Curtain wall mounting robot, position control method, and storage medium

Abstract

The present application provides a curtain wall mounting robot, a position control method, and a storage medium. The position control method comprises the following steps: achieving equivalence between a mobile base component and a manipulator component by adding virtual joints, and establishing an overall kinematic model; assigning priorities to different execution tasks in the overall kinematic model to form a first-priority task and a second-priority task, wherein the first-priority task has a higher priority than the second-priority task; upon completion of the first-priority task, scheduling the second-priority task on the basis of a null-space strategy; and performing motion control calculation by means of the overall kinematic model having undergone scheduling, and outputting control data to implement coordinated control between the mobile base component and the manipulator component. The present application solves the problems in the prior art of being unable to implement coordinated control between a manipulator component and a mobile base component and failing to sufficiently exploit the advantages of the redundancy characteristics of a mobile manipulator due to the use of hierarchical control.

Description

A robot for curtain wall installation, a position control method, and a storage medium. Technical Field

[0001] This application relates to the field of intelligent robot technology, and more particularly to a robot for curtain wall installation, a position control method, and a storage medium. Background Technology

[0002] Mobile robotic arms typically consist of a robotic arm (the actuating robotic arm component) and a mobile base component (translational mechanism and movable legs), such as a curtain wall installation robot. Mobile robotic arms mimic human walking through the mobile base component and human maneuvering through the actuating robotic arm component. High-precision robotic arms are responsible for interacting with the environment. The mobile base component with mobility capabilities transports the robotic arm to different areas, expanding its workspace. In recent years, more and more scholars have conducted in-depth research in the field of mobile robotic arms, promoting the development of mobile robotic arm technology. The application of mobile robotic arms in various applications such as factory patrol, material handling, medical services, and rescue operations is becoming increasingly frequent, providing powerful assistance to daily life and industrial production.

[0003] The robot moves to the required work location by driving the mobile base component. Therefore, the mobile base component can expand the robot's workspace. However, the movement of the mobile base component also introduces problems such as motion redundancy and control complexity into the robot system. Typical industrial robots have six degrees of freedom (DOF), sufficient to complete tasks in three-dimensional space. The degrees of freedom from the mobile base component lead to kinematic redundancy. The higher the redundancy, the more joints are involved, and the more complex the control becomes. The flow control method for mobile robots mainly adopts hierarchical control, which decouples the entire system into a robot subsystem and a mobile base component subsystem, planning and controlling the two subsystems separately during task execution.

[0004] Layered control algorithms are simple, straightforward, and easy to implement. Most existing robot control systems are still layered, where the mobile base component and the manipulator are decoupled into two subsystems, each controlled independently. Typically, the mobile base component moves to the desired position first, and then the manipulator's movement is planned. However, this wastes a significant amount of time and leads to inefficiency. The manipulator can begin working in advance during the movement of the mobile base component, without waiting for it to stop. However, since the position of the mobile base component is fixed while the manipulator is working, layered control can only handle simple tasks and cannot cope with complex scenarios. Layered control decomposes a redundant system into two non-redundant systems, failing to fully utilize the advantages of the mobile manipulator's redundancy. Therefore, it cannot use redundancy to achieve advantages such as obstacle avoidance, singularity avoidance, increased operability, and reduced energy consumption.

[0005] Therefore, existing technologies still need to be improved and developed.

[0006] Summary of the Invention

[0007] In view of the shortcomings of the prior art, the purpose of this application is to provide a robot for curtain wall installation, a position control method and a storage medium, which solves the problems of the prior art's use of hierarchical control, which makes it impossible to coordinate the control of the actuator and the moving base components and is insufficient to demonstrate the advantages of the redundancy characteristics of the mobile robot.

