Robot control method and device for industrial pipeline

Abstract

The invention relates to the technical field of robot control, and discloses a robot control method and device for an industrial pipeline, and the method comprises the steps: calculating a motion and posture coefficient based on a pitch angle, a roll angle, a motion speed and a motion acceleration of a robot; calculating an external force coefficient based on the cable dragging force and the operation counter-acting force; calculating a working condition attachment matching degree based on the instantaneous slip rate and the temperature under the motion and attitude coefficient and the external force coefficient; calculating a geometric coefficient of the pipeline based on the inner diameter, the bending radius and the inner local obstacle height of the pipeline; and based on the working condition attachment matching degree and the pipeline geometric coefficient, the target supporting arm pressing force is calculated, and the current supporting arm pressing force is adjusted to a target value. Through multi-source information fusion, the attachment state of the robot and the pipe wall and the geometric condition of the pipeline are dynamically evaluated, self-adaptive adjustment of the pressing force of the supporting arm is achieved, and the movement stability, passing ability and operation reliability of the robot in the complex pipeline environment are effectively improved.

Description

A robot control method and device for industrial pipelines Technical Field

[0001] This invention belongs to the field of robot control technology, and in particular relates to a robot control method and device for industrial pipelines. Background Technology

[0002] In the field of industrial pipeline inspection and maintenance, pipeline robots are widely used as core equipment for in-pipe flaw detection, cleaning, and repair operations in industries such as oil and gas, chemical, and nuclear power. Due to the characteristics of the pipeline environment, such as long distances, small spaces, numerous bends, and diameter changes, robots need to possess good adaptability to cope with complex pipe wall conditions. The clamping force of the support arm is a key parameter affecting the robot's walking stability, traction efficiency, and maneuverability: insufficient clamping force can easily cause the drive wheels to slip, causing the robot to lose power or even run away; excessive clamping force will increase walking resistance, exacerbate energy consumption and mechanical wear, and in severe cases, may damage the pipe wall coating or cause the robot to jam. Traditional control methods often use constant clamping force or simple feedback adjustment based on a single sensor (such as pressure or tilt angle), which is difficult to adapt to complex working conditions with multiple coupled parameters. Furthermore, in actual operations, robots often carry inspection probes or cleaning tools, and fluctuations in external loads further increase the difficulty of clamping force control. Therefore, there is an urgent need for an intelligent control method that can integrate multi-source information and adjust the support arm clamping force in real time to improve the environmental adaptability and operational reliability of pipeline robots. Summary of the Invention

[0003] The purpose of this invention is to provide a robot control method and apparatus for industrial pipelines, aiming to solve the above-mentioned problems.

[0004] This invention is implemented as follows: a robot control method for industrial pipelines includes the following steps: calculating motion and attitude coefficients based on the robot's pitch angle, roll angle, motion speed, and motion acceleration; calculating external force coefficients based on cable drag force and reaction force during operation; calculating the working condition adhesion matching degree based on the instantaneous slip rate and temperature under the motion and attitude coefficients and external force coefficients; calculating the pipeline geometry coefficients based on the pipeline's inner diameter, bending radius, and height of internal local obstacles; and calculating the target support arm clamping force based on the working condition adhesion matching degree and the pipeline geometry coefficients, and adjusting the current support arm clamping force to the target support arm clamping force.

[0005] A further technical solution involves calculating the adhesion matching degree under working conditions as follows: obtaining motion and attitude coefficients, external force coefficients, instantaneous slip ratio, and temperature; and taking the larger value between the motion and attitude coefficients and the external force coefficients as the requirement benchmark. Substitute the demand baseline and instantaneous slip ratio into the formula. Calculate and obtain the slip ratio matching degree , ,in, Instantaneous slip ratio For the ideal slip ratio, Use the demand baseline; substitute the demand baseline and temperature into the formula. Calculate and obtain temperature matching degree , ,in, For temperature, For optimal operating temperature, Operating temperature range Based on the demand baseline; the smaller value between the slip ratio matching degree and the temperature matching degree is taken as the working condition adhesion matching degree. , , When the slip ratio equals the ideal value and the temperature equals the optimal value, When the slip ratio or temperature approaches 0, it deviates significantly from the ideal value.

[0006] A further technical solution involves the following process for calculating and obtaining the motion and attitude coefficients: obtaining the robot's pitch angle, roll angle, motion speed, and motion acceleration; comparing the absolute values ​​of the robot's pitch angle and roll angle with the maximum permissible pitch angle and maximum permissible roll angle, respectively, to obtain the pitch angle index and roll angle index; comparing the absolute values ​​of the robot's motion speed and motion acceleration with the maximum speed and maximum acceleration absolute values, respectively, to obtain the motion speed index and motion acceleration index; and performing a weighted summation of the pitch angle index, roll angle index, motion speed index, and motion acceleration index to obtain the motion and attitude coefficients. The pitch angle index, roll angle index, motion speed index, and motion acceleration index are all positively correlated with the motion and attitude coefficients.

[0007] A further technical solution involves the following process for calculating and obtaining the external force coefficient: obtaining the cable drag force and the reaction force during operation, as well as the maximum cable drag force and the maximum operation reaction force; comparing the cable drag force and the reaction force during operation with the maximum cable drag force and the maximum operation reaction force, respectively, to obtain the cable drag force index and the reaction force index during operation; and taking the larger value between the cable drag force index and the reaction force index during operation as the external force coefficient. , Used to reflect the magnitude of externally applied resistance or reaction force. Indicates no external force. This indicates that at least one external force has reached its maximum value.

[0008] A further technical solution involves the following process for calculating and obtaining the pipe's geometric coefficients: Obtaining the pipe's inner diameter, bending radius, and height of any local obstruction; Ratioing the absolute value of the difference between the pipe's inner diameter and the optimal inner diameter to the maximum allowable inner diameter deviation, and then applying a min function with an upper limit of 1 to obtain the pipe's inner diameter deviation index; Ratioing the minimum allowable bending radius to the current pipe bending radius, and then applying a min function with an upper limit of 1 to obtain the bending radius index; Ratioing the current height of any local obstruction to the maximum allowable obstruction height, and then applying a min function with an upper limit of 1 to obtain the obstruction height index; Calculating the pipe's geometric coefficients based on the pipe's inner diameter deviation index, bending radius index, and obstruction height index. The pipe's geometric coefficients are positively correlated with each index, and when any index reaches its limit, the pipe's geometric coefficients approach 1; when all indices are zero, the pipe's geometric coefficients are zero.

[0009] A further technical solution is that the process of calculating and obtaining the clamping force of the target support arm is as follows: obtaining the working condition adhesion matching degree and the pipe geometry coefficient; calculating the target support arm clamping force based on the working condition adhesion matching degree, the pipe geometry coefficient, and the preset minimum and maximum values ​​of the support arm clamping force; wherein, the lower the working condition adhesion matching degree or the larger the pipe geometry coefficient, the closer the calculated target support arm clamping force is to the maximum value.

[0010] A robot control device for industrial pipelines includes: a memory for storing a computer program; and a processor for implementing the steps of the robot control method for industrial pipelines described above when executing the computer program.

[0011] Compared to existing technologies, the beneficial effects of this invention are as follows: 1. By constructing a multi-dimensional evaluation system encompassing motion and attitude coefficients, external force coefficients, working condition adhesion matching degree, and pipeline geometry coefficients, a comprehensive perception and dynamic fusion of the robot's own state, external disturbances, adhesion performance, and pipeline environment is achieved. Under complex working conditions, the support arm clamping force can be adjusted in real time according to changes in the adhesion state, effectively preventing drive wheel slippage, rollback, or jamming, and significantly improving the robot's passability and motion stability in complex pipeline environments such as curves, diameter changes, and obstacles.

