Hierarchical control method, system and readable storage medium for a robotic arm
Patent Information
- Application Number
- CN202510349292.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-24
- Publication Date
- 2026-09-25
AI Technical Summary
[0009]本发明的目的在于提供一种用于机械臂的层级控制方法、系统及可读存储介质，以解决执行器层与上层控制的信息交互问题，使得执行器能够更高效地参与机械臂系统的控制，从而释放出全部性能潜力
[0069]1)通过将各个关节电机的驱动扭矩分解为动态分量和静态分量，静态分量直接作为前馈输入到关节电机的扭矩-电流内环中，用于进行重力和摩擦补偿，以确保系统的平衡和稳定性；动态分量则以反馈形式输入末端执行器的速度环中，提升系统的动态响应，可以实现多种灵活的控制效果。该层级控制方法强化了层级之间的信息交换，支持更深入、多样化的控制算法设计，并实现了能量优化和动态响应性能的改进；
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Abstract
Description
Technical Field
[0001] This invention relates to the field of robotic arm control technology, and in particular to a hierarchical control method, system, and readable storage medium for robotic arms. Background Technology
[0002] In recent years, robotic arms have been deployed at an astonishing rate into complex, unstructured environments. This trend has increased the demand for modern robotic arm systems to handle multi-functional tasks. In this context, hierarchical control strategies, including various functional layers, have become common in addressing these challenges.
[0003] Hierarchical control strategies can adapt to diverse tasks in complex, unstructured environments. This approach typically integrates deep learning and reinforcement learning into a multi-layered control framework to mimic and learn complex biological or human actions. The process includes: planning and decision-making at the upper decision layer; performing kinematic and dynamic calculations in the motion control layer to determine the ideal control response; and finally, passing these responses to the lower actuator layer to execute actions, thereby ensuring the robustness of the entire system.
[0004] However, the importance of the actuator layer is often overlooked in related research, and it is usually treated as an independent unit. In fact, integrating actuator layer control more deeply into the robotic arm system can significantly impact overall performance. The reasons are as follows:
[0005] 1) Energy efficiency optimization: Implementing control strategies directly at the actuator level can manage energy consumption more effectively;
[0006] 2) Adaptability and Self-Correction: Actuator-level control enhances the adaptability of the robotic arm system, enabling it to adjust its motion strategy according to environmental changes or task requirements. Simultaneously, data from the actuator level facilitates fault detection and self-correction mechanisms, improving system reliability.
[0007] 3) Simplify upper-level control: By executing more complex control logic at the actuator layer, the complexity of upper-level control can be reduced.
[0008] Despite these advantages, the integration of the actuator layer into hierarchical control strategies has not been thoroughly investigated. Therefore, this research gap presents a significant opportunity for future research. Solving this problem will drive the development of robotic arm systems, making them more adaptable to complex environments and enabling them to perform a wider range of tasks with greater efficiency and reliability. Summary of the Invention
[0009] The purpose of this invention is to provide a hierarchical control method, system, and readable storage medium for robotic arms, so as to solve the information interaction problem between the actuator layer and the upper control layer, enabling the actuator to participate more efficiently in the control of the robotic arm system, thereby releasing its full performance potential.
[0010] To achieve the above objectives, the present invention provides a hierarchical control method for a robotic arm, comprising the following steps:
[0011] Acquire environmental information of the workspace where the robotic arm is located and perform path planning to generate a planned path;
[0012] The planned path is transformed into the joint space motion of the robotic arm. Based on the dynamic model, the driving torque of each joint motor of the robotic arm corresponding to each target position is determined, and the driving torque is decomposed into dynamic and static components.
[0013] The static component is used as a feedforward compensation input to the current loop of the corresponding joint motor, and the dynamic component is used as a feedback input to the speed loop of the end effector of the robotic arm.
[0014] Optionally, obtaining environmental information of the workspace where the robotic arm is located and performing path planning includes:
[0015] Obtain information about the surrounding environment of the workspace;
[0016] Determine the positions and attitudes of each target the robotic arm needs to pass through to complete the task, and plan a collision-free path.