[0008] On one hand, this application provides a position control method for a curtain wall installation robot. The applicable curtain wall installation robot includes: a moving base component and an execution robotic arm component, wherein the execution robotic arm component is connected to an end effector; wherein, the position control method includes the following steps:

[0009] By adding virtual joints, the moving base component and the execution robotic arm component are made equivalent, and an overall kinematic model is established.

[0010] Different execution tasks in the overall kinematic model are assigned priorities to form first priority tasks and second priority tasks, with the first priority task having a higher priority than the second priority task.

[0011] After the first priority task is completed, the second priority task is scheduled based on the zero-space strategy;

[0012] Motion control calculations are performed using the overall kinematic model after scheduling, and the output control data enables the moving base component and the executing robotic arm component to perform coordinated control.

[0013] Optionally, in the step of establishing an overall kinematic model by adding virtual joints to make the moving base component equivalent to the executing robotic arm component:

[0014] The mobile base component is equivalent to a jointed robotic arm by adding virtual joints, and a joint control model is established together with the execution robotic arm component.

[0015] By setting up a world coordinate system, a translation base coordinate system, a robotic arm coordinate system, and an end effector coordinate system in the joint control model, and using the DH parameter method to establish the homogeneous transformation matrix between adjacent links in the joint control model, an overall kinematic model is established.

[0016] Optionally, in the process of assigning priorities to different execution tasks in the overall kinematic model to form first-priority tasks and second-priority tasks, where the first-priority task has a higher priority than the second-priority task:

[0017] The first priority task includes: controlling the end effector to reach the execution position;

[0018] The second priority task includes: planning the gait of the six legs of the moving base component and the position of the translation mechanism based on the movement trajectory and ground conditions;

[0019] and,

[0020] Based on the curtain wall installation requirements, plan the movement path of the robotic arm components.

[0021] Optionally, in the step of planning the gait of the six legs of the moving base component and the position of the translation mechanism based on the motion trajectory and ground conditions:

[0022] The contact force between the six legs of the moving base component and the ground is detected in real time, and the posture and position of the six legs and the position of the translation mechanism are adjusted according to the contact force.

[0023] In the step of planning the motion path of the robotic arm components based on the curtain wall installation requirements:

[0024] The force sensor of the end effector detects the contact force between the end effector and the curtain wall, and the posture of the robotic arm components is adjusted according to the contact force.

[0025] Optionally, in the step of scheduling the second priority task based on the null space strategy after the first priority task has been executed:

[0026] This utilizes the necessary degrees of freedom of the overall kinematic model to complete the first priority task;

[0027] The remaining degrees of freedom in the overall kinematic model are used for the planning and control of the second priority task, where the necessary degrees of freedom + the remaining degrees of freedom = the total degrees of freedom of the overall kinematic model.

[0028] Optionally, in the step of performing motion control calculations using the scheduled overall kinematic model and outputting control data to enable coordinated control of the moving base component and the executing robotic arm component:

[0029] The inverse kinematics solution is performed on the overall kinematic model after scheduling, so that the motion process of the overall kinematic model passes through the singular point;

[0030] The gradient projection method is used to obtain operability metrics and output control data, which is used to perform coordinated control of the moving base component and the actuator component.

[0031] Optionally, in the step of performing inverse kinematics solution on the scheduled overall kinematic model to make the motion process of the overall kinematic model pass through singular points:

[0032] The inverse kinematics solution with singular robustness is generated by damped least squares method, wherein an adaptive scaling factor is introduced in the process of generating the inverse kinematics solution to keep the accuracy and joint velocity within a predetermined equilibrium range, so that the motion process can pass through the singular point.

[0033] Optionally, in the step of using the gradient projection method to obtain the operability metric and output control data:

[0034] The joint motion of the second priority task in the null space strategy is processed by the gradient projection method to obtain an operability metric. In the gradient projection method, a portion of the Jacobian matrix is ​​selected for gradient calculation.