[0012] 2. The target clamping force is calculated using a weighted combination of the adhesion matching degree under working conditions and the pipeline geometry coefficient. When the adhesion is good and the pipeline conditions are simple, the clamping force is automatically reduced to avoid unnecessary energy consumption and mechanical wear. When the adhesion deteriorates or the pipeline conditions become complex, the clamping force is promptly increased to maintain reliable adhesion. This adaptive adjustment strategy not only optimizes the robot's energy consumption performance but also extends the service life of the drive mechanism and the pipeline.

[0013] 3. By introducing a demand benchmark to dynamically weight slip ratio and temperature deviation, the assessment of adhesion status becomes more sensitive under high-demand conditions, enabling earlier identification of potential risks and the implementation of preventative adjustment measures. The modular implementation embeds the control methods into the hardware platform, ensuring real-time response and stable operation, significantly improving the reliability and safety of robots operating within pipelines of critical infrastructure such as nuclear power plants and chemical plants. Attached Figure Description

[0014] Figure 1 is a flowchart of a robot control method for industrial pipelines provided by the present invention. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0016] In the field of industrial pipeline inspection and maintenance, pipeline robots need to adapt to internal environmental conditions characterized by long distances, confined spaces, numerous bends, and changes in pipe diameter. An industrial pipeline robot is an automated device specifically designed for inspection, maintenance, or repair work inside industrial pipelines. It typically moves along the pipe wall via drive wheels or tracks, utilizing support arms to provide the necessary clamping force to ensure stable adhesion and traction. The control of the support arm's clamping force directly determines the robot's walking stability, traction efficiency, and maneuverability. Insufficient clamping force reduces the adhesion between the drive wheels and the pipe wall, causing slippage, interrupting power transmission, or causing the robot to roll away; excessive clamping force increases walking resistance, leading to increased energy consumption and accelerated mechanical wear, while also damaging the pipe wall coating or causing jamming. Traditional control methods, employing constant clamping force or feedback adjustment mechanisms based on a single sensor, cannot effectively handle dynamic changes in operating conditions involving multiple parameters. Especially when the robot carries inspection probes or cleaning tools, external load fluctuations further deteriorate the accuracy of clamping force control, affecting the stability of key performance indicators.

[0017] For example, when performing internal wall cleaning tasks in the bends of chemical pipeline systems, robots need to overcome the posture changes caused by the pipe bends. When the robot moves to an area with a small bend radius, the pitch and roll angles change, the cable drag force increases due to the resistance of the bend, and the reaction force generated by the contact between the cleaning tool and the pipe wall fluctuates. In this scenario, the instantaneous slip ratio fluctuates due to unstable adhesion, and the surface temperature of the drive wheels rises due to the accumulation of frictional heat. Traditional control methods fail to simultaneously process the comprehensive information of posture, motion state, and external forces, resulting in a lag in the adjustment of the support arm clamping force, manifested as drive wheel slippage or over-clamping, affecting the continuity of the cleaning operation and the overall performance of the system.

[0018] If these issues are not addressed, the reliability of robots operating in complex pipeline networks will decrease, and slippage or jamming events will disrupt inspection or maintenance processes. Abnormal wear of mechanical components will shorten equipment lifespan and increase maintenance burden. In pipeline inspections of critical infrastructure such as nuclear power plants, failure to control clamping force may cause robots to stall in dangerous areas, posing safety hazards and affecting the safe operation of the system.

[0019] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0020] Figure 1 illustrates a robot control method for industrial pipelines according to an embodiment of the present invention, comprising the following steps: calculating motion and attitude coefficients based on the robot's pitch angle, roll angle, motion speed, and motion acceleration; these motion and attitude coefficients are used to quantify the intensity of the robot's current motion and the degree of tilt in its posture. Their values ​​are typically within a certain range; higher values ​​indicate that the robot is in a more intense or tilted motion state, which may place higher demands on adhesion stability.

[0021] The external force coefficient is calculated based on the cable drag force and the reaction force during operation. The external force coefficient is used to comprehensively reflect the magnitude of the external resistance or reaction force exerted on the robot. Its value is usually within a certain range. A higher value indicates that the robot is subjected to a larger external load, which may require a larger support arm clamping force to overcome.

[0022] Based on the instantaneous slip ratio (the instantaneous slip ratio between the robot's drive wheel / track and the pipe wall) and temperature (the surface temperature of the robot's drive wheel / track) under motion and attitude coefficients and external force coefficients, the working condition adhesion matching degree is calculated. The working condition adhesion matching degree is used to evaluate the quality of the adhesion between the robot's drive wheel or track and the inner wall of the pipe under comprehensive working conditions such as current motion, external load, slip ratio, and temperature. A higher matching degree indicates a good adhesion state, while a lower matching degree indicates a poor adhesion state and a potential risk of slippage.

[0023] Based on the pipe's inner diameter, bending radius, and the height of local obstacles, the pipe's geometric coefficients are calculated. These coefficients quantify the degree to which the pipe's geometry hinders the robot's movement. Their values ​​typically fall within a certain range; higher values ​​indicate greater resistance to robot movement due to factors such as pipe bends, diameter changes, or the presence of obstacles.

[0024] Based on the adhesion matching degree under operating conditions and the pipe geometry, the target support arm clamping force is calculated and obtained, and the current support arm clamping force is adjusted to the target support arm clamping force. The target support arm clamping force refers to the ideal clamping force calculated based on the current operating conditions and pipe geometry, which can ensure stable robot adhesion and efficient movement. The current support arm clamping force refers to the actual clamping force applied by the robot support arm to the pipe wall. By adjusting the current support arm clamping force to the target support arm clamping force, dynamic optimization control of the robot's adhesion state can be achieved.

[0025] This embodiment constructs a multi-dimensional and comprehensive evaluation system by introducing motion and attitude coefficients, external force coefficients, working condition adhesion matching degree, and pipe geometry coefficients. This system can perceive the robot's dynamic environment and its own state in real time and comprehensively. For example, when the robot accelerates through a sharp bend, the increase in motion and attitude coefficients can promptly reflect changes in the robot's posture and motion, while the external force coefficients can capture the influence of cable dragging force or operational reaction force. This information, together with instantaneous slip ratio and temperature, accurately calculates the working condition adhesion matching degree, thereby quantifying the actual adhesion state between the robot and the pipe wall. Simultaneously, the introduction of pipe geometry coefficients allows the control system to pre-assess the potential obstruction of pipe structures (such as bends and obstacles) to the robot's movement.

[0026] Compared to existing technologies, the key innovation of this embodiment lies in its fusion of multi-source information—instead of relying on a single parameter or static settings—to dynamically calculate the clamping force of the target support arm. This fusion decision-making mechanism allows the clamping force adjustment to adapt to different working conditions. For example, when the adhesion matching degree decreases (indicating poor adhesion) or the pipeline geometry increases (indicating a challenging pipeline environment), the system can increase the clamping force to restore or enhance adhesion, effectively avoiding the risk of slippage or jamming. In areas with good adhesion and simple pipeline conditions, the system can reduce the clamping force, thereby reducing energy consumption and mechanical wear. This clamping force control strategy improves the walking stability, traction efficiency, and maneuverability of the pipeline robot in complex industrial pipeline environments, solving the technical problems of poor adaptability and insufficient reliability of traditional methods under multi-parameter coupled working conditions.

[0027] This application further proposes a process for calculating and obtaining motion and attitude coefficients as follows: acquiring the robot's pitch angle, roll angle, motion velocity, and motion acceleration; the pitch angle and roll angle reflect the degree of robot's attitude tilt within the pipe, while the motion velocity and motion acceleration characterize the intensity of the robot's dynamic motion. These data can be acquired in various ways. For example, they can be measured in real time using an inertial measurement unit (IMU) mounted on the robot body. This IMU typically includes a gyroscope and accelerometer, providing high-precision attitude and motion information. Alternatively, they can be calculated using encoder data from the robot's drive wheels combined with a kinematic model to obtain their linear and angular velocities, thereby deriving acceleration and attitude changes.

