Pipeline repairing method and system based on multi-mechanism cooperation

Abstract

The invention discloses a pipeline repairing method and system based on multi-mechanism cooperation, and belongs to the technical field of pipeline repairing. According to the method, the contact force mechanism model of the vacuum adsorption gripping apparatus of the pipeline repairing equipment is constructed, and the vacuum adsorption gripping apparatus is adjusted through the contact force mechanism model; then, a kinematics mechanism model of the mechanical arm is constructed, then the pipe piece assembling movement track of the mechanical arm is planned in combination with the pipeline three-dimensional point cloud model, and then the mechanical arm is driven through a dynamics mechanism and an impedance control mechanism to assemble the assembled pipe pieces to a preset to-be-repaired position; and after splicing of the segments is completed, a segment three-dimensional point cloud model of the to-be-repaired position is constructed, a grouting path of the to-be-repaired position is determined based on the segment three-dimensional point cloud model, and the mechanical arm is driven to conduct grouting on the to-be-repaired position along the grouting path. According to the method, through multi-mechanism cooperative control of the kinematics mechanism model, the dynamics mechanism and the impedance control mechanism, the precision and efficiency of pipeline repair are improved.

Description

Technical Field

[0001] This invention belongs to the field of pipeline repair technology, and in particular relates to a pipeline repair method and system based on multi-mechanism synergy. Background Technology

[0002] Pipelines are a crucial component of infrastructure construction, serving numerous functions such as rainwater drainage, sewage transportation, and power and communication. As pipelines age, structural defects become increasingly frequent, with problems like leakage, rupture, and deformation becoming more prominent. If not repaired promptly, these issues can easily lead to secondary disasters such as road collapses and environmental pollution. Traditional open-cut repair methods require damaging road surfaces, disrupting traffic, and have long construction cycles, making them unsuitable for current pipeline repair needs. Therefore, trenchless repair of damaged pipeline segments has become the mainstream solution for pipeline maintenance.

[0003] Current pipeline repair solutions mostly utilize pipeline repair equipment designed for specific processes. Examples include drilling robots that only perform drilling, wall-climbing robots that only perform grouting, or integrated mechanisms that only assemble pipe segments. While these devices can repair pipelines through collaborative operation, this approach requires a large number of devices working together, leading to multiple equipment changes or reliance on manual intervention for process transitions, severely limiting construction efficiency and repair accuracy. As mechanization increases, more and more pipeline repair equipment with complete repair functions is being used. However, current control methods for this type of equipment are relatively simple, failing to achieve accurate control of the entire pipeline repair process in complex environments, which severely restricts the accuracy and efficiency of pipeline repair. Summary of the Invention

[0004] The present invention aims to provide a pipeline repair method and system based on multi-mechanism synergy to solve the above-mentioned technical problems. The pipeline repair is achieved by multi-mechanism synergistic control of pipeline repair equipment, thereby improving the accuracy and efficiency of pipeline repair.

[0005] To address the aforementioned technical problems, embodiments of the present invention provide a pipeline repair method based on multi-mechanism synergy, comprising: A three-dimensional point cloud model of the pipeline is constructed, and the attitude deviation data of the preset pipeline repair equipment is determined based on the three-dimensional point cloud model of the pipeline; a contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed based on the attitude deviation data. The vacuum adsorption gripper of the pipeline repair equipment is adjusted based on the contact force mechanism model until the pipeline repair equipment meets the preset stable operation requirements. The joint parameters of the robotic arm of the pipeline repair equipment are obtained, and a kinematic mechanism model of the robotic arm is constructed based on the joint parameters; and the segment assembly motion trajectory of the robotic arm is determined based on the three-dimensional point cloud model of the pipeline and the kinematic mechanism model. The robotic arm is driven to move along the assembly trajectory of the pipe segment based on a preset dynamic mechanism and a preset impedance control mechanism, so that the robotic arm assembles the preset pipe segment to be assembled at the preset repair position; After the assembly of the segments to be assembled is completed, a three-dimensional point cloud model of the segment to be repaired is constructed; and the grouting path of the segment to be repaired is determined based on the three-dimensional point cloud model of the segment. The robotic arm is driven to move along the grouting path to grout the location to be repaired, thereby completing the repair of the pipeline.

[0006] Understandably, compared to existing technologies, this invention, by constructing a three-dimensional point cloud model of the pipeline, can provide an accurate spatial reference for the subsequent adjustment of the vacuum adsorption gripper and segment assembly of the pipeline repair equipment. Next, the attitude deviation data is determined using the three-dimensional point cloud model of the pipeline, and a contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed based on this data. This allows for the adjustment of the vacuum adsorption gripper using the contact force mechanism model, ensuring that the pipeline repair equipment meets preset stable operating requirements and providing a stable operating platform for subsequent segment assembly and grouting. Finally, the joint parameters of the robotic arm of the pipeline repair equipment are obtained, and a kinematic mechanism model of the robotic arm is constructed. This invention models the movement of a robotic arm within a pipeline and, combined with a 3D point cloud model of the pipeline, plans the segment assembly trajectory of the robotic arm. This ensures that the segment assembly trajectory not only meets the physical motion design requirements of the robotic arm but also adapts to the complex environment inside the pipeline. Then, through dynamic and impedance control mechanisms, the robotic arm is driven to assemble the segments at the preset repair locations, achieving precise segment assembly. After segment assembly, a 3D point cloud model of the segment at the repair location is constructed. Based on this model, the grouting path for the repair location is determined, and the robotic arm is driven to grout along the path. This enables accurate control of the entire pipeline repair process in complex pipeline environments. This invention, through multi-mechanism collaborative control using kinematic, dynamic, and impedance control mechanisms, achieves the completion of multiple operational stages in the pipeline repair process with a single pipeline repair device. This avoids the cumbersome process transitions and uncertainties caused by manual intervention resulting from multi-device collaboration, which lead to low pipeline repair efficiency and accuracy, thus improving the accuracy and efficiency of pipeline repair.

[0007] As a preferred embodiment, the construction of a three-dimensional point cloud model of the pipeline, determining the attitude deviation data of a preset pipeline repair device based on the three-dimensional point cloud model of the pipeline, and constructing a contact force mechanism model of the vacuum adsorption gripper of the pipeline repair device based on the attitude deviation data, including: Construct a 3D point cloud model of the pipeline; The axial direction vector and pipe wall normal vector of the pipeline are determined based on the three-dimensional point cloud model of the pipeline; the attitude deviation data of the preset pipeline repair equipment are determined based on the axial direction vector and pipe wall normal vector. The resultant external torque and external pitching torque of the pipeline repair equipment are determined based on the attitude deviation data. Obtain the real-time vacuum pressure of each vacuum adsorption gripper of the pipeline repair equipment; A contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed based on the real-time vacuum pressure, the external pitching moment, and the resultant external moment.

[0008] In the above scheme, a three-dimensional point cloud model of the pipeline is first constructed to accurately extract the axial direction vector and the pipe wall normal vector. This makes the attitude deviation data obtained from the axial direction vector and the pipe wall normal vector more comprehensive and accurate, reflecting the actual tilt and torsion state of the pipeline repair equipment relative to the inner wall of the pipeline. Then, the attitude deviation data is converted into the resultant external torque and external pitching torque that cause the pipeline repair equipment to become unstable. Subsequently, a contact force mechanism model of the vacuum adsorption gripper is constructed using the real-time vacuum pressure, external pitching torque, and resultant external torque of the vacuum adsorption gripper. The contact force mechanism model can describe how the real-time vacuum pressure of the vacuum adsorption gripper balances with the external load under the current attitude, thus providing an accurate judgment benchmark for subsequent adjustment of the vacuum adsorption gripper. It can dynamically distribute the vacuum pressure of the vacuum adsorption gripper according to the actual force situation, effectively avoiding equipment slippage or overturning caused by insufficient local adsorption of the pipeline repair equipment. This forms a stable working platform, providing a foundation for subsequent pipeline assembly and grouting, and improving the accuracy and efficiency of subsequent pipeline repair.

[0009] As a preferred embodiment, the contact force mechanism model for the vacuum adsorption gripper of the pipeline repair equipment, based on the real-time vacuum pressure, the external pitching moment, and the resultant external moment, includes: The normal adsorption force of each vacuum adsorption gripper is determined based on the real-time vacuum pressure. Obtain the unit vector of the tube wall normal at the adsorption point of each vacuum adsorption gripper; The resultant reaction torque of the pipeline repair equipment is constructed based on the normal unit vector of the pipe wall at the adsorption point of each vacuum adsorption gripper and the normal adsorption force. The torque balance constraints of the pipeline repair equipment are constructed based on the resultant reaction torque and the resultant external torque. The pitch balance torque of the pipeline repair equipment is constructed based on the normal adsorption force of each of the vacuum adsorption grippers; The pitch moment balance constraint of the pipeline repair equipment is constructed based on the pitch balance moment and the external pitch moment. Based on the torque balance constraint, the pitch torque balance constraint, and the preset anti-slip constraint, a contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed.

[0010] In the above scheme, the resultant reaction torque of the pipeline repair equipment is constructed by the unit vector normal to the pipe wall at the adsorption point of the vacuum adsorption gripper and the real-time vacuum pressure. A torque balance constraint is established for the pipeline repair equipment by combining the resultant reaction torque with the resultant external torque, ensuring that the pipeline repair equipment will not experience overall rotational instability within the pipeline. Next, a pitching balance torque is constructed using the real-time vacuum pressure of the vacuum adsorption gripper, and combined with the external pitching torque, a pitching torque balance constraint is established for the pipeline repair equipment, mitigating the risk of overturning. Finally, an anti-slip constraint is introduced to address the issue of the pipeline repair equipment... The paper addresses the common sliding problem within pipeline environments. Finally, it constructs a contact force mechanism model for the vacuum adsorption gripper of the pipeline repair equipment through torque balance constraints, pitch torque balance constraints, and anti-slip constraints. This contact mechanics mechanism model provides a comprehensive and accurate adjustment basis for the vacuum adsorption gripper, enabling the pipeline repair equipment to automatically and dynamically adjust the vacuum pressure of each vacuum adsorption gripper in complex, variable, and uncertain pipeline environments. This provides a stable foundation for the precise movement of the subsequent robotic arm and the execution of complex repair tasks, avoiding the problem of poor repair accuracy caused by equipment instability and improving the accuracy of subsequent pipeline repairs.

[0011] As a preferred embodiment, the step of obtaining the joint parameters of the robotic arm of the pipeline repair equipment, constructing a kinematic mechanism model of the robotic arm based on the joint parameters, and determining the segment assembly motion trajectory of the robotic arm based on the three-dimensional point cloud model of the pipeline and the kinematic mechanism model includes: Obtain the joint parameters of the robotic arm of the pipeline repair equipment; Based on the joint parameters, a joint homogeneous transformation matrix between two adjacent joints in the robotic arm is constructed, and an end homogeneous transformation matrix of the robotic arm is constructed based on the homogeneous transformation matrix. The kinematic mechanism model of the robotic arm is constructed based on the joint homogeneous transformation matrix and the end homogeneous transformation matrix; The kinematic mechanism model is solved based on the three-dimensional point cloud model of the pipeline to determine the segment assembly motion trajectory of the robotic arm.

[0012] In the above scheme, by acquiring the joint parameters of the robotic arm of the pipeline repair equipment and constructing homogeneous transformation matrices between adjacent joints based on the joint parameters, a precise mathematical description of the geometric structure and motion relationship of the robotic arm can be achieved. Then, the homogeneous transformation matrix of the robotic arm's end effector pose in the base coordinate system is constructed using the homogeneous transformation matrix. The kinematic mechanism model of the robotic arm is then built using the joint homogeneous transformation matrices and the end effector homogeneous transformation matrix, enabling precise control of the robotic arm. Finally, the kinematic mechanism model is solved using a 3D point cloud model of the pipeline to determine the segment assembly motion trajectory of the robotic arm. This ensures that the segment assembly motion trajectory not only meets the physical limitations of the robotic arm itself but also considers the actual internal environment of the pipeline. This allows the pipeline repair equipment to cope with pipeline repair needs of different specifications and defect locations, avoiding repeated manual teaching or program adjustments. This not only greatly improves the efficiency of pipeline repair operations but also ensures that the robotic arm can achieve precise pipeline assembly in complex pipeline environments, thereby improving the efficiency and accuracy of pipeline repair.

[0013] As a preferred embodiment, the step of solving the kinematic mechanism model based on the three-dimensional point cloud model of the pipeline to determine the segment assembly motion trajectory of the robotic arm includes: Based on the three-dimensional point cloud model of the pipeline, the starting joint motion variable data and the end-effector starting position data of the robotic arm at the preset gripping point of the pipe segment to be assembled are determined; Based on the three-dimensional point cloud model of the pipeline, the termination joint motion variable data and end-effector termination position data of the robotic arm at the preset repair position are determined. The kinematic mechanism model is solved based on the initial joint motion variable data to obtain the initial Jacobian matrix of the robotic arm at the grasping point; and the initial end-effector velocity and initial end-effector acceleration of the robotic arm at the grasping point are determined based on the initial Jacobian matrix. The kinematic mechanism model is solved based on the termination joint motion variable data to obtain the termination Jacobian matrix of the robotic arm at the repair position; and the end-effector termination velocity and end-effector termination acceleration of the robotic arm at the repair position are determined based on the termination Jacobian matrix. The target motion trajectory function of the robotic arm is constructed based on a preset fifth-order polynomial interpolation algorithm; Based on the starting position data, the starting velocity of the end effector, the starting acceleration of the end effector, the ending position data, the ending velocity of the end effector, and the ending acceleration of the end effector, the target motion trajectory function is solved to determine the segment assembly motion trajectory of the robotic arm.

