Dual-arm teleoperation system and method based on variable stiffness virtual wall and damping force field

Abstract

The application discloses a dual-arm teleoperation system and method based on a variable stiffness virtual wall and a damping force field, which is composed of a master end and a slave end, wherein the master end comprises a dual-hand controller, a human-computer interaction interface, a virtual scene generation unit and a calculation unit, and the slave end comprises dual mechanical arms, a vision and depth sensor, wherein the calculation unit is used for receiving control instructions of the dual-hand controller of the master end, generating dual-mechanical-arm control instructions of the slave end after a master-end virtual wall and damping force field algorithm, transmitting force feedback to the dual-hand controller of the master end, and transmitting depth information and vision information to the virtual scene generation module. The system and method give a collision warning to an operator in the form of force feedback through the hand controller at the master end, set a dynamic safety coefficient to update the stiffness of the virtual wall in real time, set a damping force field according to the variable stiffness virtual wall, also increase the experience of human-computer interaction in the dual-arm teleoperation process, realize natural and effective interaction between the dual arms, the master end and the slave end, and the master end and the operator, and avoid the possibility of collision and misoperation in the dual-arm teleoperation process.

Description

Technical Field

[0001] The invention belongs to the technical field of robot teleoperation control, and mainly relates to a dual-arm teleoperation system and method based on a variable stiffness virtual wall and a damping force field. Background Art

[0002] Robot teleoperation technology refers to a robotic control technique in which an operator issues control commands to a slave via a master control loop over a communication link. The slave control loop then receives these commands and controls the robot to complete its tasks. Teleoperated robots are often used to control robots in complex environments and those with time delays. By leveraging human-in-the-loop control, they can accomplish tasks that are difficult for autonomous robots.

[0003] When it comes to choosing the robotic arm for a teleoperation slave, dual-arm teleoperated robots offer greater functionality, flexibility, and payload capacity than single-arm teleoperated robots, enabling them to complete more complex tasks. However, due to the overlapping workspaces of the slave's two arms, improper operation during control can cause motion interference between the two arms, posing a safety hazard of collision.

[0004] To achieve safe control of a dual-arm teleoperated robot, traditional control methods often choose to set a static or dynamic virtual wall on the slave robot arm. The control mode that sets a virtual wall on the slave side cannot intuitively feedback information about crossing the virtual wall to the operator. In the absence of relevant information about the slave virtual wall on the master side, the operator will have cognitive biases about the position and status of the robot arm after the virtual wall acts. Moreover, existing virtual walls all have fixed stiffness and lack flexibility, and cannot be dynamically adjusted according to changes in the operating environment and task requirements. In simple tasks, the fixed stiffness may be too high, limiting operational flexibility, while in tasks requiring high-precision positioning, the stiffness may be too low, affecting operational stability.

[0005] Furthermore, in typical teleoperation force feedback processes, the master system transmits force information to the operator only after the end effector interacts with the environment. Before the robotic arm makes contact with the object or obstacle, the operator can only infer the proximity of the object or obstacle through visual information. During operation, it's difficult to accurately gauge the range and speed of the robotic arm's motion, making misjudgment and incorrect operation prone to potential safety hazards. Summary of the Invention

[0006] The application is just aimed at the problem that the double-arm teleoperation robot is easy to cause collision due to improper operation in the existing double-arm teleoperation safety control technology, and provides a double-arm teleoperation system and method based on variable stiffness virtual wall and damping force field, which is composed of a master end and a slave end, the master end includes a double-hand controller, a human-computer interaction interface, a virtual scene generation unit and a calculation unit, and the slave end includes double mechanical arms, a visual and depth sensor, wherein the calculation unit is used for receiving the control instruction of the double-hand controller of the master end, generating the double mechanical arm control instruction of the slave end after the master end virtual wall and damping force field algorithm, transmitting the force feedback to the double-hand controller of the master end, and transmitting the depth information and visual information to the virtual scene generation module. The system and method give a collision warning to the operator in the form of force feedback through the hand controller at the master end, set a dynamic safety coefficient to update the stiffness of the virtual wall in real time, set a damping force field according to the variable stiffness virtual wall, also increase the experience of human-computer interaction in the double-arm teleoperation process, realize natural and effective interaction between the double arms, the master end and the slave end, and the master end and the operator, and avoid the possibility of collision and misoperation in the double-arm teleoperation process.