[0028] The absolute values ​​of the robot's pitch and roll angles are compared with the maximum permissible pitch and roll angles, respectively, to obtain the pitch and roll exponents. This step aims to convert the robot's actual attitude values ​​into dimensionless exponents to reflect the degree of deviation of the current attitude from its limit attitude. By taking the absolute values, it is ensured that the impact on adhesion is quantified as a positive value regardless of the tilt direction.

[0029] The robot's motion speed and absolute acceleration are compared with the maximum speed and absolute acceleration, respectively, to obtain the motion speed index and motion acceleration index. This step converts the robot's actual motion speed and acceleration into dimensionless exponents to reflect the degree of deviation of the current motion intensity from its limit value. Taking absolute values ​​is to uniformly consider the impact of acceleration and deceleration, and forward and reverse motion on adhesion.

[0030] Maximum permissible pitch angle, maximum permissible roll angle, maximum speed, and maximum acceleration represent the extreme motion and attitude values ​​that a robot can withstand under design or safe operating specifications. These are the benchmarks for normalization. These extreme values ​​are usually pre-set and stored in the controller's parameter table during the robot system design phase based on its structural strength, stability, driving capability, and pipeline environment characteristics; alternatively, they can be determined through a series of extreme tests and experimental calibrations in a controlled environment.

[0031] The pitch, roll, velocity, and acceleration indices are weighted and summed to obtain the motion and attitude coefficients. All three indices are positively correlated with these coefficients. Specifically, the pitch, roll, velocity, and acceleration indices are substituted into the formula... Calculate and obtain motion and attitude coefficients , This step combines the individual attitude and motion indices into a single motion and attitude coefficient through a weighted summation method. This linear combination method can comprehensively and quantitatively reflect the overall intensity of the robot's current motion and the overall tilt of its posture. Indicates horizontal stationary or uniform linear motion. This indicates the extreme operating conditions (maximum pitch, maximum roll, maximum speed, maximum acceleration), where, , , and All are motion and attitude weights with values ​​ranging from 0 to 1, and , , , and This is used to quantify the impact of different motion posture factors on the robot's adhesion requirements. For example, under certain working conditions, tilt may have a greater impact on adhesion than speed changes. In this case, pitch and roll angles can be given higher weights, which can be initially set based on empirical values. Alternatively, extensive experimental data analysis can be conducted on different pipeline environments and robot tasks, and offline training and adjustments can be performed using optimization algorithms (such as genetic algorithms, particle swarm optimization, etc.). Or, online adaptive adjustments can be made during robot operation based on real-time feedback (such as slip ratio, energy consumption, etc.). The pitch angle index, This is the roll angle index. The velocity index is the speed index. The acceleration index is the velocity index.

[0032] The solution in this application acquires the robot's kinematic parameters such as pitch angle, roll angle, motion speed, and motion acceleration in real time, and combines these with preset maximum allowable values ​​and motion and attitude weights to perform refined ratio processing and weighted summation, thereby calculating the motion and attitude coefficients. This coefficient It is a comprehensive indicator with a value between 0 and 1, which can comprehensively and quantitatively reflect the overall intensity of the robot's current movement and the overall tilt of its posture. When When the value is 0, it indicates that the robot is in an ideal state of horizontal stillness or uniform linear motion; when... A value of 1 indicates that the robot is in its extreme operating conditions, encompassing maximum pitch, maximum roll, maximum speed, and maximum acceleration. Through this refined calculation method, motion and attitude coefficients... It can accurately capture the potential adhesion requirements caused by the robot's dynamic changes and serve as a key input for subsequent calculations of adhesion matching under different working conditions. This is especially important when the robot is undergoing violent movement or significant tilting. The value will increase accordingly, which will require a higher baseline when calculating the adhesion matching degree under operating conditions. (Taking the larger value among the motion and attitude coefficient and the external force coefficient) increases accordingly, thus imposing a heavier "penalty" on deviations in instantaneous slip ratio and temperature, leading to a decrease in the adhesion matching degree under operating conditions. The reduced matching degree prompts the system to calculate a higher target support arm clamping force, thereby increasing the clamping force of the support arm in a timely manner to cope with the problem of insufficient adhesion that may occur under highly dynamic working conditions, effectively preventing the robot from slipping or becoming unstable, and ensuring its stable and reliable operation in complex pipeline environments.

[0033] The following is a concrete example. Assume an industrial pipeline robot is performing an inspection operation inside a pipeline. It is equipped with a high-precision inertial measurement unit (IMU) and drive wheel encoders. At a certain moment, the IMU detects that the robot's pitch angle is 10 degrees and its roll angle is 5 degrees. The encoder data, combined with the kinematic model, calculates the robot's absolute velocity as 0.4 m / s and its absolute acceleration as 0.2 m / s². Simultaneously, the robot's control system is preset with a maximum permissible pitch angle of 30 degrees, a maximum permissible roll angle of 15 degrees, a maximum velocity of 1 m / s, and a maximum acceleration of 0.5 m / s². The motion and attitude weights are set offline after optimization as follows: It is 0.3. It is 0.2. It is 0.3. It is 0.2.

[0034] First, calculate the various indices: pitch index Approximately 0.333; Roll angle index Approximately 0.333; Motion speed index The acceleration index is 0.4; The value is 0.4; then, these exponents are substituted into the formula to calculate the motion and attitude coefficients. The value is 0.3665; this value will serve as an important input for subsequent calculations of the adhesion matching degree under working conditions, guiding the adjustment of the support arm clamping force.

[0035] Through the above technical solution, this application can precisely quantify the robot's pitch angle, roll angle, motion speed, and motion acceleration, and comprehensively calculate the motion and attitude coefficients by combining preset limit parameters and weights. This detailed and comprehensive calculation method overcomes the potential coarseness or inaccuracy in the dynamic state assessment of robots in traditional methods, enabling the motion and attitude coefficients to more accurately reflect the robot's true motion intensity and attitude tilt. Therefore, when calculating the adhesion matching degree under subsequent working conditions, it can more accurately assess the robot's actual adhesion requirements, thereby guiding more reasonable and timely adjustment of the support arm clamping force. This not only helps to effectively prevent slippage and instability by timely increasing the clamping force when the robot faces high-dynamic working conditions such as climbing, turning, and acceleration, ensuring the reliability and safety of robot operation; but also avoids unnecessary over-clamping under low-dynamic working conditions, thereby reducing energy consumption, extending the service life of the robot drive mechanism and battery, and improving overall operating efficiency.

[0036] This application further proposes a process for calculating and obtaining external force coefficients as follows: The cable drag force and the reaction force during operation are obtained. The cable drag force refers to the resistance force exerted on the robot by the cable connecting the robot body due to friction with the inner wall of the pipe or its own weight when the robot moves within the pipe. This force directly acts on the robot, affecting the adhesion between its drive wheels or tracks and the pipe wall. The cable drag force can be measured in real time using a force sensor installed at the connection between the robot body and the cable, or estimated by modeling the physical characteristics of the cable (such as length, diameter, material, and bending stiffness) and the robot's motion state (such as speed and acceleration). The reaction force during operation refers to the interaction force generated between the robot's working tool and the inner wall of the pipe, obstacles, or other work objects when the robot performs a specific task (such as inspection, cleaning, welding, or repair) within the pipe. This reaction force directly affects the robot's motion stability and imposes additional requirements on its adhesion. The reaction force during operation can be accurately measured by integrating a force sensor into the working tool or its connecting mechanism, or estimated empirically based on the type of work, tool design parameters, and the material properties of the work object.