[0035] On the other hand, this application also proposes a robot for curtain wall installation, which includes: a mobile base component, an execution robotic arm component, and a processor;

[0036] The processor executes the position control method described above for the curtain wall installation robot to control the moving base components and the robotic arm components to perform coordinated movements.

[0037] Thirdly, this application also proposes a computer-readable storage medium storing one or more programs that can be executed by one or more processors to implement the above-described position control method for a curtain wall installation robot.

[0038] Beneficial Effects: This application discloses a curtain wall installation robot, a position control method, and a storage medium that solve the core problem of endpoint stability control in tracked curtain wall installation robots. By establishing an overall kinematic model, the moving base component is equivalent to a part of the executing robotic arm component for overall control. Based on the task execution, priorities are assigned to the tasks. Using a zero-space tuning strategy, the second-priority tasks are adjusted and optimized while ensuring that the first-priority task remains unaffected. This ensures that the moving base component, equivalent to the executing robotic arm component, is coordinated and controlled without affecting the execution of the main tasks, thus optimizing the performance of the tracked construction robot. Motion control calculations are performed using the scheduled overall kinematic model, and the output control data enables the moving base component and the executing robotic arm component to perform coordinated control, achieving effective control of the entire tracked construction robot. This improves the reliability and practicality of the control method, jointly enhancing the movement capability and stability of the tracked curtain wall installation robot in complex construction environments, providing important technical support for its practical application. Through coordinated control, the advantages of the redundancy characteristics of the mobile robotic arm are demonstrated. Attached Figure Description

[0039] Figure 1 is a flowchart of the main steps of a position control method for a curtain wall installation robot according to an embodiment of this application;

[0040] Figure 2 is a flowchart illustrating the detailed steps of a position control method for a curtain wall installation robot according to an embodiment of this application. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this application clearer and more explicit, the following detailed description of this application is provided with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0042] Existing control methods for mobile robotic arms (footed curtain wall installation robots) are typically computationally complex and have limited applicability. Furthermore, the diverse terrain conditions at construction sites significantly impact the stability and control performance of these robots. In endpoint stabilization control, accurate prediction and compensation of dynamic effects caused by the robot's motion are crucial, placing high demands on the design of control algorithms. Upon reaching the endpoint, the robot needs to maintain a stable posture and accurate position. This requires high-precision sensors and advanced control algorithms. Simultaneously, the robot's posture and position are affected by external disturbances (such as wind and uneven ground), necessitating robust control strategies. To address these issues, this application proposes a zero-space-tuned, full-body control method for endpoint stabilization control of footed curtain wall installation robots, which is of significant importance. The core idea of ​​this method is to utilize the concept of zero space to optimize and adjust the robot's posture and position while fulfilling primary tasks (such as forward movement and turning) to achieve better stability. This application models a hexa-legged tracked construction robot as an articulated manipulator and uses a zero-space-based method to control its movement. It can simultaneously control the movement of the manipulator, the six legs, and the tracks. The method described in this application is computationally simpler, and the tracked curtain wall installation robot determines its next action based on its current state, resulting in better environmental adaptability. The specific solution of this application is as follows:

[0043] As shown in Figure 1, this embodiment proposes a position control method for a curtain wall installation robot. The applicable curtain wall installation robot mainly includes a mobile base component and an actuator robotic arm component. The mobile base component includes a translation mechanism and movable legs. Typically, the translation mechanism is a tracked mechanism, allowing for stable movement on construction sites with high speed and good terrain adaptability. The movable legs are typically six-legged, supporting the entire curtain wall installation robot in a predetermined position and leveling the body to adapt to various uneven ground environments. The actuator robotic arm component is usually a multi-joint robotic arm, which can move under control. The actuator robotic arm component is connected to an end effector, which can be a gripper, suction cup, etc. Driven by the actuator robotic arm component, the end effector is moved to the curtain wall installation position for stable curtain wall installation.

[0044] The position control method in this embodiment includes the following steps:

[0045] Step S100: By adding virtual joints, the moving base component and the execution robotic arm component are made equivalent, and an overall kinematic model is established.