[0017] Optionally, the driving torque of each joint motor of the robotic arm corresponding to each target position is determined based on the dynamic model, and the driving torque is decomposed into dynamic and static components, including:
[0018] The general dynamic model of an n-degree-of-freedom serial robotic arm can be expressed as:
[0019]
[0020] in, These are vectors representing the angle, velocity, and acceleration of any joint of the robotic arm, respectively. and These represent the inertia matrix, the Coriolis matrix, and the gravitational torque of the robotic arm, respectively. These represent Coulomb-viscous friction and joint drive torque, respectively. External disturbance torque;
[0021] The external disturbance torque is the contact force between the end effector and the environment. Represented as:
[0022] τ ext =J(q)F ext (2)
[0023] Where J(q) represents the Jacobian matrix;
[0024] Let x represent the pose of the end effector in the workspace, which can be expressed by forward kinematics as x = Φ(q). The velocity of the end effector is calculated by the following formula:
[0025]
[0026] Differentiating both sides of the above formula (3), we obtain the translation and angular acceleration of the end effector:
[0027]
[0028] Based on the above formula (4), the following formula (5) is used to utilize... Solve
[0029]
[0030] in, This represents the conjugate transpose of J. The derivative of J is represented by .
[0031] Substituting formulas (3) and (5) into formula (1), the dynamic model of the n-degree-of-freedom serial manipulator is expressed as follows:
[0032]
[0033] Where τ j , where represents the driving torque of the j-th joint of the n-degree-of-freedom serial robotic arm, j = 1, 2, ..., n, and n is a positive integer. This represents the translational and angular acceleration of the end effector borne by the j-th joint;
[0034] The driving torque τ j It can be decomposed into three components, as shown in the following formula:
[0035]
[0036] Among them, T dym For the dynamic component, T stc For the static component, T ext This refers to external torque.
[0037] Optionally, a model predictive control algorithm or an adaptive algorithm can be used to input the dynamic component as feedback into the velocity loop of the end effector.
[0038] Based on the same inventive concept, the present invention also provides a hierarchical control system for a robotic arm, comprising:
[0039] The task decision layer is used to acquire environmental information of the workspace where the robotic arm is located and to perform path planning to generate a planned path.
[0040] The motion control layer is used to convert the planned path into the joint space motion of the robotic arm, determine the driving torque of each joint motor of the robotic arm corresponding to each target position based on the dynamic model, and decompose the driving torque into dynamic components and static components.
[0041] The actuator layer is used to input the static component as a feedforward compensation into the current loop of the corresponding joint motor, and to input the dynamic component as a feedback into the speed loop of the end effector of the robotic arm.
[0042] Optionally, the task decision layer is specifically used for:
[0043] Obtain information about the surrounding environment of the workspace;
[0044] Determine the positions and attitudes of each target the robotic arm needs to pass through to complete the task, and plan a collision-free path.
[0045] Optionally, the motion control layer is specifically used for:
[0046] The general dynamic model of an n-degree-of-freedom serial robotic arm can be expressed as:
[0047]
[0048] in, These are vectors representing the angle, velocity, and acceleration of any joint of the robotic arm, respectively. and These represent the inertia matrix, the Coriolis matrix, and the gravitational torque of the robotic arm, respectively. These represent Coulomb-viscous friction and joint drive torque, respectively. External disturbance torque;
[0049] The external disturbance torque is the contact force between the end effector and the environment. Represented as:
[0050] τ ext =J(q)F ext (2)
[0051] Where J(q) represents the Jacobian matrix;
[0052] Let x represent the pose of the end effector in the workspace, which can be expressed by forward kinematics as x = Φ(q). The velocity of the end effector is calculated by the following formula:
[0053]
[0054] Differentiating both sides of the above formula (3), we obtain the translation and angular acceleration of the end effector:
[0055]
[0056] Based on the above formula (4), the following formula (5) is used to utilize... Solve
[0057]
[0058] in, This represents the conjugate transpose of J. The derivative of J is represented by .
[0059] Substituting formulas (3) and (5) into formula (1), the dynamic model of the n-degree-of-freedom serial manipulator is expressed as follows:
[0060]
[0061] Where, τ j This represents the driving torque of the j-th joint of the n-degree-of-freedom serial robotic arm, where j = 1, 2, ..., n, and n is a positive integer. This represents the translational and angular acceleration of the end effector borne by the j-th joint;
[0062] The driving torque τ j It can be decomposed into three components, as shown in the following formula:
[0063]
[0064] Among them, T dym For the dynamic component, T stc For the static component, T ext This refers to external torque.
[0065] Optionally, the actuator layer employs a model predictive control algorithm or an adaptive algorithm to input the dynamic components as feedback into the velocity loop of the end effector.
[0066] Optionally, the motion control layer is also used for position control of the end effector.
[0067] Based on the same inventive concept, the present invention also provides a readable storage medium having a computer program stored thereon, which, when executed, enables the hierarchical control method for a robotic arm as described above.
[0068] The hierarchical control method, system, and readable storage medium for robotic arms provided by this invention have at least the following advantages:
[0069] 1) By decomposing the drive torque of each joint motor into dynamic and static components, the static component is directly fed forward into the torque-current inner loop of the joint motor for gravity and friction compensation, ensuring the system's balance and stability. The dynamic component is fed back into the velocity loop of the end effector to improve the system's dynamic response, enabling various flexible control effects. This hierarchical control method strengthens information exchange between levels, supports deeper and more diverse control algorithm design, and achieves energy optimization and improved dynamic response performance.