[0037] The cable drag force and the reaction force during operation are compared with the maximum cable drag force and the maximum working reaction force, respectively, to obtain the cable drag force index and the working reaction force index. The maximum cable drag force is a pre-set upper limit determined during the robot design or testing phase, representing the maximum resistance that may be encountered under the most severe cable working conditions. The maximum working reaction force is a pre-set maximum reaction force that the robot may encounter when performing a specific task. These maximum values ​​serve as the benchmark for normalization and can be determined through extensive experimental testing, simulation analysis, or empirical data based on robot design specifications and application scenarios. The purpose of this step is to uniformly convert external forces from different sources and with different dimensions into dimensionless indices. This ratio processing maps the actual measured force values ​​to a standardized range of 0 to 1, allowing different types of external forces to be compared and comprehensively evaluated on the same scale, thus intuitively reflecting the proportion of the current external force to its maximum possible value. The cable drag force index and the reaction force index during operation are quantitative indicators obtained by ratio processing. They represent the degree of influence of the current cable drag force and the reaction force during operation on the robot's adhesion requirements, respectively. When these indices are close to 0, it indicates that the corresponding external force is very small, and the adhesion requirement is low; when the indices are close to 1, it indicates that the external force is close to its maximum allowable value, and the adhesion requirement is high. These indices provide standardized input for subsequent calculations of the external force coefficient.

[0038] The larger of the cable drag force index and the reaction force index during operation is taken as the external force coefficient. This approach aims to ensure that the external force coefficient accurately reflects the external load that has the most significant impact on the robot's adhesion requirements under the current operating conditions. In actual operation, the robot may be affected by both cable drag force and operational reaction force, but usually one of these forces poses the main challenge to the robot's stability and adhesion. Choosing a larger value ensures that the most severe external load conditions are fully considered when calculating the adhesion matching degree, thereby avoiding the risk of insufficient adhesion due to underestimating external forces. Indicates no external force. This indicates that at least one external force has reached its maximum value.

[0039] This application's solution standardizes these external forces by acquiring the cable drag force and the reaction force during operation, and combining them with preset maximum cable drag force and maximum operational reaction force. Specifically, the real-time acquired cable drag force is compared with the maximum cable drag force to obtain a cable drag force index; simultaneously, the operational reaction force is compared with the maximum operational reaction force to obtain an operational reaction force index. This ratioing process quantifies external forces from different sources and of different magnitudes into dimensionless indices between 0 and 1, allowing them to be compared within the same framework. Subsequently, by comparing these two indices, the larger one is taken as the external force coefficient $$C_{ext}$$. This selection mechanism ensures that the external force coefficient accurately captures the external load that has the most significant impact on the robot's adhesion requirements under the current working conditions. Through the above process, this application can provide a quantified and representative external force coefficient $$C_{ext}$$. This coefficient directly reflects the magnitude of the externally applied resistance or reaction force; the higher the value, the greater the external load on the robot and the higher the adhesion requirement. This precisely calculated external force coefficient Introduced into the calculation of adhesion matching degree under operating conditions, as a demand benchmark. This is part of the process, enabling a more comprehensive and accurate assessment of the actual adhesion state between the robot and the pipe wall. This avoids problems such as insufficient adhesion or excessive clamping caused by inaccurate assessment of external forces, thus providing a more reliable basis for adjusting the clamping force of the target support arm in the future.

[0040] The following example illustrates this. Suppose an industrial pipeline robot is performing internal inspection on a horizontal pipe. During the inspection, the robot uses its integrated force sensor to monitor a cable drag force of 40 Newtons in real time. Simultaneously, due to the slight contact between the detection probe and the inner wall of the pipe, a reaction force of 15 Newtons is generated. Based on the robot's design parameters and application scenario, the system's preset maximum cable drag force is 80 Newtons, and the maximum reaction force is 30 Newtons. First, the cable drag force index is calculated: the ratio of the current cable drag force of 40 Newtons to the maximum cable drag force of 80 Newtons yields a cable drag force index of 0.5. Next, the reaction force index is calculated: the ratio of the current reaction force of 15 Newtons to the maximum reaction force of 30 Newtons yields a reaction force index of 0.5. Finally, the cable drag force index of 0.5 and the reaction force index of 0.5 are compared, and the larger value, 0.5, is taken as the external force coefficient. The calculated external force coefficient of 0.5 will be used as an input parameter for subsequent calculations of the adhesion matching degree under different working conditions, reflecting the degree of influence of the current external load on the robot's adhesion requirements.

[0041] Through the above technical solution, this application can accurately quantify the external loads borne by the robot, including cable dragging force and reaction force during operation. By standardizing these external forces into an exponent and taking the larger value as the external force coefficient, it ensures that the most stringent external working conditions can be fully considered when assessing the robot's adhesion requirements. This makes the subsequent calculation of the working condition adhesion matching degree more accurate, thus providing a more reliable and precise basis for adjusting the clamping force of the target support arm, effectively avoiding insufficient adhesion or excessive clamping caused by inaccurate assessment of external forces, and improving the robot's motion stability and operating efficiency in complex industrial pipeline environments.

[0042] This application further proposes a process for calculating and obtaining the working condition adhesion matching degree as follows: acquiring motion and attitude coefficients, external force coefficients, instantaneous slip ratio, and temperature; the motion and attitude coefficients reflect the intensity of the robot's current motion and the tilt of its posture. These coefficients can be obtained by real-time acquisition of the robot's pitch angle, roll angle, motion speed, and motion acceleration using sensors, combined with preset maximum allowable values ​​for normalization calculation, or by using a lookup table method to obtain the coefficients based on preset coefficient matrices for different motion posture combinations. The external force coefficients characterize the magnitude of the external resistance or reaction force experienced by the robot during operation. These coefficients can be obtained by real-time measurement of cable drag force and reaction force during operation using force sensors, compared with preset maximum values, or by analyzing historical data to establish a mapping relationship between external forces and the robot's operating state. Instantaneous slip ratio refers to the ratio of the instantaneous relative sliding speed between the robot's drive wheel / track and the pipe wall to the linear velocity of the drive wheel / track. It can be obtained by measuring the rotational speed of the drive wheel / track with an encoder, and measuring the robot's actual movement speed with a vision sensor or inertial measurement unit (IMU), then calculating the difference between the two and the ratio to the linear velocity of the drive wheel / track. Alternatively, it can be measured directly by a slip sensor mounted on the drive wheel / track. Temperature refers to the temperature of the contact area between the robot's drive wheel / track surface and the pipe wall. It can be obtained by measuring the temperature of the drive wheel / track surface in real time using an infrared temperature sensor or a contact temperature sensor, or by performing multi-point measurements of the contact area using a thermocouple array.

[0043] The larger value among the motion and attitude coefficients and the external force coefficients is taken as the demand benchmark. This step aims to determine a baseline value representing the "demand" of the current operating condition by comprehensively considering the robot's current level of motion and external load requirements. By taking a larger value, it ensures that the higher requirements for adhesion performance are reflected under any high demand conditions (whether it is intense motion or large external load). This helps to impose a heavier "penalty" on deviations in slip ratio and temperature in subsequent calculations, thereby prompting the system to more actively adjust the clamping force to maintain adhesion.

[0044] Substituting the demand baseline and instantaneous slip ratio into the formula Calculate and obtain the slip ratio matching degree , This step quantifies the degree of matching between the robot's drive wheels / tracks and the pipe wall in terms of slip ratio. The formula uses an exponential decay form, where the instantaneous slip ratio... Deviation from ideal slip ratio At that time, matching degree It will decrease. The existence of a (demand baseline) means that even with the same slip ratio deviation, a lower fit will result when demand is high, thus more sensitively reflecting the deterioration of the adhesion state. This helps the system identify potential adhesion problems earlier under critical operating conditions. Instantaneous slip ratio For the ideal slip ratio, The ideal slip ratio refers to the small slip ratio that is allowed between the robot drive wheel / track and the pipe wall under the optimal adhesion state. It can be obtained by experimentally testing the optimal adhesion performance under different materials and pressures, or by theoretical calculation based on the tribological properties of the drive wheel / track material.