[0046] In the specific process, the entire curtain wall installation robot system is kinematically modeled, that is, the whole is equivalent to a joint motion model. The execution robotic arm component is directly included as part of the joint motion model. The moving base component needs to be equivalent to the execution robotic arm component by adding virtual joints, and is included as another part of the joint motion model, thereby establishing the overall kinematic model, and the whole system is regarded as a highly redundant articulated robotic arm system.

[0047] Step S100 specifically includes:

[0048] Step S110: The movable base component is equivalent to a jointed robotic arm by adding virtual joints, and a joint control model is established together with the execution robotic arm component.

[0049] Step S120: By setting the world coordinate system, the translation base coordinate system, the robot arm coordinate system, and the end effector coordinate system in the joint control model, the homogeneous transformation matrix between adjacent links of the joint control model is established using the DH parameter method, and the overall kinematic model is established.

[0050] In the above steps, virtual joints are added to the translation mechanism and movable foot of the moving base component respectively, and equivalent joints are added to form a joint motion model together with the joints of the execution robot arm itself, forming an overall kinematic model. Under the overall kinematic model, it is convenient to control each joint (including virtual joints) under a unified standard, making the control process more accurate.

[0051] Step S200: Assign priorities to different execution tasks in the overall kinematic model to form a first priority task and a second priority task, with the first priority task having a higher priority than the second priority task.

[0052] In practice, different tasks require different components in the overall kinematic model to be controlled, and the movement patterns of the joints connecting these components also differ. Therefore, different priorities are assigned to each task based on its importance. For example, the tasks performed by the robot are divided into first-priority tasks with the highest priority and second-priority tasks with a lower priority. First-priority tasks are given the highest priority, ensuring that their completion takes precedence over the completion of second-priority tasks.

[0053] In this embodiment, the first priority task of the curtain wall installation robot includes controlling the end effector to reach the execution position. That is, during the execution of the curtain wall installation robot's tasks, ensuring that the end effector reaches the execution position.

[0054] The second priority task of the curtain wall installation robot includes: planning the gait of the six legs of the moving base component and the position of the translation mechanism according to the motion trajectory and ground conditions; and planning the motion path of the execution robotic arm component according to the curtain wall installation requirements.

[0055] The mobile base component comprises six legs and a translation mechanism (tracks). Serving as the robot's movement and support system, the six legs and the translation mechanism (tracks) work together to ensure the robot's stability and mobility on complex terrain. By precisely controlling the movement of the six legs and tracks, the robot can achieve smooth walking and precise positioning on various terrains. The contact force between the six legs and the ground is detected in real time, and the posture and position of the six legs and the translation mechanism are adjusted based on this contact force.

[0056] The robotic arm component is an articulated structure that acts as an actuator to drive the end effector to a designated position, thereby undertaking the curtain wall installation task. The robotic arm component has multiple degrees of freedom, allowing it to drive the end effector to the designated position through various motion methods. This necessitates precise planning of the robotic arm's motion path to achieve accurate wall installation. Force sensors on the end effector detect the contact force between the end effector and the curtain wall, and the posture of the robotic arm component is adjusted based on this contact force, ensuring the end effector reaches the designated position stably and accurately.

[0057] The method in this embodiment actually involves closely coordinating the execution of the robotic arm components with the control of the six legs and tracks to ensure stable movement and safety during installation, thereby achieving further optimization of the robot's position control.

[0058] Step S300: After the first priority task is completed, the second priority task is scheduled based on the zero-space strategy.

[0059] In practice, the zero-space concept is understood as: after completing the main task, using the remaining degrees of freedom to fine-tune the posture and position. Taking the placement of a curtain wall as an example, ensuring the completion of the first priority task means that even if the end effector remains stationary at the execution position (the position where the curtain wall is placed), the gait of the six legs, the position of the translation mechanism (track), and the movement path of the robotic arm components in the second priority task can be coordinated and controlled. This ensures that the end effector can accurately reach the task position while the robotic arm components are closely coordinated with the six legs and tracks for control, ensuring stable movement and safety during installation, achieving unified control, and optimizing the robot's control method.