[0070] 2) The information interaction method is original and completely different from existing robotic arm systems, which enables the robotic arm actuator to participate in system control more efficiently, thereby releasing its full performance potential;
[0071] 3) The performance of the actuator has been optimized in terms of energy efficiency, response speed and robustness, providing more flexible and diversified control strategies for the robotic arm system, thereby ultimately improving the performance of the entire system. Attached Figure Description
[0072] Those skilled in the art will understand that the accompanying drawings are provided to better understand the invention and do not constitute any limitation on the scope of the invention. Wherein:
[0073] Figure 1 A flowchart illustrating a hierarchical control method for a robotic arm according to an embodiment of the present invention;
[0074] Figure 2 This is a structural block diagram of a hierarchical control system for a robotic arm provided in an embodiment of the present invention;
[0075] Figure 3 This is a flowchart of a bolt tightening process using a robotic arm, provided as an embodiment of the present invention.
[0076] Figure 4 Experimental results of trajectory tracking using the hierarchical control method provided in an embodiment of the present invention. Detailed Implementation
[0077] To make the objectives, advantages, and features of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the drawings are in a very simplified form and use non-precise proportions, and are only used to facilitate and clearly illustrate the purpose of the embodiments of this invention. Please refer to the accompanying drawings to make the objectives, features, and advantages of this invention more apparent and understandable. It should be understood that the structures, proportions, sizes, etc., depicted in the accompanying drawings are only used to complement the content disclosed in the specification, for those skilled in the art to understand and read, and are not intended to limit the implementation conditions of this invention. Any modifications to the structure, changes in proportions, or adjustments to the size, if they are the same as or similar to the effects and objectives achieved by this invention, should still fall within the scope of the technical content disclosed in this invention.
[0078] As used herein, the singular forms “a,” “an,” and “the” include plural objects unless otherwise expressly indicated. As used herein, the term “or” is generally used to include “and / or” unless otherwise expressly indicated. As used herein, the term “a number” is generally used to include “at least one” unless otherwise expressly indicated. As used herein, the term “at least two” is generally used to include “two or more” unless otherwise expressly indicated. Furthermore, the terms “first,” “second,” and “third” are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as “first,” “second,” or “third” may explicitly or implicitly include one or at least two of that feature.
[0079] In the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.
[0080] Please refer to Figure 1 This embodiment provides a hierarchical control method for a robotic arm, including the following steps:
[0081] S1. Obtain environmental information of the workspace where the robotic arm is located and perform path planning to generate a planned path;
[0082] S2. The planned path is converted into the joint space motion of the robotic arm. Based on the dynamic model, the driving torque of each joint motor of the robotic arm corresponding to each target position is determined, and the driving torque is decomposed into dynamic components and static components.
[0083] S3. The static component is used as a feedforward compensation input to the current loop of the corresponding joint motor, and the dynamic component is used as a feedback input to the speed loop of the end effector of the robotic arm.
[0084] The hierarchical control method for robotic arms proposed in this invention decomposes the driving torque of each joint motor into dynamic and static components. The static component is directly fed forward into the torque-current inner loop of the joint motor for gravity and friction compensation, ensuring system balance and stability. The dynamic component is fed back into the velocity loop of the end effector, improving the system's dynamic response. This hierarchical control method enhances information exchange between levels, supports more in-depth and diverse control algorithm design, and achieves energy optimization and improved dynamic response performance.
[0085] In this embodiment, S1-S3 correspond to the execution content of the task decision layer, motion control layer, and actuator layer in the hierarchical control system for the robotic arm, respectively.
[0086] First, step S1 is executed to obtain environmental information of the workspace where the robotic arm is located and perform path planning to generate a planned path. In this embodiment, the step of obtaining environmental information of the workspace where the robotic arm is located and performing path planning specifically includes:
[0087] Obtain information about the surrounding environment of the workspace;
[0088] Confirm the positions and attitudes of all targets the robotic arm needs to pass through to complete the task, and plan a collision-free path.
[0089] Specifically, path planning for the robotic arm typically requires the use of multiple onboard sensors, such as vision sensors, end effector force sensors, and inertial measurement units (IMUs). These sensors enable the robotic arm to perceive its surrounding environment, confirm the positions and attitudes of all target objects in the task, and plan collision-free paths. By integrating sensor data, a comprehensive understanding of the robotic arm's surrounding environment and the creation of relevant maps are constructed, thereby enabling precise decision-making and motion planning under dynamic environments and task requirements.