[0045] Substitute the demand baseline and temperature into the formula Calculate and obtain temperature matching degree , This step quantifies the degree of temperature matching between the robot's drive wheels and tracks. Similar to the slip ratio matching, this formula also uses an exponential decay form, where the temperature... Deviation from optimal operating temperature At that time, matching degree It will decrease. Operating temperature range. Used to normalize temperature deviations, while (Demand baseline) also plays a moderating role here, making the impact of temperature deviation on fit more significant when demand is high. This ensures that the impact of temperature on adhesion performance is fully considered under harsh operating conditions. Among these, For temperature, For optimal operating temperature, This refers to the operating temperature range (i.e., the maximum absolute value of the difference between the minimum and optimal operating temperatures and the maximum absolute value of the difference between the maximum and optimal operating temperatures). The optimal operating temperature refers to the temperature at which the robot drive wheel / track material provides the best adhesion performance. This temperature can be obtained by determining the temperature point with the maximum friction coefficient or minimum wear through material performance testing. The operating temperature range refers to the temperature range within which the robot drive wheel / track material maintains acceptable adhesion performance. This temperature range can be obtained by determining the friction coefficient variation curve of the material at different temperatures through thermal performance testing of the material.

[0046] The smaller value between slip ratio matching degree and temperature matching degree is taken as the working condition adhesion matching degree. This step aims to utilize the "weakest link" principle, meaning that the robot's overall adhesion performance is limited by its worst single factor. This is achieved by taking the slip ratio matching degree... Temperature matching The smaller value in the range ensures that if any factor (slip ratio or temperature) deviates significantly from the ideal state, the overall working condition adhesion matching degree will be affected. This will be pulled down. This allows the system to identify and respond to any critical factors that could lead to adhesion failure, thus providing a conservative and safe assessment of the adhesion status. , When the slip ratio equals the ideal value and the temperature equals the optimal value, the robot is in a perfect match, regardless of the demand size (deviation is zero). When the slip ratio or temperature deviates significantly from the ideal value when it approaches 0, and the greater the demand, the heavier the penalty for deviation, resulting in extremely low matching degree, it indicates that the current adhesion state is very poor and the clamping force needs to be adjusted urgently. The median value reflects the degree of adhesion matching between the robot and the pipe wall under the current working conditions, and can be used as a basis for subsequent clamping force adjustment (for example, when the matching degree is high, the clamping force can be appropriately reduced to save energy, and when the matching degree is low, the clamping force needs to be increased to restore adhesion).

[0047] The solution proposed in this application obtains key parameters such as the robot's motion and attitude coefficients, external force coefficients, instantaneous slip rate, and temperature, and introduces a requirement benchmark. To dynamically adjust the slip ratio matching degree Temperature matching The calculation weights. Specifically, when the robot's movement intensity or external load requirements are high, the demand baseline... This will increase accordingly, meaning that even small deviations in slip ratio or temperature will lead to a significant decrease in the matching degree. Conversely, under low-demand operating conditions, the system has a higher tolerance for these deviations. Ultimately, the matching degree is determined by taking the slip ratio. Temperature matching The smaller value in the equation is used as the adhesion matching degree under working conditions. This ensures that the assessment of adhesion status is always based on the most unfavorable factors. This comprehensive and dynamic assessment mechanism improves the adhesion matching degree under operating conditions. It can more accurately reflect the true adhesion state between the robot's drive wheels / tracks and the pipe wall, especially in complex and variable industrial pipeline environments. This precise adhesion state assessment provides a reliable basis for subsequent calculation of the target support arm's clamping force, thereby enabling more intelligent and precise clamping force adjustment and effectively avoiding problems such as insufficient adhesion or excessive clamping that may occur under different working conditions.

[0048] The following is a concrete example. Suppose a robot is performing inspection work in an industrial pipeline. The robot's control unit continuously collects various data. For example, motion and attitude coefficients can be calculated from data from the robot's internal inertial measurement unit and wheel encoders, while external force coefficients may be obtained through cable tension sensors and force sensors on the working tool. The instantaneous slip ratio can be calculated by comparing the rotational speed of the drive wheels with the robot's actual displacement speed, while the temperature of the drive wheel / track surface is monitored in real time by an infrared temperature sensor. In a specific working condition, the robot is passing through a curved pipe at a relatively high speed (resulting in a high motion and attitude coefficient, e.g., 0.7), while its working tool is drilling, generating a certain reaction force (resulting in a high external force coefficient, e.g., 0.5). In this case, the system will take the larger value of the two, i.e., 0.7, as the demand benchmark. If the instantaneous slip ratio at this time It is 0.05, while the ideal slip ratio is... The value is 0.02, while the surface temperature of the drive wheel / track is... The optimal operating temperature is 60℃. Operating temperature range: 45℃ The temperature is 25℃. In calculating the slip ratio matching degree... At that time, due to demand benchmark The slip ratio is relatively high, even if the deviation is not significant. Also because The amplification effect of the term significantly reduces this. Similarly, in calculating temperature matching degree... hour, This will also amplify the effects of temperature deviation, leading to Decrease. Ultimately, the adhesion matching degree under operating conditions... Take and The smaller value in the range. For example, if The calculated result is 0.35. The calculation result is 0.45, then It is 0.35. This is relatively low. The value will act as a signal, indicating that the current attachment status is poor and the clamping force of the support arm needs to be increased. Conversely, if the robot moves slowly and uniformly in a straight pipe without external load, the motion and attitude coefficients and the external force coefficients will be low, resulting in... It is close to 0. At this point, even if there are slight deviations in slip ratio or temperature, due to... Items close to 1 have a smaller "penalty" effect on the matching degree. and It will remain at a high level, thus making The value is also relatively high. This indicates a good adhesion condition, and the system can consider appropriately reducing the clamping force to save energy. Through the above technical solution, the working condition adhesion matching degree calculation method of this application introduces a demand benchmark. This method dynamically assesses the impact of instantaneous slip rate and temperature deviation on adhesion performance. It enables the system to more accurately identify the true adhesion state between the robot and the pipe wall under different operational requirements. Under high-demand conditions, even slight slippage or temperature deviation is identified as a serious adhesion problem, prompting a timely system response; while under low-demand conditions, a certain margin of error is allowed. This refined adhesion matching assessment allows for more precise and intelligent adjustment of the support arm clamping force. It avoids energy waste and component wear caused by excessive clamping force when adhesion is good, while ensuring that clamping force can be increased quickly and effectively when adhesion deteriorates or demand increases, thereby significantly improving the robot's motion stability, operational reliability, and energy efficiency in complex industrial pipeline environments.

[0049] This application further proposes a process for calculating and obtaining the pipe's geometric coefficients as follows: Obtain the pipe's inner diameter, bending radius, and internal local obstacle height, as well as the optimal pipe inner diameter, the maximum permissible inner diameter deviation (i.e., the maximum of the absolute values ​​of the difference between the maximum permissible inner diameter and the optimal inner diameter, and the absolute values ​​of the difference between the optimal inner diameter and the minimum permissible inner diameter), the minimum permissible bending radius, and the maximum permissible obstacle height; the pipe's inner diameter, bending radius, and internal local obstacle height are real-time or preset parameters describing the current pipe's geometric characteristics. For example, the pipe inner diameter can be obtained in real-time by a laser rangefinder or ultrasonic sensor mounted on the robot, or by pre-existing pipe inspection data; the bending radius can be estimated by the robot's inertial measurement unit (IMU) combined with a kinematic model, or by obtaining the pipe's three-dimensional scanning data; the internal local obstacle height can be detected by a vision sensor or tactile sensor at the robot's front end.