[0014] In the above scheme, the three-dimensional point cloud model of the pipeline can accurately identify the starting joint motion variables and end-effector position data of the robotic arm at the pre-set gripping point of the segment to be assembled, as well as the ending joint motion variables and end-effector position data of the robotic arm at the pre-set repair position. Then, the kinematic mechanism model is solved using the starting joint motion variable data to obtain the starting Jacobian matrix of the robotic arm at the gripping point, and thus the end-effector starting velocity and end-effector starting acceleration of the robotic arm at the gripping point. The kinematic mechanism model is then solved using the ending joint motion variable data to obtain the end-effector Jacobian matrix of the robotic arm at the repair position, and thus the end-effector starting velocity and end-effector starting acceleration of the robotic arm at the gripping point. Next, a target motion trajectory function for the robotic arm is constructed using a fifth-order polynomial interpolation algorithm. Compared to traditional trapezoidal velocity planning, the segment assembly motion trajectory calculated by the fifth-order polynomial interpolation algorithm can avoid vibration of the robotic arm in confined spaces. Finally, the starting position data, end-effector initial velocity, end-effector initial acceleration, end-effector termination position data, end-effector termination velocity, and end-effector termination acceleration are used as boundary conditions and substituted into the target motion trajectory function for solving. This yields a segment assembly motion trajectory in which the joint angles of the robotic arm change continuously and smoothly over time from the starting point to the end point. This ensures the stability of joint movements during segment assembly, thereby ensuring the stability of the segment's posture during high-speed, long-distance transportation. Consequently, precise segment assembly can be achieved, improving the accuracy of pipeline repair.

[0015] As a preferred embodiment, the robotic arm is driven to move along the assembly trajectory of the pipe segment based on a preset dynamic mechanism and a preset impedance control mechanism, so that the robotic arm assembles the preset pipe segment to be assembled at the preset repair position, including: During each control cycle of the robotic arm, the real-time end contact force, real-time joint motion variable values, and real-time joint velocity vector of the robotic arm are acquired. Based on the segment assembly motion trajectory, end-effector contact force, joint real-time motion variable values, and joint real-time velocity vector, an end-effector impedance control mechanism model of the robotic arm is constructed, and the joint correction acceleration and joint correction velocity of the robotic arm are determined based on the end-effector impedance control mechanism model. The joint correction acceleration and joint correction velocity are modeled based on a preset Lagrange dynamics modeling algorithm to determine the joint driving torque model of the robotic arm. Solve the joint driving torque model to obtain the joint driving torque of the robotic arm in the current control cycle; Based on the joint driving torque, the robotic arm moves along the assembly trajectory of the tube segment within the current control cycle, so that the robotic arm assembles the preset tube segment to be assembled at the preset repair position.

[0016] In the above scheme, the real-time end contact force, real-time joint motion variable values, and real-time joint velocity vector of the robotic arm are acquired in each control cycle of the robotic arm. Then, the end impedance control mechanism model of the robotic arm is constructed using the segment assembly motion trajectory, the real-time end contact force, the real-time joint motion variable values, and the real-time joint velocity vector. The end impedance control mechanism model enables the end of the robotic arm to have a compliant characteristic similar to spring damping, which can ensure the accuracy of segment assembly while improving operational safety. Then, the joint correction acceleration and joint correction velocity are modeled using the Lagrange dynamics modeling algorithm to determine the joint driving torque model of the robotic arm. The joint driving torque model can ensure that the joint driving torque of the robotic arm can not only consider the compliance requirements of segment assembly, but also the physical limitations of the robotic arm itself in the pipeline environment. This allows the robotic arm to perform segment assembly tasks compliantly and accurately in complex pipeline environments, improving the accuracy of segment assembly and thus improving the accuracy of pipeline repair.

[0017] As a preferred embodiment, the step of constructing an end-effector impedance control mechanism model for the robotic arm based on the segment assembly motion trajectory, real-time end-effector contact force, real-time joint motion variable values, and real-time joint velocity vector, and determining the joint correction acceleration and joint correction velocity of the robotic arm based on the end-effector impedance control mechanism model, includes: The kinematic mechanism model is solved based on the real-time motion variable values ​​of the joints to determine the real-time end position, joint position vector, and coordinate system unit vector of the robotic arm. The real-time Jacobian matrix of the robotic arm is constructed based on the joint position vector and the coordinate system unit vector, and the real-time end-effector velocity and real-time end-effector acceleration of the robotic arm are determined based on the real-time Jacobian matrix and the joint real-time velocity vector. The end target position, end target velocity, and end real-time acceleration of the robotic arm in the current control cycle are determined based on the segment assembly motion trajectory. Based on the real-time end position, real-time end velocity, real-time end acceleration, real-time end contact force, end target position, end target velocity, and real-time end acceleration, an end impedance control mechanism model for the robotic arm is constructed. The end-effector impedance control mechanism model is solved to determine the end-effector correction acceleration and end-effector correction velocity of the robotic arm. The joint correction acceleration and joint correction velocity of the robotic arm are determined based on the end-effector correction acceleration and end-effector correction velocity.

[0018] In the above scheme, the kinematic mechanism model is solved by using real-time joint motion variable values ​​to determine the real-time position of the robotic arm's end effector, joint position vector, and coordinate system unit vector. Then, a real-time Jacobian matrix that accurately describes the joints between the robotic arm's joints and the end effector is constructed using the joint position vector and coordinate system unit vector. Next, the real-time joint velocity vectors are converted into the real-time velocity and acceleration of the robotic arm's end effector using the real-time Jacobian matrix. Finally, the target end effector position, target end effector velocity, and real-time end effector acceleration of the robotic arm in the current control cycle are determined from the segment assembly motion trajectory. Finally, the real-time end effector position and real-time end effector velocity are combined with the results. A mechanism model for end-effector impedance control is constructed using real-time end-effector acceleration and contact force. This model enables precise calculation of the end-effector correction acceleration and velocity required to achieve the desired impedance characteristics, allowing the robotic arm's end-effector to exhibit spring-damped compliance characteristics. This ensures accurate segment assembly while improving operational safety. Finally, the end-effector correction acceleration and velocity are converted into directly controllable joint correction acceleration and velocity within the robotic arm, achieving precise control over segment assembly and improving the accuracy of pipeline repair.

[0019] As a preferred embodiment, after assembling the segment to be assembled, constructing a three-dimensional point cloud model of the segment at the location to be repaired; and determining the grouting path at the location to be repaired based on the three-dimensional point cloud model of the segment, includes: After the assembly of the segment to be assembled is completed, a three-dimensional point cloud model of the segment at the location to be repaired is constructed. Seed points are selected from the three-dimensional point cloud model of the tunnel segment based on a preset curvature threshold and the curvature of each point cloud in the model. Centered on the seed point, the point cloud of the three-dimensional point cloud model of the pipe segment is clustered based on a preset region growing algorithm to obtain a set of point clouds of the cavity region. Boundary fitting is performed on the point cloud set of the cavity region to determine the cavity contour boundary, and the grouting start point is determined based on the cavity contour boundary; Centered on the grouting starting point, the cavity contour boundary is sliced ​​based on a preset slicing scanning algorithm to generate an initial grouting path that determines the location to be repaired; The initial grouting path is verified based on the kinematic mechanism model to determine the grouting path for the location to be repaired.

[0020] In the above scheme, a three-dimensional point cloud model of the pipe segment to be repaired is constructed, which can accurately represent the morphology of the cavity region. Next, the point cloud is filtered using a curvature threshold and the curvature of the point cloud to obtain seed points that can represent the cavity edge or areas of drastic change. Then, starting from the seed points, a region growing algorithm is used to aggregate point clouds with similar geometric features to the seed points into a cavity region point cloud set, thereby accurately segmenting the point cloud representing the cavity region from the entire model. Finally, boundary fitting is performed on the cavity region point cloud set to determine the cavity contour boundary and the grouting start point. Using the grouting start point as the center, a slicing scanning algorithm is used to slice the cavity contour boundary dynamically. An initial grouting path is generated to determine the location to be repaired. Finally, the initial grouting path is verified by a kinematic mechanism model to obtain the grouting path for the location to be repaired. Compared with the fixed grouting path of the traditional method, the grouting path is dynamically generated by the region growing algorithm, boundary fitting, slice scanning algorithm and kinematic mechanism model. This not only enables grouting to conform to various irregular cavity shapes and ensures that there are no dead corners in grouting, but also ensures that the planned grouting path is within the reachable space of the robotic arm and that the joint movement is smooth without abrupt changes by the kinematic mechanism model. This effectively avoids the problem of incomplete or excessive grouting caused by irregular cavity shapes, improves the accuracy and efficiency of grouting, and thus improves the accuracy and efficiency of pipeline repair.

[0021] As a preferred embodiment, the step of driving the robotic arm to move along the grouting path to grout the location to be repaired, thereby completing the repair of the pipeline, includes: Drive the robotic arm to move along the grouting path and control the grouting head of the robotic arm to grout the grouting path to grout the location to be repaired; After the robotic arm completes the movement of the grouting path, a three-dimensional point cloud model of the grouting at the location to be repaired is constructed. The grouting 3D point cloud model and the segment 3D point cloud model are registered according to a preset point cloud registration algorithm to obtain the first grouting 3D point cloud model corresponding to the grouting 3D point cloud model and the first segment 3D point cloud model corresponding to the segment 3D point cloud model. The first grouting 3D point cloud model is reconstructed to obtain the grouting-filled surface model; The surface of the cavity before grouting is obtained by reconstructing the three-dimensional point cloud model of the first segment. Construct a closed bounding box between the grouting-filled surface model and the grouting-prepared cavity surface model, and determine the actual grouting-filled volume based on the closed bounding box; The grouting fullness is determined based on the actual grouting filling volume and the preset theoretical grouting volume; If the grouting fullness exceeds the preset grouting fullness threshold, the repair of the pipeline is completed. If the grout fullness does not exceed the grout fullness threshold, the grouting path of the location to be repaired is redefined, thereby driving the robotic arm to move along the redefined grouting path to grout the location to be repaired, and thus updating the grout fullness.

[0022] In the above scheme, the robotic arm is driven to move along the planned grouting path, and the grouting head is simultaneously controlled to perform grouting. After the robotic arm completes the movement of the grouting path, a 3D point cloud model of the grouting location to be repaired is constructed. The 3D point cloud model of the grouting location can reflect the surface morphology of the location to be repaired after grouting. Then, the 3D point cloud model of the grouting location and the 3D point cloud model of the tunnel segment are registered using a point cloud registration algorithm, so that the first 3D point cloud model of the grouting location and the first 3D point cloud model of the tunnel segment can be compared in the same coordinate system. Afterwards, the first 3D point cloud model of the grouting location and the first 3D point cloud model of the tunnel segment are reconstructed to obtain a post-grouting surface model that reflects the surface morphology before and after filling. The process involves creating a surface model and a cavity surface model before grouting, followed by constructing a bounding box around the grouting surface model after grouting and the cavity surface model before grouting. This bounding box determines the actual grouting volume, allowing for precise calculation of the grouting effect. Finally, the grouting fullness is calculated based on the actual grouting volume. If the grouting fullness does not exceed a preset threshold, it indicates an under-filled area. In this case, the robotic arm is re-driven to move along the newly determined grouting path to grout the area to be repaired until the grouting fullness exceeds the preset threshold. This ensures that the grouting meets the requirements for pipeline repair, improves the accuracy of grouting, and consequently improves the accuracy of pipeline repair.

[0023] Accordingly, this invention provides a pipeline repair system based on multi-mechanism synergy, including: a contact force mechanism model construction module, a vacuum adsorption gripper adjustment module, a segment assembly motion trajectory construction module, a segment assembly module, a grouting path determination module, and a grouting module; The contact force mechanism model construction module is used to construct a three-dimensional point cloud model of the pipeline, determine the attitude deviation data of the preset pipeline repair equipment based on the three-dimensional point cloud model of the pipeline, and construct the contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment based on the attitude deviation data. The vacuum adsorption gripper adjustment module is used to adjust the vacuum adsorption gripper of the pipeline repair equipment based on the contact force mechanism model until the pipeline repair equipment meets the preset stable operation requirements. The segment assembly motion trajectory construction module is used to obtain the joint parameters of the robotic arm of the pipeline repair equipment, and construct the kinematic mechanism model of the robotic arm based on the joint parameters; and determine the segment assembly motion trajectory of the robotic arm based on the pipeline three-dimensional point cloud model and the kinematic mechanism model. The segment assembly module is used to drive the robotic arm to move along the segment assembly trajectory based on a preset dynamic mechanism and a preset impedance control mechanism, so that the robotic arm assembles the preset segment to be assembled at the preset repair position. The grouting path determination module is used to construct a three-dimensional point cloud model of the segment to be repaired after the assembly of the segment to be assembled is completed; and to determine the grouting path of the segment to be repaired based on the three-dimensional point cloud model of the segment. The grouting module is used to drive the robotic arm to move along the grouting path to grout the location to be repaired, thereby completing the repair of the pipeline.