[0090] Then, step S2 is executed to transform the planned path into the joint space motion of the robotic arm. Based on the dynamic model, the driving torque of each joint motor of the robotic arm corresponding to each target position is determined, and the driving torque is decomposed into dynamic and static components. By transforming the planned path in the workspace into the joint space motion of the robotic arm, and then using kinematic and dynamic models to determine the target position and driving torque, this invention introduces an innovative data transmission method. The torque calculated by the upper layer is decomposed into dynamic and static components and transmitted to the lower actuator layer respectively.
[0091] In this embodiment, we start with the theoretical and dynamic modeling of the robotic arm and then gradually analyze the characteristics of the robotic arm control system.
[0092] For an n-DOF serial robotic arm, its general dynamic model in joint space can be expressed as:
[0093]
[0094] in, These are vectors representing the angle, velocity, and acceleration of any joint of the robotic arm, respectively. and These represent the inertia matrix, the Coriolis matrix, and the gravitational torque of the robotic arm, respectively. These represent Coulomb-viscous friction and joint drive torque, respectively. External disturbance torque;
[0095] The external disturbance torque mainly originates from the contact force between the end effector and the environment. Therefore, the external torque and the contact force are expressed as:
[0096] τ ext =J(q)F ext (2)
[0097] Where J(q) represents the Jacobian matrix;
[0098] Let x represent the pose of the end effector in the workspace, which can be expressed by forward kinematics as x = Φ(q). The velocity of the end effector is calculated by the following formula:
[0099]
[0100] because It is obtained directly based on the Jacobian matrix J(q), therefore x and There is no time derivative relationship between them.
[0101] Differentiating both sides of the above formula (3), we can obtain the translation and angular acceleration of the end effector:
[0102]
[0103] Used to track desired task space acceleration This acceleration is typically used as the control output of the motion control layer.
[0104] Based on the above formula (4), the following formula (5) can be used to utilize... Solve
[0105]
[0106] in, This represents the conjugate transpose of J. The derivative of J is represented by .
[0107] Substituting formulas (3) and (5) into formula (1), the dynamic model of the n-degree-of-freedom serial robotic arm can be obtained as follows:
[0108]
[0109] Where, τ j This represents the driving torque of the j-th joint of the n-degree-of-freedom serial robotic arm, where j = 1, 2, ..., n, and n is a positive integer. This represents the translation and angular acceleration of the end effector undertaken by the j-th joint.
[0110] The driving torque τ j It can be decomposed into three components, as shown in the following formula:
[0111]
[0112] Among them, T dym For the dynamic component, T stc For the static component, T ext This refers to external torque.
[0113] Among them, the dynamic component T dym Rapid response and adaptation to changing operating conditions are crucial, including the effects of inertia and Coriolis forces. These forces are designed to keep the robotic arm system's motion consistent with the expected velocity and acceleration, thus reflecting the system's control intent. From a high-level planning perspective, the control input is typically set to acceleration. Within this framework, inertial force becomes the only "force" that can be directly specified by control input, directly reflecting the intention of system control.
[0114] Static component Tstc Closely related to the static kinematics and configuration of the robotic arm, this component is crucial for counteracting the effects of gravity and joint friction on the system. It plays a vital role in maintaining the balance and stability of the robotic arm system and ensuring consistent operation. This is particularly critical in tasks requiring continuous force application or maintaining specific postures. In many unstructured environments, compensation for gravity and friction is essential for achieving a compliant robotic arm, enabling T... stc This is key to achieving smooth and stable operation.
[0115] In dexterity and high-intensity maneuvering tasks, handling external forces on end effectors often involves complex interactions with the environment, which are frequently addressed through compliant models and advanced algorithms such as model predictive control (MPC) or reinforcement learning. These approaches enable systems to adapt to unpredictable interactions, ensuring accuracy and compliance under external shocks or disturbances. Regarding τ... ext This component is different from F. ext The latter is typically calculated by the interactive controller during the operational task, while τ ext This refers to unexpected disturbances, such as collisions with the environment outside the end effector. Addressing these disturbances is crucial for maintaining system integrity and requires a robust approach.
[0116] Based on the dynamic model and analysis, T dym It is key to achieving instantaneous motion response and can enhance the speed response capability of the actuator; T stc Prioritizing stability ensures the robotic arm's balance and indirectly improves dynamic response performance. Furthermore, managing τ... ext (Indicating unexpected external disturbances) are particularly important for maintaining the robustness of the system and the operational integrity in interactions with unpredictable environments.
[0117] Finally, S3 is executed, in which the static component is input as feedforward compensation into the current loop of the corresponding joint motor, and the dynamic component is input as feedback into the speed loop of the end effector of the robotic arm.
