, the target adjustment amount of each heavy-duty lifting mechanism is corrected based on the load distribution reflected by the initial load information, and a second type of leveling instruction sequence is generated. The second type of leveling instruction sequence is used to coordinate the load relationship between each heavy-duty lifting mechanism. Based on the first type of leveling instruction sequence or the second type of leveling instruction sequence, the action timing and extension amount of each heavy-duty lifting mechanism are arranged to generate coordinated leveling control instructions.

6. The method according to claim 5, characterized in that, Based on either the first type of leveling instruction sequence or the second type of leveling instruction sequence, the timing and extension / retraction of each heavy-duty lifting mechanism are arranged to generate coordinated leveling control instructions, including: Based on the target adjustment amount of each heavy-duty lifting mechanism in the first type of leveling instruction sequence or the second type of leveling instruction sequence and the current extension and retraction state of each heavy-duty lifting mechanism, calculate the extension and retraction amount required for each heavy-duty lifting mechanism. Based on the structural layout of the heavy-duty mobile scaffold robot, the motion interference relationship between each heavy-duty lifting mechanism is determined; Based on the aforementioned action interference relationship, the action sequence of the heavy-duty lifting mechanisms that have interference is sorted, and the action timing is determined for all heavy-duty lifting mechanisms. Based on the telescoping amount and the timing of the actions determined for all heavy-duty lifting mechanisms, a coordinated leveling control command is generated.

7. The method according to claim 1, characterized in that, According to the coordinated leveling control command, during the extension and retraction of each heavy-duty lifting mechanism, the system monitors the changes in the posture and load information of the heavy-duty mobile module robot in real time. Based on these changes, the control of each heavy-duty lifting mechanism is adjusted in real time to eliminate the current posture error, including: The coordinated leveling control command is analyzed to obtain the target extension and retraction amount and action timing of each heavy-duty lifting mechanism; According to the action sequence, drive signals are sent to each heavy-duty lifting mechanism in stages to control each heavy-duty lifting mechanism to start the telescopic action in sequence. During the extension and retraction movement of the heavy-duty lifting mechanism, the changes in the initial attitude information and the initial load information are monitored simultaneously. Based on the monitored changes, the residual amount of the current attitude error is calculated in real time. The driving signal being executed is adjusted based on the residual value until the residual value meets a preset threshold, thereby eliminating the current attitude error.

8. A high-precision automatic leveling control system for a heavy-duty mobile template robot, characterized in that, include: The acquisition module is used to acquire the tilt angle information of the heavy-duty mobile mold frame robot as initial posture information, and the pressure information borne by the heavy-duty mobile mold frame robot at multiple independent support points as initial load information. The calculation module is used to determine the load deviation of each independent support point based on the initial load information and the preset reference information, obtain the load difference characteristics based on the load deviation, and calculate the current attitude error by combining the angle deviation and the load difference characteristics. The generation module is used to determine the target adjustment amount of each heavy-duty lifting mechanism based on the current attitude error, so as to obtain a first leveling instruction sequence and a second leveling instruction sequence, and to arrange the action timing and extension amount of each heavy-duty lifting mechanism according to the first leveling instruction sequence and the second leveling instruction sequence to generate a coordinated leveling control instruction. The drive module is used to control each heavy-duty lifting mechanism to monitor the changes in the posture and load information of the heavy-duty mobile frame robot in real time during the execution of the telescopic action according to the collaborative leveling control command. Based on the changes, the control of each heavy-duty lifting mechanism is adjusted in real time to eliminate the current posture error.

9. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement a high-precision automatic leveling control method for a heavy-duty mobile template robot as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, The system contains a computer program that, when executed by a computer, implements a high-precision automatic leveling control method for a heavy-duty mobile template robot as described in any one of claims 1 to 7.

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