[0060] By utilizing the concept of null space, low-priority tasks (such as the gait of a six-legged animal and the position of the translation mechanism (track), and the motion tracking of the robotic arm components) can be scheduled in the null space of low-priority tasks (such as end effector position tracking) without affecting the high-priority first-priority tasks (such as end effector position tracking). This allows multiple tasks to be completed simultaneously.

[0061] Step S300 specifically includes the following steps:

[0062] Step S310: Utilize the necessary degrees of freedom of the overall kinematic model to complete the first priority task.

[0063] Step S320: Use the remaining degrees of freedom in the overall kinematic model to plan and control the second priority task, where the necessary degrees of freedom + remaining degrees of freedom = the complete degrees of freedom of the overall kinematic model.

[0064] In practice, the overall kinematic model possesses complete degrees of freedom, the value of which is determined by the mechanical structure. However, achieving the overall function typically involves multiple tasks, each requiring a certain number of degrees of freedom. Therefore, when the robotic arm drives the end effector to its execution position, the end effector usually remains stationary, occupying a portion of the overall kinematic model's degrees of freedom. The degrees of freedom required to complete the highest priority task are called the necessary degrees of freedom. The robotic arm, hexapod, and tracks can adjust their movements within the remaining degrees of freedom of the overall kinematic model to achieve coordinated control. The remaining degrees of freedom, obtained by subtracting the necessary degrees of freedom from the complete degrees of freedom, are called the residual degrees of freedom. Completing the lower priority task (second priority) within the residual degrees of freedom will not affect the first priority task.

[0065] After completing the highest priority task (such as position control of the end effector), the remaining degrees of freedom (i.e., null space) of the system are used to plan and control secondary tasks (lower priority tasks). This does not affect the execution of the main task, while increasing the system's flexibility and adaptability.

[0066] Step S400: Perform motion control calculations using the overall kinematic model after scheduling, and output control data to enable coordinated control of the moving base component and the executing robotic arm component.

[0067] In the specific process, after performing kinematic analysis on the overall kinematic model to realize the function of installing the curtain wall, the specific kinematic structure of the robotic arm component and the mobile base component (six legs and tracks) is obtained. Based on this structure, control data (control commands) are generated to control the robot's actual mobile base component and to execute coordinated movements of the robotic arm component to complete the entire curtain wall installation function.

[0068] Step S400 specifically includes the following steps:

[0069] Step S410: Perform inverse kinematics solution on the scheduled overall kinematic model so that the motion process of the overall kinematic model passes through singular points.

[0070] In the specific process, the inverse kinematics solution with singular robustness is generated by the damped least squares method. An adaptive scaling factor is introduced in the process of generating the inverse kinematics solution to keep the accuracy and joint velocity within a predetermined equilibrium range, so that the motion process can pass through the singular point.

[0071] The inverse kinematics with singular robustness is generated using damped least squares. This method balances accuracy and joint velocity by introducing an adaptive scaling factor, enabling the system to smoothly pass through singularities.

[0072] Step S420: Use the gradient projection method to obtain the operability metric and output control data. The control data is used to perform coordinated control on the moving base component and the executing robotic arm component.

[0073] In the specific process, the joint motion of the second priority task in the null space strategy is processed by the gradient projection method to obtain the operability metric. In the gradient projection method, a portion of the Jacobian matrix is ​​selected for gradient calculation.

[0074] By optimizing the operability metric using gradient projection, the system's maneuverability can be improved and singular configurations avoided. Optimizing motion in the null space using gradient projection enhances both maneuverability and stability. By analyzing the structure of the Jacobian matrix and selecting a portion of it to calculate the gradient, computational complexity is reduced, thus improving algorithm efficiency.