[0118] In this embodiment, the static component serves as the input to the current-torque inner loop, handling gravity and friction compensation to ensure system balance and stability. The dynamic component serves as the controller input, optimizing control performance by considering factors such as response speed, energy consumption, and efficiency.
[0119] Preferably, a model predictive control algorithm or an adaptive algorithm is used to input the dynamic components as feedback into the speed loop of the end effector, so as to respond to dynamic performance requirements more quickly and stably.
[0120] It is important to note that lower-level position signal control often conflicts with upper-level compliant control or other force-position hybrid control. Therefore, in this hierarchical structure, the actuator layer does not handle position control; this task is handled by the motion control layer. The actuator layer responds to the desired speed and torque transmitted from the upper layer to reduce position errors.
[0121] The inner current loop of the actuator layer continuously compensates for static torque, thereby achieving effective gravity compensation. Through the interaction of speed and dynamic torque between the outer loop and the upper-level control, various flexible control effects, such as compliant control, can be achieved. This can be accomplished by setting position-related PD control in the higher-level controller to calculate the desired speed and torque, thereby eliminating position errors.
[0122] In this embodiment, it is necessary to determine whether the end effector of each robotic arm has reached the expected position. If so, the end effector performs the corresponding operation; otherwise, the joint space motion is replanned until all tasks are completed.
[0123] Based on the same inventive concept, such as Figure 2 As shown, this embodiment of the invention also proposes a hierarchical control system for a robotic arm, which mainly consists of the following three key levels:
[0124] The task decision layer is used to acquire environmental information of the workspace where the robotic arm is located and to perform path planning to generate a planned path.
[0125] The motion control layer is used to convert the planned path into the joint space motion of the robotic arm, determine the driving torque of each joint motor of the robotic arm corresponding to each target position based on the dynamic model, and decompose the driving torque into dynamic components and static components.
[0126] The actuator layer is used to input the static component as a feedforward compensation into the current loop of the corresponding joint motor, and to input the dynamic component as a feedback into the speed loop of the end effector of the robotic arm.
[0127] In this embodiment, the task decision layer is specifically used for:
[0128] Obtain information about the surrounding environment of the workspace;
[0129] Determine the positions and attitudes of each target the robotic arm needs to pass through to complete the task, and plan a collision-free path.
[0130] Specifically, the task decision layer is responsible for motion planning based on the control model. This typically requires the use of various onboard sensors, such as vision sensors, end effector force sensors, and inertial measurement units (IMUs), enabling the robotic arm to perceive its surroundings, assess the situation, and plan collision-free paths. By integrating sensor data, a comprehensive understanding of the robotic arm's environment and the creation of a map are built, thereby achieving accurate decision-making and motion planning under dynamic environments and task requirements.
[0131] Optionally, the task decision layer is generally equipped with a high-performance computing platform to perform complex tasks such as SLAM and object detection. This part can also be deployed remotely for remote operation.
[0132] In this embodiment, the motion control layer is mainly responsible for tracking the path planned by the task decision layer, converting the planned path in the workspace into the joint space motion of the robotic arm, and then using kinematic and dynamic models to determine the target position and driving torque. This invention introduces an innovative data transmission method that decomposes the torque calculated by the upper layer into dynamic and static components and transmits them to the lower actuator layer respectively.
[0133] The motion control layer is typically a high-performance embedded platform. This platform possesses considerable computing power, enabling it to share some of the computational load with the task decision layer. Furthermore, this platform provides real-time control, handling real-time data transmission and reception, and offering real-time references to the task decision layer, making it a crucial element for stable system operation. This invention, by completely decoupling the dynamic model into dynamic and static components and distributing them sequentially, enhances the information interaction between the actuator layer, the task decision layer, and other actuator layers, facilitating the development of more diverse control algorithms and logic.
[0134] In this embodiment, the motion control layer is specifically used for:
[0135] Starting with the theoretical and dynamic modeling of the robotic arm, the specific steps of determining the driving torque of each joint motor corresponding to each target position based on the dynamic model, and decomposing the driving torque into dynamic and static components, include:
[0136] For an n-DOF serial robotic arm, its general dynamic model in joint space can be expressed as:
[0137]
[0138] in, These are vectors representing the angle, velocity, and acceleration of any joint of the robotic arm, respectively. and These represent the inertia matrix, the Coriolis matrix, and the gravitational torque of the robotic arm, respectively. These represent Coulomb-viscous friction and joint drive torque, respectively. External disturbance torque;
[0139] The external disturbance torque mainly originates from the contact force between the end effector and the environment. Therefore, the external torque and the contact force are expressed as:
[0140] τ ext =J(q)F ext (2)
[0141] Where J(q) represents the Jacobian matrix;
[0142] Let x represent the pose of the end effector in the workspace, which can be expressed by forward kinematics as x = Φ(q). The velocity of the end effector is calculated by the following formula:
[0143]
[0144] because It is obtained directly based on the Jacobian matrix J(q), therefore x and There is no time derivative relationship between them.