[0024] Understandably, compared to existing technologies, this system, by constructing a 3D point cloud model of the pipeline, can provide an accurate spatial reference for the subsequent adjustment of the vacuum adsorption gripper of the pipeline repair equipment and the assembly of pipe segments. Next, the system determines the attitude deviation data using the 3D point cloud model of the pipeline and constructs a contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment based on this data. This allows for the adjustment of the vacuum adsorption gripper of the pipeline repair equipment using the contact force mechanism model, ensuring that the pipeline repair equipment meets preset stable operating requirements and providing a stable operating platform for subsequent segment assembly and grouting. Finally, the system acquires the joint parameters of the robotic arm of the pipeline repair equipment and constructs a kinematic mechanism model of the robotic arm, enabling… This invention models the movement of a robotic arm within a pipeline and, combined with a 3D point cloud model of the pipeline, plans the segment assembly trajectory of the robotic arm. This ensures that the segment assembly trajectory not only meets the physical motion design requirements of the robotic arm but also adapts to the complex environment inside the pipeline. Then, through dynamic and impedance control mechanisms, the robotic arm is driven to assemble the segments at the preset repair locations, achieving precise segment assembly. After segment assembly, a 3D point cloud model of the segment at the repair location is constructed. Based on this model, the grouting path for the repair location is determined, and the robotic arm is driven to grout along the path. This enables accurate control of the entire pipeline repair process in complex pipeline environments. This invention, through multi-mechanism collaborative control using kinematic, dynamic, and impedance control mechanisms, achieves the completion of multiple operational stages in the pipeline repair process with a single pipeline repair device. This avoids the cumbersome process transitions and uncertainties caused by manual intervention resulting from multi-device collaboration, which lead to low pipeline repair efficiency and accuracy, thus improving the accuracy and efficiency of pipeline repair. Attached Figure Description

[0025] Figure 1 A flowchart illustrating the steps of a pipeline repair method based on multi-mechanism synergy, provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of a pipeline repair device provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a robotic arm for a pipeline repair device provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the main component of a pipeline repair device provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of a grouting tank for a pipeline repair device provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of a pipeline repair system based on multi-mechanism synergy, provided as an embodiment of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] Example 1 Please refer to Figure 1 , Figure 1 The flowchart of a pipeline repair method based on multi-mechanism synergy provided in this embodiment of the invention includes steps S101 to S106.

[0028] In an optional embodiment, before detailing the pipeline repair method of this embodiment, this embodiment describes the pipeline repair equipment used in this embodiment. Please refer to... Figure 2 , Figure 3 , Figure 4 and Figure 5 , Figure 2 This is a schematic diagram of the structure of a pipeline repair device provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a robotic arm for a pipeline repair device provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the main component of a pipeline repair device provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of a grouting tank for a pipeline repair device provided in an embodiment of the present invention; as shown below. Figure 2As shown, the pipeline repair equipment includes: a tracked walking mechanism 1, a main component 2, a robotic arm 3, an adsorption gripper 4, and a slurry storage tank 5; wherein, the tracked walking mechanism 1 is located at the bottom of the pipeline repair equipment and is used to support the pipeline repair equipment for movement and positioning. Figure 2 and Figure 4 As shown, the main component 2 is located on the upper part of the tracked walking mechanism. The main component 2 includes an integrated module 2a, a camera 2b, and a 3D laser scanner 2c. The integrated module 2a integrates the control unit, battery, and wireless transmission unit of the pipeline repair equipment. The camera 2b is used to capture image data of the pipeline; the 3D laser scanner 2c is used to perform 3D laser scanning of the pipeline. Figure 2 and Figure 3 As shown, the robotic arm 3 includes a grouting head 3a, several joints 3b, a pressure control valve 3c, a flow sensor 3d, and a joint drive unit 3e. The grouting head 3a injects grout into the gaps or voids of the tunnel segments, achieving segment grouting. The joints 3b include rotary joints and telescopic joints. The rotary joints allow the robotic arm to rotate around an axis, providing a change in posture, while the telescopic joints allow the robotic arm to extend or retract in a certain direction, changing the arm span. The pressure control valve 3c controls the grouting pressure. The flow sensor 3d measures the grouting flow rate. The joint drive unit drives the movement of the joints. Adhesive grippers 4 are positioned at the front and rear of the robotic arm. These grippers are used to position and stabilize the front of the equipment. The front and rear grippers cooperate to maintain the balance and stability of the equipment during operation. Figure 2 and Figure 5 As shown, the grout storage tank 5 is located on one side of the pipeline repair equipment and is used to store grout. The grout storage tank 5 includes a flexible grouting pipe 5a, a housing 5b, and a flange interface 5c. The flexible grouting pipe 5a is used to deliver grout to the grouting head 3a. The housing 5b is used to store grout. The flange interface 5c is located on the top of the grout storage tank 5 and is used to receive externally replenished grout.

[0029] It should be noted that in widely used mechanical equipment, robotic arms are typically composed of multiple joints, and the pipe repair equipment described in this embodiment also follows this configuration. Specifically, Figures 2 to 5 The pipeline repair equipment and related structures shown are merely illustrative examples of a pipeline repair equipment described in this embodiment. The pipeline repair solution described in this embodiment is not only applicable to the pipeline repair equipment described in the illustrative example, but also applicable to related equipment that can realize the entire pipeline repair process, such as pipeline assembly and grouting.

[0030] Step S101: Construct a three-dimensional point cloud model of the pipeline, and determine the attitude deviation data of the preset pipeline repair equipment based on the three-dimensional point cloud model of the pipeline; construct the contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment based on the attitude deviation data.

[0031] In an optional embodiment, before performing step S101, the pipeline repair equipment needs to be lowered into the pipeline and the tracked walking mechanism 1 is started to walk to the pipeline to be repaired with the assistance of camera 2b and 3D laser scanner 2c.

[0032] In this embodiment, the construction of a three-dimensional point cloud model of the pipeline, the determination of attitude deviation data of a preset pipeline repair device based on the three-dimensional point cloud model of the pipeline, and the construction of a contact force mechanism model of the vacuum adsorption gripper of the pipeline repair device based on the attitude deviation data, including: Construct a 3D point cloud model of the pipeline; The axial direction vector and pipe wall normal vector of the pipeline are determined based on the three-dimensional point cloud model of the pipeline; the attitude deviation data of the preset pipeline repair equipment are determined based on the axial direction vector and pipe wall normal vector. The resultant external torque and external pitching torque of the pipeline repair equipment are determined based on the attitude deviation data. Obtain the real-time vacuum pressure of each vacuum adsorption gripper of the pipeline repair equipment; A contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed based on the real-time vacuum pressure, the external pitching moment, and the resultant external moment.

[0033] In the above embodiments, firstly, a three-dimensional point cloud model of the pipeline is constructed to accurately extract the axial direction vector and the pipe wall normal vector of the pipeline. This makes the attitude deviation data obtained from the axial direction vector and the pipe wall normal vector more comprehensive and accurate, and the attitude deviation data can reflect the actual tilt and torsion state of the pipeline repair equipment relative to the inner wall of the pipeline. Then, the attitude deviation data is converted into the resultant external torque and external pitching torque that cause the pipeline repair equipment to become unstable. Then, the contact force mechanism model of the vacuum adsorption gripper is constructed using the real-time vacuum pressure, external pitching torque and resultant external torque of the vacuum adsorption gripper. The contact force mechanism model can describe how the real-time vacuum pressure of the vacuum adsorption gripper is balanced with the external load under the current attitude, so as to provide an accurate judgment benchmark for subsequent adjustment of the vacuum adsorption gripper. It can dynamically distribute the vacuum pressure of the vacuum adsorption gripper according to the actual force situation, effectively avoiding the slippage or overturning of the pipeline repair equipment due to insufficient local adsorption, and thus forming a stable working platform, providing a foundation for subsequent pipeline assembly and grouting, and improving the accuracy and efficiency of subsequent pipeline repair.

[0034] In this embodiment, the three-dimensional point cloud model of the pipeline includes: The pipeline repair equipment uses a 3D laser scanner driven by a time-of-flight ranging algorithm to scan the pipeline and obtain a 3D laser scan point cloud dataset of the pipeline. The camera driving the pipeline repair equipment captures an image of the pipeline, obtaining the image pixel coordinate data of the pipeline; A 3D point cloud model of the pipeline is constructed based on the 3D laser scan point cloud dataset and the image pixel coordinate data.

[0035] In an optional embodiment, the 3D laser scanner of the pipeline repair equipment is driven by a Time of Flight (TOF) algorithm to scan the pipeline, and the distance from the target point to the 3D laser scanner is obtained by measuring the time difference between the emission and reflection of the 3D laser pulse. This distance can be expressed as: ; This represents the distance from the target point to the 3D laser scanner. Represents the speed of light. This represents the time difference between the emission and reflection of a three-dimensional laser pulse; Next, a 3D laser scanner is used in the horizontal direction. and vertical scanning angle The distance is converted into three-dimensional spatial points in the three-dimensional laser scanning coordinate system. : ; A point cloud is formed from points in three-dimensional space, thereby constructing a three-dimensional laser scanning point cloud dataset, which is represented as follows: ; This indicates the number of points in the 3D laser scanning point cloud dataset; Then, the pipeline is photographed by a camera to obtain the image pixel coordinate data of the pipeline; in order to obtain richer pipeline environment information, it is necessary to associate the image pixel coordinate data with the three-dimensional laser scanning point cloud dataset to construct the three-dimensional point cloud model of the pipeline; specifically, the association process is shown in the following formula (4); ; This represents the scaling factor, which is set by technicians according to actual needs. Represents the pixel coordinates of the image; Represents the 3D coordinates of the point cloud in the 3D laser scanning point cloud dataset; This represents the intrinsic parameter matrix of the camera; and These represent the rotation matrix and translation vector of the camera relative to the 3D laser scanning coordinate system, respectively.

[0036] It should be noted that Time of Flight (TOF) ranging is a ranging technique that calculates the distance between a signal (such as light, sound waves, or radio waves) and a target object by measuring the time it takes for the signal to travel to and from the transmitter and the target object. Its core principle is based on the physical relationship between signal propagation speed and time.

[0037] In one optional embodiment, the axial direction vector and pipe wall normal vector of the pipeline are extracted from the 3D point cloud model of the pipeline. Simultaneously, the current attitude data of the pipeline repair equipment is obtained through the integrated module 2a of the pipeline repair equipment. The current attitude data, axial direction vector, and pipe wall normal vector of the pipeline repair equipment are compared with the pre-acquired ideal attitude model of the pipeline repair equipment to obtain attitude deviation data of the pipeline repair equipment in pitch angle, roll angle, and axial position. Finally, the resultant external moment and external pitch moment of the pipeline repair equipment are estimated based on the attitude deviation data. The resultant external moment refers to the vector sum of all external moments acting on the equipment, which includes various sources of torque acting on the pipeline repair equipment. The external pitch moment refers to the component of the resultant external moment in the pitch direction; the pitch direction will exhibit a forward and backward tilting trend on the pipeline repair equipment.

[0038] In particular, there are already mature technologies for acquiring attitude deviation data and calculating the resultant external torque and external pitch torque, which will not be described in detail in this embodiment.

[0039] In this embodiment, the contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment, based on the real-time vacuum pressure, the external pitching moment, and the resultant external moment, includes: The normal adsorption force of each vacuum adsorption gripper is determined based on the real-time vacuum pressure. Obtain the unit vector of the tube wall normal at the adsorption point of each vacuum adsorption gripper; The resultant reaction torque of the pipeline repair equipment is constructed based on the normal unit vector of the pipe wall at the adsorption point of each vacuum adsorption gripper and the normal adsorption force. The torque balance constraints of the pipeline repair equipment are constructed based on the resultant reaction torque and the resultant external torque. The pitch balance torque of the pipeline repair equipment is constructed based on the normal adsorption force of each of the vacuum adsorption grippers; The pitch moment balance constraint of the pipeline repair equipment is constructed based on the pitch balance moment and the external pitch moment. Based on the torque balance constraint, the pitch torque balance constraint, and the preset anti-slip constraint, a contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed.

[0040] In one optional embodiment, since there is a spatial offset between the center of mass of the robotic arm and the pipeline repair equipment, the pipeline repair equipment is prone to tipping or deflection during operation; multiple vacuum adsorption grippers arranged in different positions form a spatially distributed reaction force on the pipe wall through distributed adsorption, thereby generating a reverse torque to counteract the working torque of the robotic arm and the grouting reverse thrust torque, and realizing the posture balance of the pipeline repair equipment inside the pipeline.

[0041] The normal adsorption force of vacuum adsorption grippers provides support for pipeline repair equipment, which is an important prerequisite for the realization of pipeline repair equipment. (Definition) Indicates the first A vacuum adsorption gripper ; Therefore, the first The real-time vacuum pressure of a vacuum adsorption gripper is expressed as: ; Get the The effective contact area of ​​each vacuum adsorption gripper is Meanwhile, the external atmospheric pressure is defined as Therefore, the first Normal adsorption force of a vacuum adsorption gripper It can be obtained as shown in formula (5); as shown in formula (5), the distribution of normal adsorption force in space can be achieved by independently adjusting the vacuum pressure of each vacuum adsorption gripper.