[0075] This embodiment also conducted simulation experiments to verify the above-described kinematic processing procedure:

[0076] The effectiveness of the proposed algorithm was verified through simulation experiments. In the experiments, the end effector was kept in a fixed position while the moving base tracked a circular trajectory, and the end effector was tracked a straight trajectory while the moving base tracked a sinusoidal trajectory. The results show that the algorithm can simultaneously track the desired trajectory and maintain a high operability metric.

[0077] This embodiment proposes a position control method for a curtain wall installation robot. Applied to a footed curtain wall installation robot, it fuses the state information of the six legs and robotic arm, as well as sensor data. Based on the fused information, it makes decisions for whole-body coordinated control. During movement, the motion parameters of the six legs and robotic arm are dynamically adjusted based on real-time feedback information, ensuring the robot maintains stability and adaptability in complex environments. Optimization algorithms (such as genetic algorithms and reinforcement learning) are introduced to optimize the whole-body coordinated control, improving the robot's stability and efficiency in different environments.

[0078] Example 2

[0079] This embodiment proposes a curtain wall installation robot, including a mobile base component, an actuator robotic arm component, and a processor. The processor executes the position control method for the curtain wall installation robot described above to control the mobile base component and the actuator robotic arm component to perform coordinated movements.

[0080] The curtain wall installation robot in this embodiment is a footed curtain wall installation robot. By employing the aforementioned position control method, whole-body control is achieved. Through coordinated control of the moving base components and the actuator arm components, the motion performance of the footed curtain wall installation robot is improved. In this scheme, the designed footed curtain wall installation robot is controlled by adding virtual joints and using a joint-redundant manipulator control method, assigning different priorities based on task importance. The end effector of the footed curtain wall installation robot can interact with the environment and therefore has a higher priority. Therefore, the position of the end effector is the first priority task, and the position of the six legs or tracks is the second priority task. Using the concept of null space, movement in the null space of the footed curtain wall installation robot will not lead to movement of the robot itself, thus allowing for the planning of secondary tasks. Remaining redundancy can be optimized using gradient projection for maneuverability measurements. Based on the special configuration of the footed curtain wall installation robot, a portion of the Jacobian matrix is ​​selected to calculate the gradient, thereby reducing computational complexity. The proposed technical approach focuses on solving the end-point steady-state control problem of mobile manipulators (MMs), especially at the speed level.

[0081] Example 3

[0082] This embodiment proposes a computer-readable storage medium, wherein the computer-readable storage medium stores one or more programs, which can be executed by one or more processors to implement the above-described position control method for a curtain wall installation robot.

[0083] This application discloses a curtain wall installation robot, a position control method, and a storage medium, which solves the core problem of end-point stability control for curtain wall installation robots. The method achieves stable control by precisely adjusting the movement of each joint of the curtain wall installation robot, optimizing its posture and position while fulfilling the main motion task. Its core lies in utilizing the zero-space concept, that is, fine-tuning the stability of the curtain wall installation robot within the remaining degrees of freedom after completing the main task, thereby ensuring that it maintains a stable posture and position upon reaching the endpoint. This method not only improves the stability of the footed curtain wall installation robot but also enhances its adaptability in complex environments.

[0084] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A position control method for a curtain wall installation robot, applicable to curtain wall installation robots including: A mobile base component and an execution robotic arm component, the execution robotic arm component being connected to an end effector; characterized in that the position control method includes the following steps: By adding virtual joints, the moving base component and the executing robotic arm component are made equivalent, and an overall kinematic model is established. Different execution tasks in the overall kinematic model are assigned priorities to form a first priority task and a second priority task, wherein the first priority task has a higher priority than the second priority task. After the first priority task is completed, the second priority task is scheduled based on the zero-space strategy; Motion control calculations are performed using the overall kinematic model after scheduling, and the output control data enables the moving base component and the executing robotic arm component to perform coordinated control.