[0145] Differentiating both sides of the above formula (3), we can obtain the translation and angular acceleration of the end effector:
[0146]
[0147] Used to track desired task space acceleration This acceleration is typically used as the control output of the motion control layer.
[0148] Based on the above formula (4), the following formula (5) can be used to utilize... Solve
[0149]
[0150] in, This represents the conjugate transpose of J. The derivative of J is represented by .
[0151] Substituting formulas (3) and (5) into formula (1), the dynamic model of the n-degree-of-freedom serial robotic arm can be obtained as follows:
[0152]
[0153] Where, τ jThis represents the driving torque of the j-th joint of the n-degree-of-freedom serial robotic arm, where j = 1, 2, ..., n, and n is a positive integer. This represents the translation and angular acceleration of the end effector undertaken by the j-th joint.
[0154] The driving torque τ j It can be decomposed into three components, as shown in the following formula:
[0155]
[0156] Among them, T dym For the dynamic component, T stc The static component, T ext This refers to external torque.
[0157] Preferably, the motion control layer is also used for position control of the end effector. It should be noted that the position signal control at the lower level often conflicts with the compliant control or other force-position hybrid control at the upper level. Therefore, in this hierarchical structure, the actuator layer does not handle position control; this task is handled by the motion control layer. The actuator layer responds to the desired speed and torque transmitted from the upper layer to reduce position errors.
[0158] In this embodiment, the actuator layer is the core component of the study, processing the static and dynamic components from the motion control layer. The static component serves as the input to the current-torque inner loop, handling gravity and friction compensation to ensure system balance and stability. The dynamic component serves as the input to the controller, optimizing control performance by considering factors such as response speed, energy consumption, and efficiency.
[0159] The inner current loop of the actuator layer continuously compensates for static torque, thereby achieving effective gravity compensation. Through the interaction of speed and dynamic torque between the outer loop and the upper-level control, various flexible control effects, such as compliant control, can be achieved. This can be accomplished by setting position-related PD control in the higher-level controller to calculate the desired speed and torque, thus eliminating position errors.
[0160] Preferably, the actuator layer uses a model predictive control algorithm or an adaptive algorithm to input the dynamic components as feedback into the speed loop of the end effector, so as to respond to dynamic performance requirements more quickly and stably.
[0161] In this embodiment, it is necessary to determine whether each joint of each robotic arm has reached the expected position. If so, the end effector performs the corresponding operation; otherwise, the joint space motion is replanned until all tasks are completed.
[0162] The technical concept of the present invention is further illustrated by a specific example below, such as... Figure 3 As shown, Figure 3This is a flowchart for using a robotic arm to tighten bolts.
[0163] First, the surrounding environment and bolt distribution are perceived using airborne sensors. After all the fastening bolts are numbered, the information is sent to the host computer. After the host computer confirms the fastening sequence, the camera is activated to guide the robotic arm to gradually approach the bolts to be fastened.
[0164] Then determine whether the bolt to be tightened is located at the center of the image. If so, drive the end of the robotic arm to move along the normal direction of the bolt to be tightened and try to align it with the bolt. If not, adjust the pose of the robotic arm until the bolt to be tightened is located at the center of the image.
[0165] Next, it is determined whether the sleeve at the end of the robotic arm is in contact with the bolt to be tightened. If so, the end joint of the robotic arm is rotated with constant force in the normal direction. It is then determined whether the sleeve is aligned with the bolt to be tightened. If not, the end of the robotic arm is driven to move along the normal direction of the bolt to be tightened, and the attempt to align it with the bolt to be tightened is continued.
[0166] If the sleeve is aligned with the bolt to be tightened, the bolt is tightened using the electric wrench at the end of the robotic arm. If the sleeve is not aligned with the bolt to be tightened, the end joint of the robotic arm is rotated with a constant force in the normal direction until the sleeve is aligned with the bolt to be tightened.
[0167] After the tightening operation is completed, the robotic arm is reset to its initial position. The above steps are repeated to tighten all bolts within the working range.
[0168] The main functions of this invention are summarized as follows:
[0169] This invention proposes a novel hierarchical control method and system for robotic arms, aiming to improve their integration within the overall system. The method and system divide the robotic arm's torque output into dynamic and static components, each managed by a specific control loop within the actuator layer. The dynamic loop is used for rapid adjustments, while the static loop focuses on maintaining stable torque. This integrated control strategy aims to improve the accuracy, adaptability, and overall efficiency of the robotic arm system, enabling it to better handle complex tasks.