[0042] ; Next, the unit vector of the tube wall normal at the adsorption point of each vacuum adsorption gripper is obtained. The unit vector normal to the tube wall at the adsorption point It refers to the first The normal unit vector of the vacuum adsorption gripper at the adsorption point of the pipe wall; with the centroid of the pipe repair equipment. For reference point, the first The position vector between a vacuum adsorption gripper and a reference point is represented as follows: Therefore, the resultant reaction torque It can be expressed as the sum of the torques of the various normal adsorption forces of the vacuum adsorption gripper on the unit normal vector of the tube wall at the adsorption point, as shown in formulas (6) and (7): ; ; When the resultant reaction moment is obtained Resultant external torque Subsequently, the torque balance constraint of the constructed pipeline repair equipment is shown in formula (8); ; Next, because the pipeline repair equipment is prone to generating an external pitching moment that could cause it to overturn in the pitching direction. Therefore, it is still necessary to balance the normal adsorption force of the pipeline repair equipment in the pitch direction to form a pitch balance torque in the pitch direction; the normal adsorption forces generated by the vacuum adsorption gripper located in front of the pipeline repair equipment are defined as follows: and The normal adsorption forces generated by the vacuum adsorption gripper located behind the pipeline repair equipment are respectively and Simultaneously, the center-to-center distance between the front and rear vacuum adsorption grippers is defined as... Therefore, the pitch balancing torque It can be shown in formula (9): ; Obtain the pitch equilibrium moment and external pitch moment Subsequently, the pitching moment balance constraint of the pipeline repair equipment is expressed as shown in formula (10); when formula (10) is satisfied, the external pitching moment can be balanced. The balance is maintained to suppress the tendency of pipeline repair equipment to overturn inside the pipeline.

[0043] ; Furthermore, during the assembly and grouting process, the pipeline repair equipment is affected by the combined effects of gravity, the reaction force of the robotic arm, and dynamic disturbances. The vacuum adsorption gripper inevitably bears an equivalent external load along the tangential direction of the pipe wall at the pipe wall contact interface. To prevent slippage of the vacuum adsorption gripper, the adsorption structure must meet anti-slip stability conditions. Therefore, this embodiment introduces anti-slip constraints, as shown in formula (11). ; In formula (11) Indicates the first The coefficient of friction between the vacuum adsorption gripper and the adsorption point; Indicates the first The equivalent external load borne by a vacuum adsorption gripper; Therefore, a contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed based on formulas (8), (10) and (11).

[0044] In the above embodiments, the resultant reaction torque of the pipeline repair equipment is constructed using the unit vector normal to the pipe wall at the adsorption point of the vacuum adsorption gripper and the real-time vacuum pressure. A torque balance constraint is established between this resultant reaction torque and the external resultant external torque to ensure that the pipeline repair equipment does not experience overall rotational instability within the pipeline. Next, a pitching balance torque is constructed using the real-time vacuum pressure of the vacuum adsorption gripper, and this is combined with the external pitching torque to construct a pitching torque balance constraint for the pipeline repair equipment, thus mitigating the risk of overturning. Finally, an anti-slip constraint is introduced to address the pipeline repair equipment's slippage risk. This study addresses the common sliding problem encountered in pipeline environments. Finally, a contact force mechanism model for the vacuum adsorption gripper of the pipeline repair equipment is constructed using torque balance constraints, pitch torque balance constraints, and anti-slip constraints. This contact mechanics mechanism model provides a comprehensive and accurate adjustment basis for the vacuum adsorption gripper, enabling the pipeline repair equipment to automatically and dynamically adjust the vacuum pressure of each vacuum adsorption gripper in complex, variable, and uncertain pipeline environments. This provides a stable foundation for the precise movement of the subsequent robotic arm and the execution of complex repair tasks, avoiding the problem of poor repair accuracy caused by equipment instability and improving the accuracy of subsequent pipeline repairs.

[0045] Step S102: Adjust the vacuum adsorption gripper of the pipeline repair equipment based on the contact force mechanism model until the pipeline repair equipment meets the preset stable operation requirements.

[0046] In one alternative embodiment, a mathematical solver (such as MATLAB) can be used to solve the contact force mechanism model to obtain the target value of the normal adsorption force of each vacuum adsorption gripper; by adjusting the power output of the vacuum pump built into the vacuum adsorption gripper, the vacuum pressure inside the vacuum adsorption gripper cavity can be adjusted so that the normal adsorption force of the vacuum adsorption gripper reaches the target value of the normal adsorption force, thereby achieving posture stability of the pipeline repair equipment (i.e., preset stable operation requirements).

[0047] In one optional embodiment, after the pipeline repair equipment meets the preset stable operation requirements, segment assembly and grouting operations can be carried out. However, in the actual pipeline repair process, due to factors such as the surface roughness of the pipe wall, the elastic deformation of the suction cup material, and incomplete sealing, there will be minor leaks in the cavity of the vacuum adsorption gripper. To describe the dynamic characteristics of the vacuum pressure change over time in the cavity of the vacuum adsorption gripper, this embodiment introduces a first-order equivalent model to describe the vacuum pressure change process, as shown in formula (12): ; In formula (12), This represents the rate of change of vacuum pressure (Pa / s) within the vacuum adsorption gripper cavity. This indicates the pressure difference (Pa) between the inside and outside of the cavity of the vacuum adsorption gripper. Equivalent leakage resistance (Pa·s / m³); This is the volume factor (m³ / Pa).

[0048] Based on formula (12), it is possible to monitor the vacuum pressure change rate in the vacuum adsorption gripper cavity in real time, so that the vacuum pressure can be dynamically adjusted in the subsequent segment assembly and grouting process, thereby ensuring that the pipeline repair equipment can still provide a stable working platform under the condition of changing working load or attitude disturbance. In this embodiment, the real-time vacuum pressure change rate of each vacuum adsorption gripper is calculated using formula (12) at a frequency of 100Hz. And define the leakage rate threshold. Its value ranges from 1.0 to 5.0 kPa / s. If... If the current leakage is within a controllable range, this condition is defined as a stable holding period. Therefore, the vacuum pump should maintain its current power output or intermittently replenish gas to maintain optimal energy consumption. If... This refers to a situation where the vacuum pressure drops too rapidly; this condition is defined as the active compensation period. The period is based on the real-time vacuum pressure change rate. The slope is adjusted by increasing the motor speed or duty cycle of the vacuum pump through a PID algorithm, thereby increasing the air flow rate to offset the leakage and forcibly maintaining a constant vacuum pressure inside the vacuum adsorption gripper cavity.

[0049] Furthermore, if a single vacuum adsorption gripper (such as the front vacuum adsorption gripper) still cannot maintain a constant vacuum pressure inside the vacuum adsorption gripper cavity under the active compensation period, in order to prevent the pipeline repair equipment from overturning, the normal adsorption force of its diagonal point (i.e. the rear diagonal vacuum adsorption gripper) is reduced according to formula (8); or the posture of the robotic arm is directly adjusted to change the center of gravity of the pipeline repair equipment, and the target value of the normal adsorption force of each vacuum adsorption gripper is recalculated according to the contact force mechanism model, so as to readjust the vacuum adsorption gripper.

[0050] In the above optional embodiments, by continuously monitoring the rate of change of vacuum pressure inside the vacuum adsorption gripper cavity, the vacuum adsorption gripper can be dynamically adjusted during the segment assembly and grouting process, providing a stable working platform for segment assembly and grouting, thus ensuring the accuracy and efficiency of pipeline repair.

[0051] Step S103: Obtain the joint parameters of the robotic arm of the pipeline repair equipment, and construct the kinematic mechanism model of the robotic arm based on the joint parameters; and determine the segment assembly motion trajectory of the robotic arm based on the three-dimensional point cloud model of the pipeline and the kinematic mechanism model.

[0052] In this embodiment, the steps of acquiring the joint parameters of the robotic arm of the pipeline repair equipment, constructing a kinematic mechanism model of the robotic arm based on the joint parameters, and determining the segment assembly motion trajectory of the robotic arm based on the three-dimensional point cloud model of the pipeline and the kinematic mechanism model include: Obtain the joint parameters of the robotic arm of the pipeline repair equipment; Based on the joint parameters, a joint homogeneous transformation matrix between two adjacent joints in the robotic arm is constructed, and an end homogeneous transformation matrix of the robotic arm is constructed based on the homogeneous transformation matrix. The kinematic mechanism model of the robotic arm is constructed based on the joint homogeneous transformation matrix and the end homogeneous transformation matrix; The kinematic mechanism model is solved based on the three-dimensional point cloud model of the pipeline to determine the segment assembly motion trajectory of the robotic arm.

[0053] In the above embodiments, by acquiring the joint parameters of the robotic arm of the pipeline repair equipment and constructing homogeneous transformation matrices between adjacent joints based on the joint parameters, a precise mathematical description of the geometric structure and motion relationship of the robotic arm can be achieved. Then, an end-effector homogeneous transformation matrix is ​​constructed using the homogeneous transformation matrix to determine the pose of the robotic arm's end effector in the base coordinate system. A kinematic mechanism model of the robotic arm is then constructed using the joint homogeneous transformation matrices and the end-effector homogeneous transformation matrix, enabling precise control of the robotic arm. Finally, the kinematic mechanism model is solved using a 3D point cloud model of the pipeline to determine the segment assembly trajectory of the robotic arm. This ensures that the segment assembly trajectory not only meets the physical limitations of the robotic arm itself but also considers the actual internal environment of the pipeline. This allows the pipeline repair equipment to handle pipeline repair needs of different specifications and defect locations, avoiding repeated manual teaching or program adjustments. This not only greatly improves the efficiency of pipeline repair operations but also ensures that the robotic arm can achieve precise pipeline assembly in complex pipeline environments, thereby improving the efficiency and accuracy of pipeline repair.

[0054] In this embodiment, the step of solving the kinematic mechanism model based on the three-dimensional point cloud model of the pipeline to determine the segment assembly motion trajectory of the robotic arm includes: Based on the three-dimensional point cloud model of the pipeline, the starting joint motion variable data and the end-effector starting position data of the robotic arm at the preset gripping point of the pipe segment to be assembled are determined; Based on the three-dimensional point cloud model of the pipeline, the termination joint motion variable data and end-effector termination position data of the robotic arm at the preset repair position are determined. The kinematic mechanism model is solved based on the initial joint motion variable data to obtain the initial Jacobian matrix of the robotic arm at the grasping point; and the initial end-effector velocity and initial end-effector acceleration of the robotic arm at the grasping point are determined based on the initial Jacobian matrix. The kinematic mechanism model is solved based on the termination joint motion variable data to obtain the termination Jacobian matrix of the robotic arm at the repair position; and the end-effector termination velocity and end-effector termination acceleration of the robotic arm at the repair position are determined based on the termination Jacobian matrix. The target motion trajectory function of the robotic arm is constructed based on a preset fifth-order polynomial interpolation algorithm; Based on the starting position data, the starting velocity of the end effector, the starting acceleration of the end effector, the ending position data, the ending velocity of the end effector, and the ending acceleration of the end effector, the target motion trajectory function is solved to determine the segment assembly motion trajectory of the robotic arm.

[0055] In the above embodiments, based on the three-dimensional point cloud model of the pipeline, the starting joint motion variable data and end-effector starting position data of the robotic arm at the preset gripping point of the segment to be assembled, as well as the ending joint motion variable data and end-effector ending position data of the robotic arm at the preset repair position, can be accurately identified. Then, the kinematic mechanism model is solved by the starting joint motion variable data to obtain the starting Jacobian matrix of the robotic arm at the gripping point, and thus the end-effector starting velocity and end-effector starting acceleration of the robotic arm at the gripping point are obtained. The kinematic mechanism model is solved by the ending joint motion variable data to obtain the end-effector Jacobian matrix of the robotic arm at the repair position, and thus the end-effector starting velocity and end-effector starting acceleration of the robotic arm at the gripping point are obtained. Next, a target motion trajectory function for the robotic arm is constructed using a fifth-order polynomial interpolation algorithm. Compared to traditional trapezoidal velocity planning, the segment assembly motion trajectory calculated by the fifth-order polynomial interpolation algorithm can avoid vibration of the robotic arm in confined spaces. Finally, the starting position data, end-effector initial velocity, end-effector initial acceleration, end-effector termination position data, end-effector termination velocity, and end-effector termination acceleration are used as boundary conditions and substituted into the target motion trajectory function for solving. This yields a segment assembly motion trajectory in which the joint angles of the robotic arm change continuously and smoothly over time from the starting point to the end point. This ensures the stability of joint movements during segment assembly, thereby ensuring the stability of the segment's posture during high-speed, long-distance transportation. Consequently, precise segment assembly can be achieved, improving the accuracy of pipeline repair.

[0056] Step S104: Drive the robotic arm to move along the assembly trajectory of the tube segment based on the preset dynamic mechanism and preset impedance control mechanism, so that the robotic arm assembles the preset tube segment to be assembled at the preset repair position.