[0050] The pipe diameter deviation index is obtained by comparing the absolute value of the difference between the pipe's inner diameter and the optimal inner diameter with the maximum permissible inner diameter deviation (i.e., the maximum of the absolute values ​​of the maximum permissible difference between the optimal and minimum permissible inner diameters), and then applying a min function with an upper limit of 1. This step aims to quantify the degree to which the pipe's inner diameter deviates from the ideal state. The pipe diameter deviation index reflects the proportion of the difference between the current inner diameter and the optimal inner diameter relative to the maximum permissible deviation. By calculating the absolute difference and comparing it with the maximum permissible deviation, a standardized, dimensionless index can be obtained. The upper limit of 1 for the min function ensures that the index is between 0 and 1; even if the actual deviation exceeds the maximum permissible deviation, the index will not exceed 1, thus avoiding excessive weighting or unreasonable results in subsequent calculations. For example, when the pipe's inner diameter is exactly the same as the optimal inner diameter, the difference is 0, and the index is 0; when the deviation reaches the maximum permissible deviation, the index is 1.

[0051] The minimum permissible bending radius is compared to the current pipe bending radius, and a min function is used to limit the ratio to an upper limit of 1 to obtain the bending radius index. This step quantifies the impact of pipe bending on robot motion. The bending radius index reflects the severity of the current pipe bending. The smaller the pipe bending radius, the greater the difficulty for the robot to pass through, and the larger the index should be. By comparing the minimum permissible bending radius with the current bending radius, an index reflecting the severity of the bending can be obtained. Similarly, using a min function with an upper limit of 1 ensures that the index is between 0 and 1, representing the change in bending severity from ideal (large bending radius, index close to 0) to extreme (small bending radius, index close to 1).

[0052] The obstacle height index is obtained by comparing the current local obstacle height within the pipe with the maximum permissible obstacle height, and then using a min function to limit the ratio to an upper limit of 1. This step aims to quantify the degree to which obstacles within the pipe hinder the robot's movement. The obstacle height index reflects the proportion of the obstacle's height relative to the maximum height the robot can safely cross. By comparing the current obstacle height with the maximum permissible obstacle height, a standardized index can be obtained. Using a min function with an upper limit of 1 ensures that the index is between 0 and 1, representing the change in obstacle height from none (index 0) to the limit (index 1).

[0053] The optimal pipe inner diameter, maximum permissible inner diameter deviation, minimum permissible bending radius, and maximum permissible obstacle height are preset reference values ​​used to assess the degree of deviation between the current pipe geometry and the ideal state. These reference values ​​are typically set according to the robot's design specifications, motion capabilities, attachment mechanism characteristics, and pipeline operation safety regulations, and are stored in the robot's control system.

[0054] The pipe geometric coefficient is calculated based on the pipe inner diameter deviation index, bending radius index, and obstacle height index. The pipe geometric coefficient is positively correlated with each index, and it approaches 1 when any index reaches its limit; it is zero when all indices are zero. Specifically, the calculation method involves substituting the pipe inner diameter deviation index, bending radius index, and obstacle height index into the formula. Calculate and obtain the pipe geometric coefficients , This step combines the three geometric indices mentioned above to obtain a unified pipe geometric coefficient. The formula uses a product form, where each term... This indicates the "accessibility" or "friendliness" of the corresponding geometric feature. When a certain index... When the value is close to 1 (i.e., the geometric conditions are very poor), the corresponding If the term is close to 0, this will cause the entire product term to be close to 0, thus making... Close to 1. Conversely, when all indices are close to 1. When all are close to 0 (i.e., the geometric conditions are very ideal), all All terms are close to 1, making Approaching 0. This calculation method effectively integrates three independent but interrelated factors: pipe inner diameter deviation, bending radius, and obstacle height, forming a comprehensive index that fully reflects the degree to which pipe geometry hinders robot movement. The deviation index of the pipe inner diameter. The bending radius index, This is the obstacle height index.

[0055] The proposed solution first obtains real-time geometric parameters of the pipe, such as its inner diameter, bending radius, and height of internal local obstacles, and then combines these with preset reference values, including the optimal pipe inner diameter, maximum allowable inner diameter deviation, minimum allowable bending radius, and maximum allowable obstacle height. Subsequently, these real-time geometric parameters are standardized and compared with the preset reference values ​​to generate pipe inner diameter deviation indices. Bending radius index Obstacle height index These indices are all limited to a range of 0 to 1, effectively transforming the geometric characteristics of different dimensions into a unified, dimensionless index reflecting their severity. Next, these three indices are substituted into the formula. The calculation is performed. This formula cleverly multiplies the "friendliness" of each geometric factor (i.e., 1 minus the corresponding index), then subtracts this product from 1, thus obtaining the final pipe geometry coefficient. This product-based calculation logic ensures that the pipe geometry coefficient will remain constant as long as any one of the geometric factors (such as inner diameter deviation, bend, or obstruction) reaches its limit value (i.e., the corresponding exponent is 1). The value will approach 1, indicating that the pipe geometry greatly hinders the robot's movement. Conversely, the pipe geometry coefficient will only be negative when all geometric factors are ideal (i.e., all exponents are 0). The result is 0. Through this refined calculation process, this method can accurately and comprehensively quantify the combined impact of pipe geometry on robot motion, overcoming the inaccuracies that may arise from simple assessments. The calculated pipe geometry coefficients... The force is then input into the calculation of the clamping force of the target support arm, working in conjunction with the working condition adhesion matching degree. This allows the robot to dynamically adjust the clamping force of the support arm according to the actual geometric challenges of the pipeline, thereby maintaining stable adhesion and efficient movement in various complex pipeline environments.

[0056] The following example illustrates this. Suppose an industrial pipeline robot is performing a pipeline inspection task. Through its onboard sensor system, the robot obtains real-time data showing the pipeline's inner diameter as 280mm, bending radius as 1.5m, and the height of any internal obstacle as 5mm. Simultaneously, the robot's control system has preset reference values: optimal pipeline inner diameter of 300mm, maximum allowable inner diameter deviation of 50mm, minimum allowable bending radius of 1m, and maximum allowable obstacle height of 10mm. First, the pipeline inner diameter deviation index is calculated. The absolute value of the difference between the current inner diameter and the optimal inner diameter is 20mm. Ratioing this to the maximum permissible inner diameter deviation of 50mm yields 0.4. After applying a min function with an upper limit of 1, The value is 0.4. Next, the bending radius exponent is calculated. The ratio of the minimum allowable bending radius of 1m to the current bending radius of 1.5m is calculated to obtain 0.67. After applying the min function to limit the upper limit to 1, The value is 0.67. Next, calculate the obstacle height index. The ratio of the current local obstacle height (5mm) in the pipeline to the maximum allowable obstacle height (10mm) is calculated to obtain 0.5. After applying the min function with an upper limit of 1, The value is 0.5. Finally, substitute the calculated exponent into the formula. The calculation yields 0.901. This result... A value of 0.901 indicates that the current pipe geometry significantly impedes the robot's movement, approaching its limit. Based on this high pipe geometry coefficient, the control system, along with other factors, calculates a relatively large target support arm clamping force to ensure the robot maintains sufficient adhesion when traversing this complex pipe, preventing slippage or jamming.

[0057] Through the above technical solution, this application can accurately quantify the combined hindering effect of pipe inner diameter deviation, curvature, and the height of internal local obstacles on robot movement. By converting these geometric features into standardized indices and using a product-form formula for comprehensive calculation, the obtained pipe geometric coefficients can comprehensively and accurately reflect the complexity of the current pipe environment. This avoids errors caused by single or coarse evaluation of geometric conditions, ensuring that the actual geometric challenges of the pipe are fully considered when calculating the clamping force of the target support arm. Therefore, the robot can dynamically adjust its support arm clamping force according to the actual geometry of the pipe, thereby significantly improving the robot's adaptability, stability, and throughput in complex and variable pipe environments, and effectively reducing energy loss and component wear caused by robot jamming, slippage, or improper clamping force.