[0007] In order to achieve the above-mentioned purpose, the technical scheme adopted by the application is as follows: a double-arm teleoperation system based on variable stiffness virtual wall and damping force field, which is composed of a master end and a slave end, the master end includes a double-hand controller, a human-computer interaction interface, a virtual scene generation unit and a calculation unit; the slave end includes double mechanical arms, a visual and depth sensor; wherein,

[0008] The double mechanical arms are used for realizing the teleoperation scene task.

[0009] The visual and depth sensor is used for acquiring work environment information and distance information, providing proximity information to the calculation unit of the master end, and being used for three-dimensional reconstruction of the scene.

[0010] The double-hand controller corresponds to the double mechanical arms of the slave end, and is used for providing the control instruction of the double mechanical arms and providing force feedback to the operator.

[0011] The virtual scene generation unit is used for generating a virtual reality scene after processing the acquired work environment information by the calculation unit, and outputting the virtual reality scene to the human-computer interaction interface.

[0012] The human-computer interaction interface is used for providing a teleoperation human-computer interaction interface, and feeding back the virtual reality scene generated by the virtual scene generation unit to the operator.

[0013] The calculation unit is used for receiving the control instruction of the double-hand controller of the master end, generating the double mechanical arm control instruction of the slave end after the master end virtual wall and damping force field algorithm, transmitting the force feedback to the double-hand controller of the master end, and transmitting the depth information and visual information to the virtual scene generation module.

[0014] As an improvement of the present invention, the three-dimensional reconstruction includes the three-dimensional reconstruction of the robotic arm itself and the reconstruction of the working environment and obstacles. The three-dimensional reconstruction of the robotic arm itself is performed by establishing the robotic arm geometric model and current joint angle information in advance; the three-dimensional reconstruction of the working environment and obstacles is performed based on the point cloud depth information and color images obtained by the vision and depth sensors.

[0015] In order to achieve the above object, the present invention also adopts a technical solution: a dual-arm teleoperation method based on a variable stiffness virtual wall and a damping force field, comprising at least the following steps:

[0016] S1, scene reconstruction: On the master side, by building a geometric model in advance and receiving the current joint angle values ​​of the robotic arms, the current posture of the two arms is reconstructed in 3D;

[0017] S2, variable stiffness dynamic virtual wall setting: Based on the current dual-arm posture, two variable stiffness virtual walls are generated in real time. The variable stiffness dynamic virtual walls are perpendicular to the working plane and correspond to the two robotic arms respectively;

[0018] S3, damping force field setting: according to the virtual wall generated in step S2 and its stiffness, a corresponding damping force field is set, wherein the damping force field includes the virtual wall and the surrounding area;

[0019] S4, motion prediction: The master-side hand controller receives the operator's instructions and predicts the new position that the arms will reach based on the instructions;

[0020] S5, set force feedback and command processing: According to the current position of the robot arm and the damping force field obtained in step S3, corresponding force feedback is applied to the hand controller. According to the current virtual wall stiffness, the motion command is processed to achieve safe control.

[0021] As an improvement of the present invention, in step S2, the normal vector direction of the virtual wall is determined according to the direction vector formed by the end of the robotic arm on one side and the nearest point of the robotic arm on the other side, and the two virtual walls are parallel to each other.

[0022] As another improvement of the present invention, the virtual wall in step S2 has a virtual wall stiffness determined by a dynamic safety factor μ. When the safety factor μ=1, the virtual wall is completely impenetrable; when the safety factor μ=0, the virtual wall does not exist; when the safety factor μ is between 0 and 1, the virtual wall is in a variable stiffness state.

[0023] As another improvement of the present invention, the safety factor μ is related to the movement speed of the robot arm e speed , the preset safety factor e of the current operation task task Environmental factors environment and the relationship between the current position of the robot and the workspace e pos Related, specifically:

[0024] μ=ω1*e speed +ω2*e task +ω3*e environment +ω4*e pos

[0025] Among them, ω1, ω2, ω3, and ω4 are the weights of each factor.