[0057] In this embodiment, the step of driving the robotic arm to move along the assembly trajectory of the pipe segment based on a preset dynamic mechanism and a preset impedance control mechanism, so that the robotic arm assembles the preset pipe segment to be assembled at the preset repair position, includes: During each control cycle of the robotic arm, the real-time end contact force, real-time joint motion variable values, and real-time joint velocity vector of the robotic arm are acquired. Based on the segment assembly motion trajectory, end-effector contact force, joint real-time motion variable values, and joint real-time velocity vector, an end-effector impedance control mechanism model of the robotic arm is constructed, and the joint correction acceleration and joint correction velocity of the robotic arm are determined based on the end-effector impedance control mechanism model. The joint correction acceleration and joint correction velocity are modeled based on a preset Lagrange dynamics modeling algorithm to determine the joint driving torque model of the robotic arm. Solve the joint driving torque model to obtain the joint driving torque of the robotic arm in the current control cycle; Based on the joint driving torque, the robotic arm moves along the assembly trajectory of the tube segment within the current control cycle, so that the robotic arm assembles the preset tube segment to be assembled at the preset repair position.

[0058] In the above embodiments, the real-time end contact force, real-time joint motion variable values, and real-time joint velocity vector of the robotic arm are acquired in each control cycle of the robotic arm. Then, the end impedance control mechanism model of the robotic arm is constructed using the segment assembly motion trajectory, the real-time end contact force, the real-time joint motion variable values, and the real-time joint velocity vector. The end impedance control mechanism model enables the end of the robotic arm to have compliant characteristics similar to spring damping, which can ensure the accuracy of segment assembly while improving operational safety. Then, the joint correction acceleration and joint correction velocity are modeled using the Lagrange dynamics modeling algorithm to determine the joint driving torque model of the robotic arm. The joint driving torque model can ensure that the joint driving torque of the robotic arm not only considers the compliance requirements of segment assembly, but also considers the physical limitations of the robotic arm itself in the pipeline environment, enabling the robotic arm to perform segment assembly tasks compliantly and accurately in complex pipeline environments, improving the accuracy of segment assembly, and thus improving the accuracy of pipeline repair.

[0059] In this embodiment, the step of constructing an end-effector impedance control mechanism model for the robotic arm based on the segment assembly motion trajectory, real-time end-effector contact force, real-time joint motion variable values, and real-time joint velocity vector, and determining the joint correction acceleration and joint correction velocity of the robotic arm based on the end-effector impedance control mechanism model, includes: The kinematic mechanism model is solved based on the real-time motion variable values ​​of the joints to determine the real-time end position, joint position vector, and coordinate system unit vector of the robotic arm. The real-time Jacobian matrix of the robotic arm is constructed based on the joint position vector and the coordinate system unit vector, and the real-time end-effector velocity and real-time end-effector acceleration of the robotic arm are determined based on the real-time Jacobian matrix and the joint real-time velocity vector. The end target position, end target velocity, and end real-time acceleration of the robotic arm in the current control cycle are determined based on the segment assembly motion trajectory. Based on the real-time end position, real-time end velocity, real-time end acceleration, real-time end contact force, end target position, end target velocity, and real-time end acceleration, an end impedance control mechanism model for the robotic arm is constructed. The end-effector impedance control mechanism model is solved to determine the end-effector correction acceleration and end-effector correction velocity of the robotic arm. The joint correction acceleration and joint correction velocity of the robotic arm are determined based on the end-effector correction acceleration and end-effector correction velocity.

[0060] In the above embodiments, the kinematic mechanism model is solved by using real-time joint motion variable values ​​to determine the real-time position of the robotic arm's end effector, joint position vector, and coordinate system unit vector. Then, a real-time Jacobian matrix that accurately describes the joints between the robotic arm's joints and the end effector is constructed using the joint position vector and coordinate system unit vector. Next, the real-time joint velocity vectors are converted into the real-time velocity and acceleration of the robotic arm's end effector using the real-time Jacobian matrix. Then, the target end effector position, target end effector velocity, and real-time end effector acceleration of the robotic arm in the current control cycle are determined from the segment assembly motion trajectory. Finally, the real-time end effector position and real-time end effector velocity are combined with the real-time end effector position and real-time end effector velocity. A mechanism model for end-effector impedance control is constructed using real-time end-effector acceleration and contact force. This model enables precise calculation of the end-effector correction acceleration and velocity required to achieve the desired impedance characteristics, allowing the robotic arm's end-effector to exhibit spring-damped compliance characteristics. This ensures accurate segment assembly while improving operational safety. Finally, the end-effector correction acceleration and velocity are converted into directly controllable joint correction acceleration and velocity within the robotic arm, achieving precise control over segment assembly and improving the accuracy of pipeline repair.

[0061] In an optional embodiment, as described in steps S103 to S104, the end effector of the robotic arm needs to achieve precise positioning within a confined space and make controlled contact with the tube segment and its wall. Therefore, the robotic arm not only needs accurate pose control capabilities but also needs to maintain stability and compliance during contact to avoid damage to the tube segment structure. Thus, this embodiment introduces the synergy of kinematic mechanism models, dynamic mechanisms, and impedance control mechanisms to achieve precise control of the robotic arm.

[0062] First, the pose relationship of the robotic arm needs to be modeled. Since most robotic arms currently use a series joint structure, the pose of its end effector relative to the base coordinate system of the pipeline repair equipment can be described by the DH (Denavit-Hartenberg) parametric method. The homogeneous transformation matrices of each joint are multiplied in the order of the joints to obtain the end effector homogeneous transformation matrix. The end effector homogeneous transformation matrix can describe the spatial position and orientation of the robotic arm under different joint configurations.

[0063] Specifically, the joint parameters of the robotic arm of the pipeline repair equipment are obtained, whereby the following is defined: The first part of the robotic arm The first joint; for the robotic arm's first joint; Each joint has parameters including: link length. Linkage torsion angle Joint displacement and joint angle Therefore, two adjacent joints in the robotic arm (i.e., the first joint) The joint relative to the first The joint homogeneous transformation matrix between (joints) The calculation method is expressed as shown in the following formula (13); where Indicates the first The motion variables of a joint are as follows: if the joint is a rotational joint, then the motion variable is the joint angle. If the joint is a translational joint, then the motion variable is the joint displacement. Therefore, the motion variables of a joint can be understood as the state of the joint; after obtaining the homogeneous transformation matrix of the joints, the homogeneous transformation matrix of the joints is multiplied according to the joint order to obtain the homogeneous transformation matrix of the distal end. The specific calculation process is shown in formula (14); ; After obtaining the terminal homogeneous transformation matrix and joint homogeneous transformation matrix Then, the kinematic mechanism model of the robotic arm is formed using formulas (13) and (14).

[0064] In an optional embodiment, after forming the kinematic mechanism model of the robotic arm, in order to map the joint motion to the end effector motion, this embodiment introduces a Jacobian matrix, which can map the joint velocity to the end effector velocity; the specific mapping relationship is shown in formula (15): ; In formula (15), This represents the end effector velocity vector (m / s or rad / s) of the robotic arm. Represents the Jacobian matrix; Represents the joint velocity vector (m / s or rad / s); The Jacobian matrix can be calculated based on the joint motion variables of the robotic arm; where the joint motion variables are specifically represented as shown in formula (16): ; The Jacobian matrix can be expressed in the form shown in formula (17). Indicates the first The contribution of each joint to the end effector velocity is specifically obtained from the joint homogeneous transformation matrix corresponding to the joint motion variables of the robotic arm; if the th joint... If the nth joint is a rotary joint, then its contribution is as shown in formula (18); if the nth joint is a rotary joint, then its contribution is as shown in formula (18); If each joint is a moving joint, then its contribution is as shown in formula (19); ; in, Indicates the first The unit vector of each joint in the base coordinate system along the Z-axis; Indicates the first The position vectors of each joint at the origin of the base coordinate system; This represents the position vector of the robotic arm's end effector. and It is obtained through the joint homogeneous transformation matrix corresponding to the joint motion variables of the robotic arm; Based on the above formulas (15) to (18), a mapping relationship between joint motion and end-effector motion is established. Therefore, in the planning of the segment assembly motion trajectory, this embodiment first extracts the starting joint motion variable data and end-effector starting position data of the robotic arm at the preset gripping point of the segment to be assembled from the three-dimensional point cloud model of the pipeline, and extracts the ending joint motion variable data and end-effector ending position data of the robotic arm at the preset repair position; as described above, the starting joint motion variable data can represent the state of different joints (rotational joints or displacement joints) of the robotic arm at the gripping point; the target joint motion variable data can represent the state of different joints (rotational joints or displacement joints) of the robotic arm at the repair position; Next, the initial joint motion variable data are substituted into the kinematic mechanism model for solution to obtain the initial joint homogeneous transformation matrix of the robotic arm at the grasping point; then, the data required for formulas (17) to (18) are extracted from the initial joint homogeneous transformation matrix to calculate the initial Jacobian matrix of the robotic arm at the grasping point; then, the initial Jacobian matrix is ​​substituted into formula (15), and then the joint velocity vector in formula (15) is set (the specific value is set according to the actual needs) to obtain the end-effector initial velocity of the robotic arm at the grasping point; after determining the end-effector initial velocity, the end-effector initial acceleration velocity can be solved using the end-effector initial velocity; Similarly, the data of the termination joint motion variables are substituted into the kinematic mechanism model for solution to obtain the homogeneous transformation matrix of the termination joint of the robot arm at the position to be repaired; then the data required for formulas (17) to (18) are extracted from the homogeneous transformation matrix of the termination joint to calculate the termination Jacobian matrix of the robot arm at the position to be repaired; then the termination Jacobian matrix is ​​substituted into formula (15), and then the joint velocity vector in formula (15) is set (the specific value is set according to the actual needs) to obtain the end termination velocity of the robot arm at the position to be repaired; after determining the end termination velocity, the end termination acceleration velocity can be solved by the end termination velocity; Then, the target motion trajectory function of the robotic arm is constructed according to the fifth-order polynomial interpolation algorithm; the target motion trajectory function is shown in formulas (19), (20) and (21), and formulas (20) and (21) are obtained by differentiating formula (19); Indicates the end effector of the robotic arm at The target location at any given time; Indicates the end effector of the robotic arm at The target speed at any given moment; Indicates the end effector of the robotic arm at The target acceleration at any given moment; , , , , , and All are coefficients; ; ; ; Using the initial position data, initial end velocity, initial end acceleration, final end position data, final end velocity, and final end acceleration as boundary conditions, the coefficients of the target motion trajectory function are solved to generate the segment assembly motion trajectory of the robotic arm.

[0065] In one optional embodiment, the segment assembly motion trajectory of the robotic arm is obtained by solving the equation, and the robotic arm is driven to move along the segment assembly motion trajectory to achieve segment assembly; within each control cycle of the robotic arm, the real-time contact force at the end of the robotic arm is acquired. Real-time motion variables of the joint and real-time velocity vector of the joint; Similar to the previous optional embodiment, the real-time motion variable values ​​of the joints are substituted into the kinematic mechanism model for solution to obtain the real-time homogeneous transformation matrix of the robotic arm; then, the real-time end position, joint position vector (i.e., the position vector of the joint at the origin of the base coordinate system) and coordinate system unit vector (i.e., the Z-axis unit vector of the joint in the base coordinate system) of the robotic arm are extracted from the real-time homogeneous transformation matrix; then, the real-time Jacobian matrix of the robotic arm is constructed using the joint position vector and the coordinate system unit vector, as shown in formulas (17) to (19); then, the real-time end velocity and real-time end acceleration of the robotic arm are determined using the real-time Jacobian matrix and the real-time joint velocity vector as shown in formula (15); Next, the end target position, end target velocity, and real-time end acceleration of the robotic arm in the current control cycle are extracted from the segment assembly motion trajectory. Therefore, the end-effector impedance control mechanism model of the constructed robotic arm is shown in formula (22); ; In formula (22), Indicates the real-time contact force at the end; Indicates the real-time acceleration at the end point; Indicates the real-time speed at the terminal; Indicates the real-time location of the terminal; Indicates the terminal target acceleration; Indicates the velocity of the terminal target; Indicates the location of the terminal target; This represents the virtual mass (kg), which is used to set the equivalent inertia of the pipeline repair equipment. ; This represents virtual damping (N·s / m), which is used to adjust the damping ratio of the system. ; This represents virtual stiffness (N / m), which is used to determine the degree of compliance of the end effector with the environment. ; After obtaining the end impedance control mechanism model, the mathematical solver is used to solve the end impedance control mechanism model to obtain the end correction acceleration and end correction velocity of the robotic arm; then, according to formula (15), the end correction acceleration and end correction velocity of the robotic arm are converted into the joint correction acceleration and joint correction velocity of the robotic arm. Furthermore, the joint correction acceleration and joint correction velocity are modeled by a preset Lagrange dynamics modeling algorithm to determine the joint driving torque model of the robotic arm; the joint driving torque model is shown in formula (23); ; In formula (23), This represents the joint driving torque (N·m). Let be the inertia matrix (kg·m²). This is the joint acceleration vector (rad / s² or m / s²). For Coriolis force and centrifugal force terms (kg·m² / s); For gravity (N·m); This refers to the real-time contact force at the end of the robotic arm. This represents the transpose of the real-time Jacobian matrix; It should be noted that the inertia matrix The inertial characteristics of the system are calculated by summing the mass distribution of each link in the robotic arm and its moment of inertia about the joint axis; Coriolis force and centrifugal force terms are also included. Calculated using Christofel notation, it is used to describe the velocity coupling effect during high-speed motion of multiple joints; gravity term. By analyzing the total potential energy of the pipeline repair equipment Motion variables of joints We obtain it by taking the partial derivative, i.e. ; Substitute the joint correction acceleration and joint correction velocity into formula (23) to obtain the joint driving torque of the robotic arm in the current control cycle; and drive the robotic arm to move along the assembly trajectory of the tube segment in the current control cycle through the joint driving torque of the robotic arm in the current control cycle, so that the robotic arm assembles the preset tube segment to be assembled at the preset repair position.