[0058] This application further proposes a process for calculating the clamping force of the target support arm as follows: The working condition adhesion matching degree and the pipe geometry coefficient are obtained. The working condition adhesion matching degree reflects the adhesion state between the robot's drive wheel / track and the pipe wall under current motion posture, external force, instantaneous slip rate, and temperature conditions. Its value range is (0,1], where 1 represents a perfect matching state, and close to 0 indicates a poor adhesion state. This coefficient is a key indicator for evaluating the robot's current adhesion performance; the lower the value, the more prone the robot is to slippage or poor adhesion, thus requiring a larger clamping force to compensate. The pipe geometry coefficient is used to quantify the degree to which the pipe geometry hinders the robot's movement. Its value range is [0,1], where 0 represents an ideal straight pipe, optimal inner diameter, and no obstacles, and 1 represents the limiting bending radius, maximum allowable inner diameter deviation, and highest obstacle. The higher the coefficient, the more complex the pipe environment, and the greater the clamping force required by the robot to overcome geometric obstacles and maintain stable passage. These parameters are calculated through the aforementioned modules.

[0059] The target support arm clamping force is calculated based on the working condition adhesion matching degree, the pipe geometry coefficient, and the preset minimum and maximum values ​​of the support arm clamping force. The lower the working condition adhesion matching degree or the larger the pipe geometry coefficient, the closer the calculated target support arm clamping force is to the maximum value. Specifically, the calculation method involves substituting the working condition adhesion matching degree and the pipe geometry coefficient into the formula. Calculate and obtain the clamping force of the target support arm. ,in, This represents the minimum clamping force of the support arm. This represents the minimum clamping force that the support arm must apply under any circumstances. This minimum value is usually set based on the robot's own weight, basic friction requirements, and the minimum force required to maintain stability under ideal working conditions, so as to ensure that the robot can maintain basic attachment and support even under the most favorable conditions. This represents the maximum clamping force of the support arm. This represents the maximum clamping force that the support arm can apply. This maximum value is usually limited by factors such as the strength of the robot structure, the capability of the drive mechanism, the pressure resistance of the pipe wall material, and the need to avoid excessive energy consumption and component wear. Setting a maximum value is to prevent damage to the robot or pipe due to excessive clamping force. The adaptation weights are in the range of 0-1. Used to adjust the adhesion matching degree under working conditions and pipe geometry The relative importance of the clamping force in the calculation of the target support arm, when A larger value indicates that the calculation of the target clamping force places more emphasis on the influence of the current working condition's adhesion state; when... When the value is small, it means that more emphasis is placed on the influence of pipeline geometry. By adjusting this weight, the demand for clamping force by dynamic working conditions and static environmental factors can be flexibly balanced according to the actual application scenario and control strategy preferences. For the degree of adhesion matching under working conditions, For pipeline geometry coefficients.

[0060] The proposed solution calculates the clamping force of the target support arm in an adaptive manner by comprehensively considering the dynamic attachment state between the robot and the pipe wall, as well as the static geometric characteristics of the pipe environment. Specifically, the solution first obtains the working condition attachment matching degree, which reflects the current attachment performance. Pipeline geometry coefficients that reflect pipeline complexity Given the adhesion matching degree under operating conditions The lower the value, the greater the clamping force required by the robot to maintain adhesion; therefore, its complement is used in the calculation. To indicate the degree of clamping force required, i.e. The larger the value, the greater the required clamping force. Simultaneously, the pipe geometry... The higher the value, the more challenging the pipeline environment, and the greater the clamping force required for the robot to overcome obstacles. These two requirements, namely... and By adapting weights A weighted combination is performed to form a comprehensive demand factor. This comprehensive demand factor is then used to minimize the clamping force of the support arm. and the maximum clamping force of the support arm Interpolation is performed between these values ​​to calculate the final target support arm clamping force. This calculation method allows the target clamping force to dynamically respond to the actual working conditions and pipeline environment of the robot, ensuring that the clamping force is increased to enhance stability when the adhesion is poor or the pipeline is complex, while the clamping force is reduced to save energy and reduce wear when the adhesion is good and the pipeline is simple.

[0061] As a specific implementation method, when calculating the clamping force of the target support arm, a minimum clamping force of the support arm can be set first. and the maximum clamping force of the support arm ,For example, It can be set as the minimum force required for the robot to maintain basic support, while This can be set to the maximum force that can be applied without damaging pipes or robot components. (Adaptation weight) The adhesion matching degree can be determined according to the actual application conditions. and pipe geometry The emphasis can be adjusted; for example, if more attention is paid to dynamic adhesion performance, then... Set it to 0.6 or 0.7; if you are more concerned about pipe geometry, you can... Set to 0.3 or 0.4. During robot operation, the current adhesion matching degree under working conditions is acquired in real time. and pipe geometry For example, when the robot is in a good attachment state (e.g., working condition attachment matching degree), (0.8) and the piping environment is relatively simple (e.g., piping geometry). When the target support arm clamping force is 0.1, the calculated clamping force is... It will approach Conversely, when the robot faces poor adhesion conditions (e.g., poor adhesion matching in the working condition), (0.2) and the pipeline environment is complex (e.g., pipeline geometry). When the challenge is 0.7), the calculated target support arm clamping force is... It will increase significantly, approaching... In this way, the system can accurately calculate the appropriate clamping force based on real-time data and preset parameters.

[0062] Through the above technical solution, this application can achieve precise and adaptive control of the clamping force of a robot support arm for industrial pipelines. This solution comprehensively considers the dynamic attachment state between the robot and the pipe wall and the static geometric characteristics of the pipeline environment, avoiding the limitations of single-factor decision-making. By adjusting the working condition attachment matching degree... and pipe geometry A weighted combination is performed, and interpolation calculations are then performed within a preset clamping force range to ensure the clamping force of the target support arm is [calculated / measured]. It can dynamically adapt to constantly changing working conditions and pipeline conditions. This not only significantly improves the stability and reliability of the robot's movement in complex industrial pipelines, effectively preventing slippage and jamming, but also reduces the robot's energy consumption by avoiding unnecessary excessive clamping force, and reduces wear between the drive wheels / tracks and the pipe wall, thereby extending the service life of the robot and the pipeline, and improving operational efficiency and safety.

[0063] In other embodiments, this application proposes a robot control device for industrial pipelines, which can embed the above-mentioned robot control method for industrial pipelines into a hardware carrier, thereby realizing the automation and real-time execution of the method.

[0064] While the aforementioned robot control methods for industrial pipelines define in detail how to calculate and adjust the clamping force of the support arm to adapt to different working conditions and pipeline geometry, they remain at the methodological level. In practical industrial applications, effectively and reliably deploying these complex calculation and adjustment logics into the robot system and ensuring its stable operation is a technical problem that needs to be solved.

[0065] This application further proposes a robot control device for industrial pipelines, comprising: a memory for storing a computer program; and a processor for implementing the steps of the aforementioned robot control method for industrial pipelines when executing the computer program. The memory is a hardware component used to store data and instructions. It can be volatile memory, such as random access memory (RAM), for temporarily storing the currently executing program and data; or it can be non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive, or solid-state drive, for long-term storage of the operating system, application programs (such as the computer program corresponding to the robot control method described in this application), and configuration data. Its function is to provide the processor with all the information required to execute tasks. A computer program is a collection of instructions designed to guide the computer to perform specific tasks or operations. In this application, the computer program includes all the logic and algorithms for implementing the aforementioned robot control method for industrial pipelines, such as steps for calculating motion and attitude coefficients, external force coefficients, working condition adhesion matching degree, pipeline geometric coefficients, and target support arm clamping force. The computer program can exist in the form of source code or as compiled and linked executable code. The processor is the core component of a computer system, responsible for interpreting and executing instructions in a computer program, and performing data processing and calculations. It can be a central processing unit, microcontroller, digital signal processor, or field-programmable gate array, among others. The processor controls the operation of various robot components by executing computer programs stored in memory and implements complex control algorithms, such as adjusting the clamping force of the support arm based on calculation results.