[0026] As a further improvement of the present invention, in step S3, when the dynamic safety factor μ changes from 1 to 0, the virtual wall is in a variable stiffness state, and the damping force field is along the direction of the dynamic virtual wall normal vector, and there is a transition region Δ from 0 to the maximum damping force on the boundary of the virtual wall. d , the maximum damping force increases with the increase of safety factor μ, and the damping force field is divided into the transition area Δ d , virtual wall thickness h, and distance l from point to virtual wall are generated.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] (1) This method is highly secure. The virtual wall and the damping force field both act on the master end, and the potential collision risk can be warned before the command is sent to the slave end, thus preventing accidents before they occur.

[0029] (2) This method is highly flexible, and the virtual wall is dynamically updated in real time. The stiffness can be adjusted according to specific task requirements and mechanical status, and is suitable for a variety of operating environments.

[0030] (3) This method provides a strong sense of immersion for the operator. The operator can understand the working status of the dual-arm collaboration through force feedback while controlling the dual-arm robot to complete the task. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a schematic structural diagram of the dual-arm teleoperation system based on a variable stiffness virtual wall and a damping force field according to the present invention;

[0032] Figure 2 Schematic diagram of the realization of the double-arm variable stiffness virtual wall of the present invention;

[0033] Figure 3 This is a flowchart of the steps of the dual-arm teleoperation method based on a variable stiffness virtual wall and a damping force field of the present invention;

[0034] Figure 4 is a schematic diagram of factors related to the variable stiffness virtual wall of the present invention;

[0035] Figure 5 This is an example diagram of the damping force field in the present invention. DETAILED DESCRIPTION

[0036] The present invention will be further described below with reference to the accompanying drawings and specific embodiments. It should be understood that the following specific embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention.

[0037] Example 1

[0038] A dual-arm teleoperation system based on variable stiffness virtual wall and damping force field, such as Figure 1 As shown, it includes: dual controllers, human-computer interaction interface, virtual scene generation unit, and computing unit on the master side, and dual robotic arms, vision and depth sensors on the slave side.

[0039] The slave's dual robotic arms are equipped with grippers to implement specific teleoperation scenarios. The workspaces of the two robotic arms intersect, enabling dual-arm collaboration. In this example, two Universal Robots 10 are used as slave robotic arms, each equipped with a Robotiq two-finger electric gripper to implement specific teleoperation scenarios.

[0040] The slave's vision and depth sensors are used to obtain information about the working environment and the distance between the end of the robotic arm and the target object or obstacle, providing proximity information to the master's computing unit for 3D reconstruction. This embodiment uses RealSense as the slave's vision and depth sensor to obtain information about the robotic arm's surrounding environment and obstacles, and provide it to the master's computing unit.

[0041] The computing unit of the master end is used to receive control instructions from the master end's dual controllers, and after passing through the master end's virtual wall and damping force field algorithm, generate corresponding dual robotic arm control instructions for the slave end, transmit the calculated force feedback to the master end's dual controllers, and provide depth information and visual information to the virtual reality generation module.

[0042] The virtual scene generation unit of the master end is used to generate a virtual reality scene after processing the dual robotic arms and environmental information of the slave end through the computing unit, and display it on the human-computer interaction interface.

[0043] The computing unit and virtual scene generation unit of the host side are specifically integrated into the host side computer.

[0044] The dual hand controllers on the master side correspond to the dual robotic arms on the slave side. Each hand controller is used to provide control commands for the corresponding robotic arm and provide a certain amount of force feedback to the operator. This certain force feedback is calculated in the computing unit using a variable stiffness virtual wall and damping force field algorithm. In this embodiment, two 3D SYSTEMS touch hand controllers are used to correspond to the dual robotic arms on the slave side. Each hand controller is used to provide control commands for the corresponding robotic arm and provide a certain amount of force feedback to the operator. This force feedback is specifically implemented through the touch hand controller driver interface.

[0045] The human-computer interaction interface of the master terminal is used to provide a remote human-computer interaction interface and display a virtual scene to the operator, and can specifically exist in the form of a display screen. In this embodiment, Unity is used to build the human-computer interaction interface.