[0066] In one optional embodiment, after the assembly of the pipe segments to be assembled is completed, a three-dimensional point cloud model of the pipe segments after assembly is constructed. The joint spacing of the adjacent pipe segment joint area at the location to be repaired is solved by the three-dimensional point cloud model of the pipe segments after assembly and the three-dimensional point cloud model of the pipe. Then, the assembly gap error is calculated based on the joint spacing. The calculation of the assembly gap error is shown in formula (24): ; In formula (24), To account for assembly gap error; This refers to the seam spacing; This refers to the theoretical joint spacing; if it's due to assembly joint error... If the gap is less than the preset assembly gap threshold (the specific value can be set according to actual needs, and is not limited in this embodiment), it indicates that the segment assembly meets the requirements, and grouting in subsequent steps S105 to S106 can proceed; if the gap is due to assembly gap error... If the gap is greater than or equal to the preset assembly gap threshold, the segment assembly needs to be repeated, that is, steps S103 to S104 need to be repeated.

[0067] Step S105: After assembling the segment to be assembled, construct a three-dimensional point cloud model of the segment at the location to be repaired; and determine the grouting path at the location to be repaired based on the three-dimensional point cloud model of the segment.

[0068] In this embodiment, after assembling the segment to be assembled, constructing a three-dimensional point cloud model of the segment at the location to be repaired; and determining the grouting path at the location to be repaired based on the three-dimensional point cloud model of the segment, includes: After the assembly of the segment to be assembled is completed, a three-dimensional point cloud model of the segment at the location to be repaired is constructed. Seed points are selected from the three-dimensional point cloud model of the tunnel segment based on a preset curvature threshold and the curvature of each point cloud in the model. Centered on the seed point, the point cloud of the three-dimensional point cloud model of the pipe segment is clustered based on a preset region growing algorithm to obtain a set of point clouds of the cavity region. Boundary fitting is performed on the point cloud set of the cavity region to determine the cavity contour boundary, and the grouting start point is determined based on the cavity contour boundary; Centered on the grouting starting point, the cavity contour boundary is sliced ​​based on a preset slicing scanning algorithm to generate an initial grouting path that determines the location to be repaired; The initial grouting path is verified based on the kinematic mechanism model to determine the grouting path for the location to be repaired.

[0069] In an optional embodiment, after the assembly of the segment to be assembled is completed, a three-dimensional point cloud model of the segment at the location to be repaired is similarly constructed; then the curvature of each point cloud in the three-dimensional point cloud model of the segment is calculated, and a curvature threshold is set. If the curvature of the point cloud is greater than the curvature threshold If the seed point is selected, then the point cloud is determined as the seed point. Then, using the seed point as the center, the Region Growing Algorithm is used to cluster the point clouds of the 3D point cloud models of the pipe segments that satisfy the spatial connectivity condition and whose depth values ​​are greater than the pipe wall reference plane, thus obtaining the cavity region point cloud set. Then the point cloud of the cavity region is aggregated. Projecting onto the tangent plane of the pipe wall using the convex hull algorithm or The algorithm (Alpha Shape Algorithm) performs boundary fitting on the point cloud set of the cavity region to determine the cavity contour boundary. Then calculate the cavity profile boundary. Centroid position This serves as the starting point for grouting. Finally, using the grouting starting point as the center, the Slice Scanning Method slices the cavity contour boundary. Specifically, the cavity contour boundary is sliced ​​at equal intervals along the main axis direction of the robotic arm's end effector. (Determined by the spray width of the grouting head), generating an initial grouting path to determine the location to be repaired. The initial grouting path follows a "U" or "S" shaped scanning strategy to improve grouting coverage. Finally, the initial grouting path... By substituting the kinematic mechanism model for verification, singular points or collision interference points are identified, and the grouting path of the location to be repaired is obtained.

[0070] In the above embodiments, a three-dimensional point cloud model of the pipe segment at the location to be repaired is constructed, which can accurately represent the morphology of the cavity region. Next, the point cloud is filtered using a curvature threshold and the curvature of the point cloud to obtain seed points that can represent the cavity edge or areas of drastic change. Then, starting from the seed points, a region growing algorithm is used to aggregate point clouds with similar geometric features to the seed points into a cavity region point cloud set, thereby accurately segmenting the point cloud representing the cavity region from the entire model. Finally, boundary fitting is performed on the cavity region point cloud set to determine the cavity contour boundary and the grouting start point. Using the grouting start point as the center, a slicing scanning algorithm is used to slice the cavity contour boundary dynamically. An initial grouting path is generated to determine the location to be repaired. Finally, the initial grouting path is verified by a kinematic mechanism model to obtain the grouting path for the location to be repaired. Compared with the fixed grouting path of the traditional method, the grouting path is dynamically generated by the region growing algorithm, boundary fitting, slice scanning algorithm and kinematic mechanism model. This not only enables grouting to conform to various irregular cavity shapes and ensures that there are no dead corners in grouting, but also ensures that the planned grouting path is within the reachable space of the robotic arm and that the joint movement is smooth without abrupt changes by the kinematic mechanism model. This effectively avoids the problem of incomplete or excessive grouting caused by irregular cavity shapes, improves the accuracy and efficiency of grouting, and thus improves the accuracy and efficiency of pipeline repair.

[0071] Step S106: Drive the robotic arm to move along the grouting path to grout the location to be repaired, thereby completing the repair of the pipeline.

[0072] In this embodiment, driving the robotic arm to move along the grouting path to grout the location to be repaired, thereby completing the repair of the pipeline, includes: Drive the robotic arm to move along the grouting path and control the grouting head of the robotic arm to grout the grouting path to grout the location to be repaired; After the robotic arm completes the movement of the grouting path, a three-dimensional point cloud model of the grouting at the location to be repaired is constructed. The grouting 3D point cloud model and the segment 3D point cloud model are registered according to a preset point cloud registration algorithm to obtain the first grouting 3D point cloud model corresponding to the grouting 3D point cloud model and the first segment 3D point cloud model corresponding to the segment 3D point cloud model. The first grouting 3D point cloud model is reconstructed to obtain the grouting-filled surface model; The surface of the cavity before grouting is obtained by reconstructing the three-dimensional point cloud model of the first segment. Construct a closed bounding box between the grouting-filled surface model and the grouting-prepared cavity surface model, and determine the actual grouting-filled volume based on the closed bounding box; The grouting fullness is determined based on the actual grouting filling volume and the preset theoretical grouting volume; If the grouting fullness exceeds the preset grouting fullness threshold, the repair of the pipeline is completed. If the grout fullness does not exceed the grout fullness threshold, the grouting path of the location to be repaired is redefined, thereby driving the robotic arm to move along the redefined grouting path to grout the location to be repaired, and thus updating the grout fullness.

[0073] In one optional embodiment, the robotic arm is driven to move along the grouting path, and the grouting head of the robotic arm is controlled to grout the grouting path. At the same time as grouting, the flow rate of the grout is monitored in real time by the flow sensor 3d, and the flow rate of the grout in the grouting head is controlled by the pressure control valve 3c, thereby avoiding overpressure that could damage the pipe segment or joint structure.

[0074] Furthermore, since grouting is performed using the grouting head of a robotic arm, the robotic arm is also controlled. Therefore, the kinematic mechanism model, dynamic mechanism, and impedance control mechanism of steps S103 to S104 can be used to regulate the robotic arm during the grouting process. Since the regulation method has been specifically described in steps S103 to S104, it will not be described again in this embodiment.

[0075] In one optional embodiment, after the robotic arm completes the movement of the grouting path, a three-dimensional point cloud model of the grouting at the location to be repaired is constructed; The grouting surface point cloud set of the grouting 3D point cloud model and the point cloud set of the surface of the segment before grouting in the three-dimensional point cloud model. Substituting into the calculation formula of the Iterative Closest Point (ICP) algorithm, i.e. formula (25), the Iterative Closest Point (ICP) algorithm is used for registration, thereby eliminating the pose error caused by the movement of the pipeline repair equipment; ; In formula (25), This refers to points in a reference point cloud. Corresponding points in the point cloud to be registered Indicates the first One point, Indicates the number of points; and Represents the optimal rigid body transformation between point clouds; The first 3D point cloud model corresponding to the grouting 3D point cloud model and the first 3D point cloud model corresponding to the segment 3D point cloud model are obtained through the Iterative Closest Point (ICP) algorithm; the point cloud set of the first grouting 3D point cloud model is represented as follows: The point cloud set of the three-dimensional point cloud model of the first segment is represented as: Then, the Delaunay triangulation algorithm or the Poisson reconstruction algorithm were used to process the point cloud set of the first grouting 3D point cloud model. Perform surface reconstruction to obtain the grouting-filled surface model. The point cloud set of the 3D point cloud model of the first segment is processed using the Delaunay triangulation algorithm or the Poisson reconstruction algorithm. Perform surface reconstruction to obtain the grouting-filled surface model. Next, the surface model after grouting is calculated. and grouting after filling surface model The enclosed box between them, and the actual grouting filling volume is determined based on the enclosed box. Actual grouting volume The calculation is shown in formula (26): ; In formula (26), This represents the volume of the filled surface model in the normal direction after grouting; This represents the volume of the filled surface model in the normal direction after grouting; Indicates the projected range of the grouting area; Represents depth information; Finally, the theoretical grouting volume is set as Therefore, the fullness of grouting As shown in formula (27), ; A grout saturation threshold of 95% is defined. If the grout saturation exceeds 95%, the grouting effect is considered excellent, and the pipeline repair is completed. If the grout saturation does not exceed 95%, the grouting effect is considered poor, the grouting path of the location to be repaired is redefined, and the robotic arm is re-driven to move along the redefined grouting path to grout the location to be repaired, thereby updating the grout saturation.

[0076] In the above embodiments, the robotic arm is driven to move along the planned grouting path, and the grouting head is simultaneously controlled to perform grouting. After the robotic arm completes the movement of the grouting path, a three-dimensional point cloud model of the grouting location to be repaired is constructed. The three-dimensional point cloud model of the grouting location can reflect the surface morphology of the location to be repaired after grouting. Then, the three-dimensional point cloud model of the grouting location and the three-dimensional point cloud model of the tunnel segment are registered using a point cloud registration algorithm, so that the first three-dimensional point cloud model of the grouting location and the first three-dimensional point cloud model of the tunnel segment can be compared in the same coordinate system. Afterwards, the first three-dimensional point cloud model of the grouting location and the first three-dimensional point cloud model of the tunnel segment are reconstructed to obtain a post-grouting surface model that reflects the surface morphology before and after filling. The process involves creating a surface model and a cavity surface model before grouting, followed by constructing a bounding box around the grouting surface model after grouting and the cavity surface model before grouting. This bounding box determines the actual grouting volume, allowing for precise calculation of the grouting effect. Finally, the grouting fullness is calculated based on the actual grouting volume. If the grouting fullness does not exceed a preset threshold, it indicates an under-filled area. In this case, the robotic arm is re-driven to move along the newly determined grouting path to grout the area to be repaired until the grouting fullness exceeds the preset threshold. This ensures that the grouting meets the requirements for pipeline repair, improves the accuracy of grouting, and consequently improves the accuracy of pipeline repair.

[0077] In an optional embodiment, after the pipeline repair is completed, all data involved in the pipeline repair process (i.e., all data obtained in steps S101 to S106 above) are stored in chronological order to form a complete construction dataset for pipeline repair. Then, the complete construction dataset is transmitted to the ground control platform via the wireless transmission unit within the integration module 2a for subsequent quality monitoring and archiving of construction results. Finally, the vacuum adsorption state of the vacuum gripper is released, allowing the pipeline repair equipment to resume its walking posture. Driven by the tracked walking mechanism 1, it then leaves the current construction position and moves along the pipeline to the next construction point.