[0170] This invention is specifically designed for robotic arms in unstructured environments, and is particularly suitable for robotic arms that have extensive contact with their environment. With its rapid response and effective gravity and friction compensation, this hierarchical control system is particularly well-suited for scenarios where robotic arms frequently come into contact with various objects or surfaces. This invention can also be used in research to drive further development and applications.
[0171] Experimental Verification: To verify the effectiveness of the proposed hierarchical control method and system, a physical model of the robotic arm was constructed using Simulink and Simscape Multibody. For the joint motors, Simscape Electrical was used to construct n full-bridge topologies for n permanent magnet synchronous motors (PMSMs), and PWM control was implemented on the full-bridge topology switches using Matlab Functions. The output torque was directly input into the joint model of the robotic arm. Compliant control was performed at the planning layer based on feedback from the joint sensors, and kinematic and dynamic calculations were completed to simulate the entire process.
[0172] This invention employs trajectory tracking experiments to evaluate the response performance of the proposed hierarchical control method and system. The experiments assume that the task decision layer provides a series of interpolated trajectory points marked with time coordinates. After calculating the torque using the kinematic and dynamic models of the robotic arm, the dynamic component T is... dym and static component T stc The data is input into the controllers of each joint motor, driving the joint motors and the robotic arm to move. Taking the first joint as an example, its experimental data is as follows: Figure 4 As shown.
[0173] The results are as follows Figure 4 As shown, the hierarchical control method exhibits superior accuracy and adaptability. The system can effectively track the desired joint angles and velocities, ensuring precise motion. It can also efficiently compensate for gravity and friction, maintaining the system's stability and responsiveness, which is reflected in the high consistency between the desired trajectory and the actual trajectory.
[0174] Based on the same inventive concept, embodiments of the present invention also propose a readable storage medium storing a computer program thereon, which, when executed, can implement the hierarchical control method for a robotic arm as described above.
[0175] A readable storage medium can be a tangible device capable of holding and storing instructions for use by an instruction execution device, such as, but not limited to, electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof. The computer programs described herein can be downloaded from the readable storage medium to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. Networks can include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. Each computing / processing device's network adapter card or network interface receives and forwards a computer program from the network for storage on a readable storage medium within the respective computing / processing device. The computer program used to perform the operations of this invention can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, etc., and conventional procedural programming languages such as "C" or similar languages. The computer program can execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuits, such as programmable logic circuits, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), are personalized by utilizing state information from a computer program. These electronic circuits can execute computer-readable program instructions, thereby realizing various aspects of the present invention.
[0176] Various aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, systems, and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by a computer program. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. These computer programs can also be stored in a readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the readable storage medium storing the computer program comprises an article of manufacture including instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams.
[0177] A computer program may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the computer program executing on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.
[0178] In summary, this invention provides a hierarchical control method, system, and readable storage medium for a robotic arm. By decomposing the driving torque of each joint motor into dynamic and static components, the static component is directly fed forward into the torque-current inner loop of the joint motor for gravity and friction compensation, ensuring system balance and stability. The dynamic component is fed back into the velocity loop of the end effector, improving the system's dynamic response. This hierarchical control method enhances information exchange between levels, supports more in-depth and diverse control algorithm design, and achieves energy optimization and improved dynamic response performance.
[0179] Furthermore, it should be understood that although the present invention has been disclosed above with reference to preferred embodiments, these embodiments are not intended to limit the present invention. For any person skilled in the art, many possible variations and modifications can be made to the technical solutions of the present invention based on the disclosed technical content, or equivalent embodiments can be modified accordingly, without departing from the scope of the present invention. Therefore, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention, without departing from the content of the present invention, shall still fall within the scope of protection of the present invention.
Claims
1. A hierarchical control method for a robotic arm, characterized in that, Includes the following steps: Acquire environmental information of the workspace where the robotic arm is located and perform path planning to generate a planned path; The planned path is transformed into the joint space motion of the robotic arm. Based on the dynamic model, the driving torque of each joint motor of the robotic arm corresponding to each target position is determined, and the driving torque is decomposed into dynamic and static components. The static component is used as a feedforward compensation input to the current loop of the corresponding joint motor, and the dynamic component is used as a feedback input to the speed loop of the end effector of the robotic arm.
2. The hierarchical control method for a robotic arm according to claim 1, characterized in that, The process of acquiring environmental information of the workspace where the robotic arm is located and performing path planning includes: Obtain information about the surrounding environment of the workspace; Determine the positions and attitudes of each target the robotic arm needs to pass through to complete the task, and plan a collision-free path.