[0046] In this system, the operator observes the interactive interface and controls the hand controller, which transmits control commands to the computing unit. Control commands can also be generated and sent through the interactive interface. The computing unit, which incorporates a variable-stiffness virtual wall and damping force field algorithm, transmits the generated robotic arm control commands to the slave robotic arm via the communication module, prompting the robotic arm to respond. Simultaneously, the visual depth sensor provides proximity information, and the robotic arm transmits its status and environmental information to the master via the communication module. The computing unit processes this information through the virtual scene generation unit and displays it on the human-machine interface. The computing unit also generates force feedback information, which is then applied to the hand controller and fed back to the operator.

[0047] Therefore, the dual-arm teleoperation safety control system based on variable stiffness virtual wall and damping force field provided by the present invention can realize safe, efficient and highly interactive dual-arm teleoperation control, and improve the control accuracy and operation feel during the operation process.

[0048] Example 2

[0049] Dual-arm teleoperation method based on variable stiffness virtual wall and damping force field, such as Figure 3 As shown, the following steps are included:

[0050] Step S1, scene reconstruction: the master end performs real-time 3D reconstruction of the slave end's dual robotic arm posture and working environment;

[0051] The scene reconstruction is divided into the three-dimensional reconstruction of the robot arm and the reconstruction of the working environment. The three-dimensional reconstruction of the robot arm itself is performed by establishing the robot arm geometric model and current joint angle information in advance; the three-dimensional reconstruction of the working environment and obstacles is performed based on the point cloud depth information and color images obtained by the vision and depth sensors.

[0052] Specifically, for known robotic arm structures, a model import method is used, utilizing SolidWorks and OpenGL geometric modeling tools. CAD models of each joint are created based on the arm's parameters. These models are then imported into a local computer for joint module splicing and rendering, ultimately creating a precise geometric model of the virtual robotic arm. Real-time joint angle information is then derived from the robotic arm's feedback, completing the 3D reconstruction of the dual-arm robot. For more complex operating environments, a LiDAR-based radar system is combined with an RGBD camera to create a 3D reconstruction model based on multi-sensor fusion, completing the geometric modeling of the complex environment. This is accomplished in six steps: sensor calibration, feature point extraction, point cloud matching, global optimization, data fusion, and model extraction.

[0053] Step S2, setting a dynamic virtual wall with variable stiffness: Calculate the safety factor μ to determine the virtual wall stiffness, and set a dynamic virtual wall according to the current position of the arms;

[0054] like Figure 2 As shown, the variable stiffness dynamic virtual wall is perpendicular to the working plane, and two virtual walls are generated in real time corresponding to the two robotic arms. This embodiment establishes a virtual wall perpendicular to the xy plane, and projects the connecting rods and joints that make up the two arms onto the xy plane. Both the connecting rods and the virtual wall can be regarded as line segments in the xy plane. The projection point at the end of the left robotic arm is defined as p1, and the projection point at the end of the right robotic arm is defined as p2. First, the distance from p1 to all the projected line segments of the right robotic arm is calculated respectively, and the shortest distance and the corresponding closest point p in the right projection are obtained. n , p1 and p n The vector formed is the normal vector of the right arm virtual wall plane. At the same time, the distance threshold lw is set, that is, the distance from the right arm virtual wall to p n Do the same operation on p2 to generate two virtual walls, which are parallel to each other.

[0055] The variable-stiffness virtual wall's stiffness is determined by a dynamic safety factor μ, which is updated in real time. When the safety factor μ = 1, the virtual wall is completely impenetrable; when μ = 0, the virtual wall does not exist; and when μ is between 0 and 1, the virtual wall is in a variable-stiffness state.

[0056] The safety factor is related to the movement speed of the robot arm, the preset safety factor of the current operation task, environmental factors and the relationship between the current position of the robot arm and the workspace, such as Figure 4 shown.

[0057] The relationship between the safety factor and the robot arm's movement speed is characterized in that the safety factor is adjusted according to the speed at which the robot arm approaches the virtual wall. When the speed is fast, the safety factor is increased to prevent collisions; when the speed is slow, the safety factor is reduced to facilitate fine manipulation. maxis the maximum moving speed of the robot arm, and the speed factor is defined as e speed =v / v max ,The current moving speed is obtained through the feedback information of the robotic arm.