[0066] The solution in this application achieves automation and real-time execution of the aforementioned robot control method for industrial pipelines by embedding it into a hardware carrier. Specifically, the memory is responsible for securely storing the computer programs required to implement the robot control method. When the robot system starts or needs to perform a control task, the processor reads and executes these computer programs from the memory. During execution, the processor acquires various sensor data in real time, including the robot's pitch angle, roll angle, motion speed, motion acceleration, cable drag force, reaction force during operation, instantaneous slip rate (instantaneous slip rate between the robot drive wheel / track and the pipe wall), temperature (surface temperature of the robot drive wheel / track), pipe inner diameter, bending radius, and height of internal local obstacles, according to the program instructions. Subsequently, the processor calculates the motion and attitude coefficients, external force coefficients, working condition adhesion matching degree, and pipe geometric coefficients sequentially according to the algorithm preset in the computer program, and finally calculates the target support arm clamping force. After the calculation is completed, the processor issues an instruction to drive the robot's actuator (e.g., the drive unit of the support arm) to adjust the current support arm clamping force to the calculated target support arm clamping force. The entire process forms a closed-loop control system, enabling the robot to dynamically adjust its attachment state based on real-time operating conditions and pipeline geometry, thereby ensuring stable and efficient operation in complex and ever-changing industrial pipeline environments. This device-based implementation transforms abstract control methods into practically deployable and operational physical systems, greatly enhancing the practicality and reliability of the control methods.

[0067] In one specific implementation, the aforementioned robot control device for industrial pipelines can be integrated into an embedded control unit. The memory can be a NAND flash memory chip, used to store the operating system, robot control application, and preset parameter configurations. The processor can be a high-performance ARM Cortex-M series microcontroller, which has sufficient processing power to execute complex control algorithms in real time and can interact with the robot's sensor modules (e.g., attitude sensors, force sensors, temperature sensors, slip ratio sensors, etc.) and actuator modules (e.g., the motor driver of the support arm) via various communication interfaces (such as CAN bus, SPI, I2C, etc.) and send control commands. The computer program can be written in C / C++ and compiled and burned into the NAND flash memory. When the robot is powered on and started, the microcontroller loads and runs the program from the flash memory, continuously monitoring the robot's status and the pipeline environment, and logically calculates and adjusts the support arm's clamping force according to the aforementioned method.

[0068] The above technical solution realizes the robot control method for industrial pipelines in the form of a device, solving the problem that the method is difficult to directly apply to actual robot systems. This control device integrates complex computational logic and adjustment strategies into a hardware platform, enabling the robot to autonomously and in real-time perceive environmental changes and precisely adjust the clamping force. This not only improves the automation level and response speed of robot control, but also ensures the stable operation of the control method through hardware reliability, avoiding errors and lags caused by human intervention. Therefore, it significantly improves the safety, stability, and efficiency of robots operating in complex industrial pipelines.

[0069] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A robot control method for industrial pipelines, characterized in that, Includes the following steps: Based on the robot's pitch angle, roll angle, motion speed, and motion acceleration, motion and attitude coefficients are calculated and obtained. Based on the cable drag force and the reaction force during operation, the external force coefficient is calculated and obtained; based on the motion and attitude coefficients and the instantaneous slip rate and temperature under the external force coefficients, the working condition adhesion matching degree is calculated and obtained; based on the inner diameter, bending radius and height of local obstacles in the pipe, the pipe geometry coefficient is calculated and obtained; based on the working condition adhesion matching degree and the pipe geometry coefficient, the target support arm clamping force is calculated and obtained, and the current support arm clamping force is adjusted to the target support arm clamping force.

2. The robot control method for industrial pipelines according to claim 1, characterized in that, The process for calculating and obtaining the adhesion matching degree under working conditions is as follows: obtain the motion and attitude coefficients, external force coefficients, instantaneous slip ratio, and temperature; and take the larger value between the motion and attitude coefficients and the external force coefficients as the requirement benchmark. Substitute the demand baseline and instantaneous slip ratio into the formula. Calculate and obtain the slip ratio matching degree ， ,in, Instantaneous slip ratio For the ideal slip ratio, Use the demand baseline; substitute the demand baseline and temperature into the formula. Calculate and obtain temperature matching degree ， ,in, For temperature, For optimal operating temperature, Operating temperature range Based on the demand baseline; the smaller value between the slip ratio matching degree and the temperature matching degree is taken as the working condition adhesion matching degree. ， ， When the slip ratio equals the ideal value and the temperature equals the optimal value, When the slip ratio or temperature approaches 0, it deviates significantly from the ideal value.

3. The robot control method for industrial pipelines according to claim 2, characterized in that, The process for calculating and obtaining motion and attitude coefficients is as follows: Obtain the robot's pitch angle, roll angle, motion speed, and motion acceleration; Ratio the absolute values ​​of the robot's pitch angle and roll angle to the maximum permissible pitch angle and maximum permissible roll angle, respectively, to obtain the pitch angle index and roll angle index; Ratio the absolute values ​​of the robot's motion speed and motion acceleration to the maximum speed and maximum acceleration absolute values, respectively, to obtain the motion speed index and motion acceleration index; Weighted summation of the pitch angle index, roll angle index, motion speed index, and motion acceleration index yields the motion and attitude coefficients. The pitch angle index, roll angle index, motion speed index, and motion acceleration index are all positively correlated with the motion and attitude coefficients.

4. The robot control method for industrial pipelines according to claim 2, characterized in that, The process for calculating and obtaining the external force coefficient is as follows: obtain the cable drag force and the reaction force during operation, as well as the maximum cable drag force and the maximum reaction force during operation; The cable drag force and the reaction force during operation are respectively compared with the maximum cable drag force and the maximum reaction force during operation to obtain the cable drag force index and the reaction force index during operation. The larger of the cable drag force index and the reaction force index during operation is taken as the external force coefficient. ， Used to reflect the magnitude of externally applied resistance or reaction force. Indicates no external force. This indicates that at least one external force has reached its maximum value.

5. The robot control method for industrial pipelines according to claim 1, characterized in that, The process for calculating and obtaining the pipe's geometric coefficients is as follows: Obtain the pipe's inner diameter, bending radius, and height of any local obstruction; Ratio the absolute value of the difference between the pipe's inner diameter and the optimal inner diameter with the maximum permissible inner diameter deviation, and apply a min function with an upper limit of 1 to obtain the pipe inner diameter deviation index; Ratio the minimum permissible bending radius with the current pipe bending radius, and apply a min function with an upper limit of 1 to obtain the bending radius index; Ratio the current height of any local obstruction within the pipe with the maximum permissible obstruction height, and apply a min function with an upper limit of 1 to obtain the obstruction height index; Calculate the pipe's geometric coefficients based on the pipe inner diameter deviation index, bending radius index, and obstruction height index. The pipe's geometric coefficients are positively correlated with each index, and when any index reaches its limit, the pipe's geometric coefficients approach 1; when all indices are zero, the pipe's geometric coefficients are zero.

6. The robot control method for industrial pipelines according to claim 1, characterized in that, The process for calculating the clamping force of the target support arm is as follows: obtain the working condition adhesion matching degree and the pipe geometry coefficient; calculate the target support arm clamping force based on the working condition adhesion matching degree, the pipe geometry coefficient, and the preset minimum and maximum values ​​of the support arm clamping force; wherein, the lower the working condition adhesion matching degree or the larger the pipe geometry coefficient, the closer the calculated target support arm clamping force is to the maximum value.

7. A robot control device for industrial pipelines, characterized in that, include: Memory, used to store computer programs; A processor, configured to, when executing a computer program, implement the steps of the robot control method for industrial pipelines as described in any one of claims 1-6.

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