2. The position control method for a curtain wall installation robot according to claim 1, characterized in that, In the step of establishing an overall kinematic model by adding virtual joints to make the movable base component equivalent to the execution robotic arm component: The mobile base component is equivalent to a jointed robotic arm by adding virtual joints, and a joint control model is established together with the execution robotic arm component. By setting up a world coordinate system, a translation base coordinate system, a robotic arm coordinate system, and an end effector coordinate system in the joint control model, and using the DH parameter method to establish the homogeneous transformation matrix between adjacent links of the joint control model, an overall kinematic model is established.

3. The position control method for a curtain wall installation robot according to claim 2, characterized in that, In the step of assigning priorities to different execution tasks in the overall kinematic model to form a first priority task and a second priority task, wherein the first priority task has a higher priority than the second priority task: The first priority task includes: controlling the end effector to reach the execution position; The second priority task includes: planning the gait of the six legs of the moving base component and the position of the translation mechanism based on the movement trajectory and ground conditions; and, Based on the curtain wall installation requirements, plan the movement path of the robotic arm components.

4. The position control method for a curtain wall installation robot according to claim 3, characterized in that, Based on the motion trajectory and ground conditions, the steps for planning the gait of the six legs of the moving base component and the position of the translation mechanism are as follows: The contact force between the six legs of the moving base component and the ground is detected in real time, and the posture and position of the six legs and the position of the translation mechanism are adjusted according to the contact force. In the step of planning the motion path of the robotic arm components based on the curtain wall installation requirements: The force sensor of the end effector detects the contact force between the end effector and the curtain wall, and the posture of the robotic arm component is adjusted according to the contact force.

5. The position control method for a curtain wall installation robot according to claim 1, characterized in that, In the step of scheduling the second priority task based on the zero-space strategy after the first priority task has been executed: This utilizes the necessary degrees of freedom of the overall kinematic model to complete the first priority task; The remaining degrees of freedom in the overall kinematic model are used for the planning and control of the second priority task, wherein the necessary degrees of freedom + the remaining degrees of freedom = the total degrees of freedom of the overall kinematic model.

6. The position control method for a curtain wall installation robot according to claim 1, characterized in that, In the step of performing motion control calculations using the overall kinematic model after scheduling, and outputting control data to enable coordinated control of the moving base component and the executing robotic arm component: The inverse kinematics solution is performed on the overall kinematic model after scheduling, so that the motion process of the overall kinematic model passes through the singular point; The operability metric is obtained using the gradient projection method, and control data is output. The control data is used to perform coordinated control on the moving base component and the executing robotic arm component.

7. The position control method for a curtain wall installation robot according to claim 1, characterized in that, In the step of solving the inverse kinematics of the overall kinematic model after scheduling, so that the motion process of the overall kinematic model passes through the singular points: A singularly robust inverse kinematic solution is generated using damped least squares, wherein an adaptive scaling factor is introduced during the generation of the inverse kinematic solution to keep accuracy and joint velocity within a predetermined equilibrium range, thus ensuring smooth motion. The process can pass through the singularity.

8. The position control method for a curtain wall installation robot according to claim 5, characterized in that, In the step of obtaining operability metrics and outputting control data using the gradient projection method: The joint motion of the second priority task in the null space strategy is processed by the gradient projection method to obtain an operability metric. In the gradient projection method, a portion of the Jacobian matrix is ​​selected for gradient calculation.

9. A robot for curtain wall installation, characterized in that, include: Mobile base components, robotic arm components, and processor; The processor executes the position control method for a curtain wall installation robot as described in any one of claims 1-8 to control the moving base component and the executing robotic arm component to perform coordinated movements.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores one or more programs, which can be executed by one or more processors to implement the position control method for a curtain wall installation robot as described in any one of claims 1-8.

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