[0058] The relationship between the safety factor and the preset safety factor of the current operation task is characterized in that the operator presets the safety factor e according to the task type before performing the task. task It ranges from 0 to 1 and can be manually adjusted based on the human-computer interaction interface during operation to adapt to specific operational requirements.

[0059] The relationship between the safety factor and the environmental factors is characterized in that the safety factor is dynamically adjusted according to the environmental information obtained by the vision and depth sensors, and the environmental factors are defined as e environment , when the environment is more complex or close to obstacles, e environment larger, while in simple environments, e environment In this embodiment, the obstacle information is obtained based on the acquired point cloud information.

[0060] The relationship factor between the current position of the manipulator and the workspace is characterized in that when the current position of the manipulator is in the common workspace of the two arms, the safety factor increases to ensure the stability of the operation. The position factor is defined as e pos In this embodiment, the collaborative workspace of the dual-arm robot is analyzed according to the improved Monte Carlo method to obtain the collaborative workspace of the dual-arm robot. When the end position of the robot arm is closer to the center of the collaborative space, the e pos Increases, when the end position of the robot arm is far away from the collaborative space position, e pos Decrease.

[0061] The dynamic safety factor is calculated by combining the above factors, μ = ω1*e speed +ω2*e task +ω3*e environment +ω4*e pos , where ω1, ω2, ω3, and ω4 are the weights of each factor, which are adjusted according to specific application scenarios and requirements. speed 、e task 、e environment 、e pos Belongs to 0 to 1.

[0062] S3, damping force field setting: in a specific implementation, the damping force field is set according to the stiffness of the virtual wall;

[0063] A damping force field is set based on the variable stiffness virtual wall. The damping force changes with the virtual wall stiffness. As the safety factor μ changes from 1 to 0, the virtual wall stiffness decreases, and the damping force field is along the direction of the dynamic virtual wall normal vector.

[0064] In this embodiment, the force and torque acting on the operator's hand must be guaranteed to change continuously, otherwise it will cause violent oscillations in the boundary area. Therefore, there is a transition area Δ from 0 to the maximum damping force on the virtual wall boundary. d .

[0065] cu=0(l>h / 2+Δ d )

[0066]

[0067] cu=1(l≤h / 2)

[0068] where Δ d is the width of the transition area, h is the thickness of the virtual wall, l c is the distance from the end point to the center of the virtual wall, such as Figure 5 As shown. The damping force field is defined as f region =cu*f max *e, where e is the virtual wall unit normal vector, f max is the maximum damping force and increases with the increase of the safety factor μ, corresponding to the impenetrability of the virtual wall.

[0069] S4, motion prediction: In the specific implementation, the new position that the arms will reach is predicted based on the instructions obtained by the master hand controller;

[0070] Motion prediction involves mapping the movement pose of the touch hand controller to the end-arm of the robotic arm. The three rear joints of the touch hand controller correspond to the Euler angles γ, β, and α, respectively. Based on the joint angles returned by the hand controller, the rotation matrix and displacement are calculated. The end-arm pose is mapped to the hand controller coordinate system, multiplied by the hand controller's rotation matrix, and then transformed back to the robotic arm coordinate system to obtain the predicted movement position of the robotic arm.

[0071] S5, Set Force Feedback and Command Processing: In practice, force feedback is applied to the hand controller based on the current position of the robotic arm and the damping force field. The motion command is processed based on the current virtual wall stiffness. When the safety factor is 1, the virtual wall is impenetrable. If the robotic arm is predicted to cross the virtual wall, the control command is ignored.

[0072] Setting up force feedback and command processing specifically involves applying force feedback to the operator on the Touch controller based on the current position and damping force field. Commands are also processed based on the virtual wall stiffness. If a motion prediction indicates that one arm will cross the dynamic virtual wall of the other arm, the master ignores the motion command.

[0073] In summary, the present invention discloses a safety control method for a dual-arm teleoperated robot based on a variable stiffness virtual wall and a damping force field. The master-end virtual wall can predict and intervene in the collision of the two arms during teleoperation, and provide a collision warning to the operator in the form of force feedback through the hand controller at the master end. In combination with factors such as the movement speed of the robotic arm, the preset safety factor of the current operation task, environmental factors, and the relationship between the current position and the workspace, a dynamic safety factor is set to update the stiffness of the virtual wall in real time, and a damping force field is set according to the variable stiffness virtual wall. The above scheme is adopted to increase the experience of human-computer interaction during the dual-arm teleoperation process, realize natural and effective interaction between the two arms, between the master end and the slave end, and between the master end and the operator, and avoid the possibility of collision and misoperation during the dual-arm teleoperation process.