[0078] This embodiment constructs a 3D point cloud model of the pipeline, providing an accurate spatial reference for the subsequent adjustment of the vacuum adsorption gripper and segment assembly of the pipeline repair equipment. Next, the 3D point cloud model is used to determine attitude deviation data, and this data is used to construct a contact force mechanism model for the vacuum adsorption gripper of the pipeline repair equipment. This allows for adjustment of the vacuum adsorption gripper to ensure the pipeline repair equipment meets preset stable operation requirements, providing a stable operating platform for subsequent segment assembly and grouting. Finally, the joint parameters of the robotic arm of the pipeline repair equipment are obtained, and a kinematic mechanism model of the robotic arm is constructed, enabling adjustments to the robotic arm's movement within the pipeline. The invention models the motion within the pipeline and then plans the segment assembly trajectory of the robotic arm using a 3D point cloud model of the pipeline. This ensures that the segment assembly trajectory not only meets the physical motion design requirements of the robotic arm but also adapts to the complex environment inside the pipeline. Subsequently, the robotic arm is driven by dynamic and impedance control mechanisms to assemble the segments at the preset repair locations, achieving precise segment assembly. After assembly, a 3D point cloud model of the segment at the repair location is constructed. Based on this model, the grouting path is determined, and the robotic arm is driven to grout the repair location along the path. This achieves accurate control of the entire pipeline repair process in complex environments. This invention utilizes a multi-mechanism collaborative control approach, combining kinematic, dynamic, and impedance control mechanisms, to complete multiple operational stages of the pipeline repair process with a single pipeline repair device. This avoids the cumbersome process transitions and uncertainties caused by manual intervention that result in low efficiency and accuracy in pipeline repair caused by multi-device collaboration, thus improving the accuracy and efficiency of pipeline repair.

[0079] Example 2 Please refer to Figure 6 , Figure 6 A schematic diagram of a pipeline repair system based on multi-mechanism synergy provided in an embodiment of the present invention includes: a contact force mechanism model construction module 201, a vacuum adsorption gripper adjustment module 202, a segment assembly motion trajectory construction module 203, a segment assembly module 204, a grouting path determination module 205, and a grouting module 206; The contact force mechanism model construction module 201 is used to construct a three-dimensional point cloud model of the pipeline, determine the attitude deviation data of the preset pipeline repair equipment based on the three-dimensional point cloud model of the pipeline, and construct the contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment based on the attitude deviation data. The vacuum adsorption gripper adjustment module 202 is used to adjust the vacuum adsorption gripper of the pipeline repair equipment based on the contact force mechanism model until the pipeline repair equipment meets the preset stable operation requirements. The segment assembly motion trajectory construction module 203 is used to acquire the joint parameters of the robotic arm of the pipeline repair equipment, and construct the kinematic mechanism model of the robotic arm based on the joint parameters; and determine the segment assembly motion trajectory of the robotic arm based on the pipeline three-dimensional point cloud model and the kinematic mechanism model. The segment assembly module 204 is used to drive the robotic arm to move along the segment assembly trajectory based on a preset dynamic mechanism and a preset impedance control mechanism, so that the robotic arm assembles the preset segment to be assembled at the preset repair position. The grouting path determination module 205 is used to construct a three-dimensional point cloud model of the segment to be repaired after the assembly of the segment to be assembled is completed; and to determine the grouting path of the segment to be repaired based on the three-dimensional point cloud model of the segment. The grouting module 206 is used to drive the robotic arm to move along the grouting path to grout the location to be repaired, thereby completing the repair of the pipeline.

[0080] In this embodiment, the contact force mechanism model construction module 201 includes: a contact force mechanism model construction unit; The contact force mechanism model building unit is used to build a three-dimensional point cloud model of the pipeline; The axial direction vector and pipe wall normal vector of the pipeline are determined based on the three-dimensional point cloud model of the pipeline; the attitude deviation data of the preset pipeline repair equipment are determined based on the axial direction vector and pipe wall normal vector. The resultant external torque and external pitching torque of the pipeline repair equipment are determined based on the attitude deviation data. Obtain the real-time vacuum pressure of each vacuum adsorption gripper of the pipeline repair equipment; A contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed based on the real-time vacuum pressure, the external pitching moment, and the resultant external moment.

[0081] In this embodiment, the contact force mechanism model construction unit includes: a contact force mechanism model construction subunit; The contact force mechanism model construction subunit is used to determine the normal adsorption force of each vacuum adsorption gripper based on the real-time vacuum pressure; Obtain the unit vector of the tube wall normal at the adsorption point of each vacuum adsorption gripper; The resultant reaction torque of the pipeline repair equipment is constructed based on the normal unit vector of the pipe wall at the adsorption point of each vacuum adsorption gripper and the normal adsorption force. The torque balance constraints of the pipeline repair equipment are constructed based on the resultant reaction torque and the resultant external torque. The pitch balance torque of the pipeline repair equipment is constructed based on the normal adsorption force of each of the vacuum adsorption grippers; The pitch moment balance constraint of the pipeline repair equipment is constructed based on the pitch balance moment and the external pitch moment. Based on the torque balance constraint, the pitch torque balance constraint, and the preset anti-slip constraint, a contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed.

[0082] In this embodiment, the segment assembly motion trajectory construction module 203 includes: a segment assembly motion trajectory construction unit; The segment assembly motion trajectory construction unit is used to obtain the joint parameters of the robotic arm of the pipeline repair equipment; Based on the joint parameters, a joint homogeneous transformation matrix between two adjacent joints in the robotic arm is constructed, and an end homogeneous transformation matrix of the robotic arm is constructed based on the homogeneous transformation matrix. The kinematic mechanism model of the robotic arm is constructed based on the joint homogeneous transformation matrix and the end homogeneous transformation matrix; The kinematic mechanism model is solved based on the three-dimensional point cloud model of the pipeline to determine the segment assembly motion trajectory of the robotic arm.

[0083] In this embodiment, the segment assembly motion trajectory construction unit includes: a segment assembly motion trajectory construction subunit; The segment assembly motion trajectory construction subunit is used to determine the starting joint motion variable data and end-effector starting position data of the robotic arm at the preset gripping point of the segment to be assembled based on the three-dimensional point cloud model of the pipeline; Based on the three-dimensional point cloud model of the pipeline, the termination joint motion variable data and end-effector termination position data of the robotic arm at the preset repair position are determined. The kinematic mechanism model is solved based on the initial joint motion variable data to obtain the initial Jacobian matrix of the robotic arm at the grasping point; and the initial end-effector velocity and initial end-effector acceleration of the robotic arm at the grasping point are determined based on the initial Jacobian matrix. The kinematic mechanism model is solved based on the termination joint motion variable data to obtain the termination Jacobian matrix of the robotic arm at the repair position; and the end-effector termination velocity and end-effector termination acceleration of the robotic arm at the repair position are determined based on the termination Jacobian matrix. The target motion trajectory function of the robotic arm is constructed based on a preset fifth-order polynomial interpolation algorithm; Based on the starting position data, the starting velocity of the end effector, the starting acceleration of the end effector, the ending position data, the ending velocity of the end effector, and the ending acceleration of the end effector, the target motion trajectory function is solved to determine the segment assembly motion trajectory of the robotic arm.

[0084] In this embodiment, the segment assembly module 204 includes: a segment assembly unit; The segment assembly unit is used to acquire the real-time end contact force, real-time joint motion variable values, and real-time joint velocity vector of the robotic arm in each control cycle of the robotic arm. Based on the segment assembly motion trajectory, end-effector contact force, joint real-time motion variable values, and joint real-time velocity vector, an end-effector impedance control mechanism model of the robotic arm is constructed, and the joint correction acceleration and joint correction velocity of the robotic arm are determined based on the end-effector impedance control mechanism model. The joint correction acceleration and joint correction velocity are modeled based on a preset Lagrange dynamics modeling algorithm to determine the joint driving torque model of the robotic arm. Solve the joint driving torque model to obtain the joint driving torque of the robotic arm in the current control cycle; Based on the joint driving torque, the robotic arm moves along the assembly trajectory of the tube segment within the current control cycle, so that the robotic arm assembles the preset tube segment to be assembled at the preset repair position.

[0085] In this embodiment, the segment assembly unit includes: an application subunit for the end impedance control mechanism model; The end-effector impedance control mechanism model application sub-unit is used to solve the kinematic mechanism model based on the real-time motion variable values ​​of the joint, and to determine the real-time end position, joint position vector, and coordinate system unit vector of the robotic arm; The real-time Jacobian matrix of the robotic arm is constructed based on the joint position vector and the coordinate system unit vector, and the real-time end-effector velocity and real-time end-effector acceleration of the robotic arm are determined based on the real-time Jacobian matrix and the joint real-time velocity vector. The end target position, end target velocity, and end real-time acceleration of the robotic arm in the current control cycle are determined based on the segment assembly motion trajectory. Based on the real-time end position, real-time end velocity, real-time end acceleration, real-time end contact force, end target position, end target velocity, and real-time end acceleration, an end impedance control mechanism model for the robotic arm is constructed. The end-effector impedance control mechanism model is solved to determine the end-effector correction acceleration and end-effector correction velocity of the robotic arm. The joint correction acceleration and joint correction velocity of the robotic arm are determined based on the end-effector correction acceleration and end-effector correction velocity.

[0086] In this embodiment, the grouting path determination module 205 includes: a grouting path determination unit; The grouting path determination unit is used to construct a three-dimensional point cloud model of the segment to be repaired after the assembly of the segment to be assembled is completed. Seed points are selected from the three-dimensional point cloud model of the tunnel segment based on a preset curvature threshold and the curvature of each point cloud in the model. Centered on the seed point, the point cloud of the three-dimensional point cloud model of the pipe segment is clustered based on a preset region growing algorithm to obtain a set of point clouds of the cavity region. Boundary fitting is performed on the point cloud set of the cavity region to determine the cavity contour boundary, and the grouting start point is determined based on the cavity contour boundary; Centered on the grouting starting point, the cavity contour boundary is sliced ​​based on a preset slicing scanning algorithm to generate an initial grouting path that determines the location to be repaired; The initial grouting path is verified based on the kinematic mechanism model to determine the grouting path for the location to be repaired.

[0087] In this embodiment, the grouting module 206 includes: a grouting unit; The grouting unit is used to drive the robotic arm to move along the grouting path and control the grouting head of the robotic arm to grout the grouting path in order to grout the location to be repaired. After the robotic arm completes the movement of the grouting path, a three-dimensional point cloud model of the grouting at the location to be repaired is constructed. The grouting 3D point cloud model and the segment 3D point cloud model are registered according to a preset point cloud registration algorithm to obtain the first grouting 3D point cloud model corresponding to the grouting 3D point cloud model and the first segment 3D point cloud model corresponding to the segment 3D point cloud model. The first grouting 3D point cloud model is reconstructed to obtain the grouting-filled surface model; The surface of the cavity before grouting is obtained by reconstructing the three-dimensional point cloud model of the first segment. Construct a closed bounding box between the grouting-filled surface model and the grouting-prepared cavity surface model, and determine the actual grouting-filled volume based on the closed bounding box; The grouting fullness is determined based on the actual grouting filling volume and the preset theoretical grouting volume; If the grouting fullness exceeds the preset grouting fullness threshold, the repair of the pipeline is completed. If the grout fullness does not exceed the grout fullness threshold, the grouting path of the location to be repaired is redefined, thereby driving the robotic arm to move along the redefined grouting path to grout the location to be repaired, and thus updating the grout fullness.

[0088] This embodiment constructs a 3D point cloud model of the pipeline, providing an accurate spatial reference for the subsequent adjustment of the vacuum adsorption gripper and segment assembly of the pipeline repair equipment. Next, the 3D point cloud model is used to determine attitude deviation data, and this data is used to construct a contact force mechanism model for the vacuum adsorption gripper of the pipeline repair equipment. This allows for adjustment of the vacuum adsorption gripper to ensure the pipeline repair equipment meets preset stable operation requirements, providing a stable operating platform for subsequent segment assembly and grouting. Finally, the joint parameters of the robotic arm of the pipeline repair equipment are obtained, and a kinematic mechanism model of the robotic arm is constructed, enabling adjustments to the robotic arm's movement within the pipeline. The invention models the motion within the pipeline and then plans the segment assembly trajectory of the robotic arm using a 3D point cloud model of the pipeline. This ensures that the segment assembly trajectory not only meets the physical motion design requirements of the robotic arm but also adapts to the complex environment inside the pipeline. Subsequently, the robotic arm is driven by dynamic and impedance control mechanisms to assemble the segments at the preset repair locations, achieving precise segment assembly. After assembly, a 3D point cloud model of the segment at the repair location is constructed. Based on this model, the grouting path is determined, and the robotic arm is driven to grout the repair location along the path. This achieves accurate control of the entire pipeline repair process in complex environments. This invention utilizes a multi-mechanism collaborative control approach, combining kinematic, dynamic, and impedance control mechanisms, to complete multiple operational stages of the pipeline repair process with a single pipeline repair device. This avoids the cumbersome process transitions and uncertainties caused by manual intervention that result in low efficiency and accuracy in pipeline repair caused by multi-device collaboration, thus improving the accuracy and efficiency of pipeline repair.