3. The hierarchical control method for a robotic arm according to claim 1, characterized in that, The driving torque of each joint motor of the robotic arm corresponding to each target position is determined based on the dynamic model, and the driving torque is decomposed into dynamic components and static components, including: The general dynamic model of an n-degree-of-freedom serial robotic arm can be expressed as: in, These are vectors representing the angle, velocity, and acceleration of any joint of the robotic arm, respectively. and These represent the inertia matrix, the Coriolis matrix, and the gravitational torque of the robotic arm, respectively. These represent Coulomb-viscous friction and joint drive torque, respectively. External disturbance torque; The external disturbance torque is the contact force between the end effector and the environment. Represented as: τ ext =J(q)F ext (2) Where J(q) represents the Jacobian matrix; Let x represent the pose of the end effector in the workspace, which can be expressed by forward kinematics as x = Φ(q). The velocity of the end effector is calculated by the following formula: Differentiating both sides of the above formula (3), we obtain the translation and angular acceleration of the end effector: Based on the above formula (4), the following formula (5) is used to utilize... Solve in, This represents the conjugate transpose of J. The derivative of J is represented by . Substituting formulas (3) and (5) into formula (1), the dynamic model of the n-degree-of-freedom serial manipulator is expressed as follows: Where, τ j This represents the driving torque of the j-th joint of the n-degree-of-freedom serial robotic arm, where j = 1, 2, ..., n, and n is a positive integer. This represents the translational and angular acceleration of the end effector borne by the j-th joint; The driving torque τ j It can be decomposed into three components, as shown in the following formula: Among them, T dym For the dynamic component, T stc For the static component, T ext This refers to external torque.
4. The hierarchical control method for a robotic arm according to claim 1, characterized in that, The dynamic components are used as feedback inputs into the velocity loop of the end effector using a model predictive control algorithm or an adaptive algorithm.
5. A hierarchical control system for a robotic arm, characterized in that, include: The task decision layer is used to acquire environmental information of the workspace where the robotic arm is located and to perform path planning to generate a planned path. The motion control layer is used to convert the planned path into the joint space motion of the robotic arm, determine the driving torque of each joint motor of the robotic arm corresponding to each target position based on the dynamic model, and decompose the driving torque into dynamic components and static components. The actuator layer is used to input the static component as a feedforward compensation input to the current loop of the corresponding joint motor, and to input the dynamic component as a feedback input to the speed loop of the end effector of the robotic arm.
6. The hierarchical control system for a robotic arm according to claim 5, characterized in that, The task decision layer is specifically used for: Obtain information about the surrounding environment of the workspace; Determine the positions and attitudes of each target the robotic arm needs to pass through to complete the task, and plan a collision-free path.
7. The hierarchical control system for a robotic arm according to claim 5, characterized in that, The motion control layer is specifically used for: The general dynamic model of an n-degree-of-freedom serial robotic arm can be expressed as: in, These are vectors representing the angle, velocity, and acceleration of any joint of the robotic arm, respectively. and These represent the inertia matrix, the Coriolis matrix, and the gravitational torque of the robotic arm, respectively. These represent Coulomb-viscous friction and joint drive torque, respectively. External disturbance torque; The external disturbance torque is the contact force between the end effector and the environment. Represented as: τ ext =J(q)F ext (2) Where J(q) represents the Jacobian matrix; Let x represent the pose of the end effector in the workspace, which can be expressed by forward kinematics as x = Φ(q). The velocity of the end effector is calculated by the following formula: Differentiating both sides of the above formula (3), we obtain the translation and angular acceleration of the end effector: Based on the above formula (4), the following formula (5) is used to utilize... Solve in, This represents the conjugate transpose of J. The derivative of J is represented by . Substituting formulas (3) and (5) into formula (1), the dynamic model of the n-degree-of-freedom serial manipulator is expressed as follows: Where, τ j This represents the driving torque of the j-th joint of the n-degree-of-freedom serial robotic arm, where j = 1, 2, ..., n, and n is a positive integer. This represents the translational and angular acceleration of the end effector borne by the j-th joint; The driving torque τ j It can be decomposed into three components, as shown in the following formula: Among them, T dym For the dynamic component, T stc For the static component, T ext This refers to external torque.
8. The hierarchical control system for a robotic arm according to claim 5, characterized in that, The actuator layer uses a model predictive control algorithm or an adaptive algorithm to input the dynamic components as feedback into the velocity loop of the end effector.
9. The hierarchical control system for a robotic arm according to claim 5, characterized in that, The motion control layer is also used for the position control of the end effector.
10. A readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it can implement the hierarchical control method for a robotic arm according to any one of claims 1-4.