[0089] In summary, this invention, by constructing a three-dimensional point cloud model of the pipeline, provides an accurate spatial reference for the subsequent adjustment of the vacuum adsorption gripper and segment assembly of the pipeline repair equipment. Next, the posture deviation data is determined using the three-dimensional point cloud model, and a contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed based on this data. This allows for the adjustment of the vacuum adsorption gripper using the contact force mechanism model, ensuring the pipeline repair equipment meets preset stable operation requirements and providing a stable operating platform for subsequent segment assembly and grouting. Finally, the joint parameters of the robotic arm of the pipeline repair equipment are obtained, and a kinematic mechanism model of the robotic arm is constructed, enabling adjustments to the robotic arm's joints. The movement of the robotic arm within the pipeline is modeled, and then combined with a 3D point cloud model of the pipeline to plan the segment assembly trajectory of the robotic arm. This ensures that the segment assembly trajectory not only meets the physical motion design requirements of the robotic arm but also adapts to the complex environment inside the pipeline. Subsequently, the robotic arm is driven by dynamic and impedance control mechanisms to assemble the segments at the preset repair locations, achieving precise segment assembly. After segment assembly, a 3D point cloud model of the segment at the repair location is constructed, and the grouting path for the repair location is determined based on this model. The robotic arm is then driven to grout the repair location along the grouting path, thus achieving accurate control of the entire pipeline repair process in complex pipeline environments. This invention, through multi-mechanism collaborative control using kinematic, dynamic, and impedance control mechanisms, enables a single pipeline repair device to complete multiple operational stages of the pipeline repair process. This avoids the cumbersome process transitions and uncertainties caused by manual intervention resulting from multi-device collaboration, which lead to low pipeline repair efficiency and accuracy, thereby improving the accuracy and efficiency of pipeline repair.

[0090] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A pipeline repair method based on multi-mechanism synergy, characterized in that, include: Construct a three-dimensional point cloud model of the pipeline, and determine the attitude deviation data of the preset pipeline repair equipment based on the three-dimensional point cloud model of the pipeline; A contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed based on the posture deviation data. The vacuum adsorption gripper of the pipeline repair equipment is adjusted based on the contact force mechanism model until the pipeline repair equipment meets the preset stable operation requirements. The joint parameters of the robotic arm of the pipeline repair equipment are obtained, and a kinematic mechanism model of the robotic arm is constructed based on the joint parameters; and the segment assembly motion trajectory of the robotic arm is determined based on the three-dimensional point cloud model of the pipeline and the kinematic mechanism model. The robotic arm is driven to move along the assembly trajectory of the pipe segment based on a preset dynamic mechanism and a preset impedance control mechanism, so that the robotic arm assembles the preset pipe segment to be assembled at the preset repair position; After the assembly of the segments to be assembled is completed, a three-dimensional point cloud model of the segment to be repaired is constructed; and the grouting path of the segment to be repaired is determined based on the three-dimensional point cloud model of the segment. The robotic arm is driven to move along the grouting path to grout the location to be repaired, thereby completing the repair of the pipeline.

2. The pipeline repair method based on multi-mechanism synergy as described in claim 1, characterized in that, The construction of the pipeline three-dimensional point cloud model, and the determination of the attitude deviation data of the preset pipeline repair equipment based on the pipeline three-dimensional point cloud model; Based on the attitude deviation data, a contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed, including: Construct a 3D point cloud model of the pipeline; The axial direction vector and pipe wall normal vector of the pipeline are determined based on the three-dimensional point cloud model of the pipeline; the attitude deviation data of the preset pipeline repair equipment are determined based on the axial direction vector and pipe wall normal vector. The resultant external torque and external pitching torque of the pipeline repair equipment are determined based on the attitude deviation data. Obtain the real-time vacuum pressure of each vacuum adsorption gripper of the pipeline repair equipment; A contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed based on the real-time vacuum pressure, the external pitching moment, and the resultant external moment.

3. The pipeline repair method based on multi-mechanism synergy as described in claim 2, characterized in that, The contact force mechanism model for the vacuum adsorption gripper of the pipeline repair equipment, constructed based on the real-time vacuum pressure, the external pitching moment, and the resultant external moment, includes: The normal adsorption force of each vacuum adsorption gripper is determined based on the real-time vacuum pressure. Obtain the unit vector of the tube wall normal at the adsorption point of each vacuum adsorption gripper; The resultant reaction torque of the pipeline repair equipment is constructed based on the normal unit vector of the pipe wall at the adsorption point of each vacuum adsorption gripper and the normal adsorption force. The torque balance constraints of the pipeline repair equipment are constructed based on the resultant reaction torque and the resultant external torque. The pitch balance torque of the pipeline repair equipment is constructed based on the normal adsorption force of each of the vacuum adsorption grippers; The pitch moment balance constraint of the pipeline repair equipment is constructed based on the pitch balance moment and the external pitch moment. Based on the torque balance constraint, the pitch torque balance constraint, and the preset anti-slip constraint, a contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment is constructed.

4. The pipeline repair method based on multi-mechanism synergy as described in claim 1, characterized in that, The joint parameters of the robotic arm of the pipeline repair equipment are obtained, and a kinematic mechanism model of the robotic arm is constructed based on the joint parameters; The segment assembly motion trajectory of the robotic arm is determined based on the three-dimensional point cloud model and kinematic mechanism model of the pipeline, including: Obtain the joint parameters of the robotic arm of the pipeline repair equipment; Based on the joint parameters, a joint homogeneous transformation matrix between two adjacent joints in the robotic arm is constructed, and an end homogeneous transformation matrix of the robotic arm is constructed based on the homogeneous transformation matrix. The kinematic mechanism model of the robotic arm is constructed based on the joint homogeneous transformation matrix and the end homogeneous transformation matrix; The kinematic mechanism model is solved based on the three-dimensional point cloud model of the pipeline to determine the segment assembly motion trajectory of the robotic arm.

5. The pipeline repair method based on multi-mechanism synergy as described in claim 4, characterized in that, The step of solving the kinematic mechanism model based on the three-dimensional point cloud model of the pipeline to determine the segment assembly motion trajectory of the robotic arm includes: Based on the three-dimensional point cloud model of the pipeline, the starting joint motion variable data and the end-effector starting position data of the robotic arm at the preset gripping point of the pipe segment to be assembled are determined; Based on the three-dimensional point cloud model of the pipeline, the termination joint motion variable data and end-effector termination position data of the robotic arm at the preset repair position are determined. The kinematic mechanism model is solved based on the initial joint motion variable data to obtain the initial Jacobian matrix of the robotic arm at the grasping point; and the initial end-effector velocity and initial end-effector acceleration of the robotic arm at the grasping point are determined based on the initial Jacobian matrix. The kinematic mechanism model is solved based on the termination joint motion variable data to obtain the termination Jacobian matrix of the robotic arm at the repair position; and the end-effector termination velocity and end-effector termination acceleration of the robotic arm at the repair position are determined based on the termination Jacobian matrix. The target motion trajectory function of the robotic arm is constructed based on a preset fifth-order polynomial interpolation algorithm; Based on the starting position data, the starting velocity of the end effector, the starting acceleration of the end effector, the ending position data, the ending velocity of the end effector, and the ending acceleration of the end effector, the target motion trajectory function is solved to determine the segment assembly motion trajectory of the robotic arm.

6. The pipeline repair method based on multi-mechanism synergy as described in claim 4, characterized in that, The robotic arm is driven to move along the assembly trajectory of the pipe segment based on a preset dynamic mechanism and a preset impedance control mechanism, so that the robotic arm assembles the preset pipe segment to be assembled at the preset repair position, including: During each control cycle of the robotic arm, the real-time end contact force, real-time joint motion variable values, and real-time joint velocity vector of the robotic arm are acquired. Based on the segment assembly motion trajectory, end-effector contact force, joint real-time motion variable values, and joint real-time velocity vector, an end-effector impedance control mechanism model of the robotic arm is constructed, and the joint correction acceleration and joint correction velocity of the robotic arm are determined based on the end-effector impedance control mechanism model. The joint correction acceleration and joint correction velocity are modeled based on a preset Lagrange dynamics modeling algorithm to determine the joint driving torque model of the robotic arm. Solve the joint driving torque model to obtain the joint driving torque of the robotic arm in the current control cycle; Based on the joint driving torque, the robotic arm moves along the assembly trajectory of the tube segment within the current control cycle, so that the robotic arm assembles the preset tube segment to be assembled at the preset repair position.

7. The pipeline repair method based on multi-mechanism synergy as described in claim 6, characterized in that, The process of constructing an end-effector impedance control mechanism model for the robotic arm based on the segment assembly motion trajectory, real-time end-effector contact force, real-time joint motion variable values, and real-time joint velocity vectors, and determining the joint correction acceleration and joint correction velocity of the robotic arm based on the end-effector impedance control mechanism model, includes: The kinematic mechanism model is solved based on the real-time motion variable values ​​of the joints to determine the real-time end position, joint position vector, and coordinate system unit vector of the robotic arm. The real-time Jacobian matrix of the robotic arm is constructed based on the joint position vector and the coordinate system unit vector, and the real-time end-effector velocity and real-time end-effector acceleration of the robotic arm are determined based on the real-time Jacobian matrix and the joint real-time velocity vector. The end target position, end target velocity, and end real-time acceleration of the robotic arm in the current control cycle are determined based on the segment assembly motion trajectory. Based on the real-time end position, real-time end velocity, real-time end acceleration, real-time end contact force, end target position, end target velocity, and real-time end acceleration, an end impedance control mechanism model for the robotic arm is constructed. The end-effector impedance control mechanism model is solved to determine the end-effector correction acceleration and end-effector correction velocity of the robotic arm. The joint correction acceleration and joint correction velocity of the robotic arm are determined based on the end-effector correction acceleration and end-effector correction velocity.

8. The pipeline repair method based on multi-mechanism synergy as described in claim 1, characterized in that, After the assembly of the segment to be assembled is completed, a three-dimensional point cloud model of the segment at the location to be repaired is constructed. And based on the three-dimensional point cloud model of the tunnel segment, the grouting path of the location to be repaired is determined, including: After the assembly of the segment to be assembled is completed, a three-dimensional point cloud model of the segment at the location to be repaired is constructed. Seed points are selected from the three-dimensional point cloud model of the tunnel segment based on a preset curvature threshold and the curvature of each point cloud in the model. Centered on the seed point, the point cloud of the three-dimensional point cloud model of the pipe segment is clustered based on a preset region growing algorithm to obtain a set of point clouds of the cavity region. Boundary fitting is performed on the point cloud set of the cavity region to determine the cavity contour boundary, and the grouting start point is determined based on the cavity contour boundary; Centered on the grouting starting point, the cavity contour boundary is sliced ​​based on a preset slicing scanning algorithm to generate an initial grouting path that determines the location to be repaired; The initial grouting path is verified based on the kinematic mechanism model to determine the grouting path for the location to be repaired.

9. A pipeline repair method based on multi-mechanism synergy as described in claim 8, characterized in that, The process of driving the robotic arm to move along the grouting path to grout the location to be repaired, thereby completing the repair of the pipeline, includes: Drive the robotic arm to move along the grouting path and control the grouting head of the robotic arm to grout the grouting path to grout the location to be repaired; After the robotic arm completes the movement of the grouting path, a three-dimensional point cloud model of the grouting at the location to be repaired is constructed. The grouting 3D point cloud model and the segment 3D point cloud model are registered according to a preset point cloud registration algorithm to obtain the first grouting 3D point cloud model corresponding to the grouting 3D point cloud model and the first segment 3D point cloud model corresponding to the segment 3D point cloud model. The first grouting 3D point cloud model is reconstructed to obtain the grouting-filled surface model; The surface of the cavity before grouting is obtained by reconstructing the three-dimensional point cloud model of the first segment. Construct a closed bounding box between the grouting-filled surface model and the grouting-prepared cavity surface model, and determine the actual grouting-filled volume based on the closed bounding box; The grouting fullness is determined based on the actual grouting filling volume and the preset theoretical grouting volume; If the grouting fullness exceeds the preset grouting fullness threshold, the repair of the pipeline is completed. If the grout fullness does not exceed the grout fullness threshold, the grouting path of the location to be repaired is redefined, thereby driving the robotic arm to move along the redefined grouting path to grout the location to be repaired, and thus updating the grout fullness.

10. A pipeline repair system based on multi-mechanism synergy, characterized in that, include: The module includes a contact force mechanism model construction module, a vacuum adsorption gripper adjustment module, a segment assembly motion trajectory construction module, a segment assembly module, a grouting path determination module, and a grouting module. The contact force mechanism model construction module is used to construct a three-dimensional point cloud model of the pipeline, determine the attitude deviation data of the preset pipeline repair equipment based on the three-dimensional point cloud model of the pipeline, and construct the contact force mechanism model of the vacuum adsorption gripper of the pipeline repair equipment based on the attitude deviation data. The vacuum adsorption gripper adjustment module is used to adjust the vacuum adsorption gripper of the pipeline repair equipment based on the contact force mechanism model until the pipeline repair equipment meets the preset stable operation requirements. The segment assembly motion trajectory construction module is used to obtain the joint parameters of the robotic arm of the pipeline repair equipment, and construct the kinematic mechanism model of the robotic arm based on the joint parameters; and determine the segment assembly motion trajectory of the robotic arm based on the pipeline three-dimensional point cloud model and the kinematic mechanism model. The segment assembly module is used to drive the robotic arm to move along the segment assembly trajectory based on a preset dynamic mechanism and a preset impedance control mechanism, so that the robotic arm assembles the preset segment to be assembled at the preset repair position. The grouting path determination module is used to construct a three-dimensional point cloud model of the segment to be repaired after the assembly of the segment to be assembled is completed; and to determine the grouting path of the segment to be repaired based on the three-dimensional point cloud model of the segment. The grouting module is used to drive the robotic arm to move along the grouting path to grout the location to be repaired, thereby completing the repair of the pipeline.

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