[0074] It should be noted that the above content merely illustrates the technical idea of ​​the present invention and cannot be used to limit the scope of protection of the present invention. For ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications all fall within the scope of protection of the claims of the present invention.

Claims

1. A dual-arm teleoperation system based on a variable stiffness virtual wall and a damping force field, characterized by : It consists of a master end and a slave end, the master end includes a dual controller, a human-computer interaction interface, a virtual scene generation unit and a computing unit; the slave end includes a dual robotic arm, a vision and depth sensor; wherein, The dual robotic arms are used to implement teleoperation scenario tasks; The vision and depth sensor is used to obtain working environment information and distance information, and provide proximity information to the computing unit of the main end for 3D reconstruction of the scene; The dual controllers correspond to the dual robotic arms of the slave end and are used to provide control instructions for the dual robotic arms and force feedback to the operator; The virtual scene generation unit is used to generate a virtual reality scene after processing the acquired working environment information by the computing unit, and output the virtual reality scene to the human-computer interaction interface; The human-computer interaction interface is used to provide a remote human-computer interaction interface and feed back the virtual reality scene generated by the virtual scene generation unit to the operator; The computing unit is configured to receive control instructions from the dual controllers on the master side and the current state of the robotic arms, generate control instructions for the dual robotic arms on the slave side based on the state of the robotic arms after applying the master side virtual wall and damping force field algorithm, transmit force feedback to the dual controllers on the master side, and transmit depth information and visual information to the virtual scene generation unit; The method for setting the variable stiffness virtual wall and damping force field is as follows: based on the current dual-arm posture, two variable stiffness dynamic virtual walls are generated in real time. The variable stiffness dynamic virtual walls are perpendicular to the working plane and correspond to the two robotic arms respectively; according to the generated virtual walls and their stiffness, the corresponding damping force field is set. The damping force field includes the virtual walls and the surrounding area; wherein, The virtual wall is determined by the dynamic safety factor Determine the virtual wall stiffness, when the dynamic safety factor When the virtual wall is completely impenetrable; when the dynamic safety factor When the virtual wall does not exist; when the dynamic safety factor Between 0 and 1, the virtual wall is in a variable stiffness state; Dynamic safety factor Factors related to the robot's moving speed , preset safety factor for current operation task , environmental factors and the positional factors of the relationship between the current position of the robot and the workspace Related, specifically: ； in, is the weight of each factor; the robot arm moving speed factor , by the current moving speed Obtained through the feedback information of the robotic arm, is the maximum moving speed of the robot arm; Belongs to 0 to 1.

2. The dual-arm teleoperation system based on a variable stiffness virtual wall and a damping force field according to claim 1, characterized in that: The three-dimensional reconstruction includes the three-dimensional reconstruction of the robotic arm itself and the reconstruction of the working environment and obstacles. The three-dimensional reconstruction of the robotic arm itself is performed by establishing the robotic arm geometric model and current joint angle information in advance; the three-dimensional reconstruction of the working environment and obstacles is performed based on the point cloud depth information and color images obtained by the vision and depth sensors.

3. A dual-arm teleoperation method based on a variable stiffness virtual wall and a damping force field using the system of claim 1, characterized in that: At least the following steps are included: S1, scene reconstruction: On the master side, by building a geometric model in advance and receiving the current joint angle values ​​of the robotic arms, the current posture of the two arms is reconstructed in 3D; S2, variable stiffness dynamic virtual wall setting: Based on the current dual-arm posture, two variable stiffness dynamic virtual walls are generated in real time. The variable stiffness dynamic virtual walls are perpendicular to the working plane and correspond to the two robotic arms respectively; S3, damping force field setting: according to the virtual wall generated in step S2 and its stiffness, a corresponding damping force field is set, wherein the damping force field includes the virtual wall and the surrounding area; S4, motion prediction: The master-side hand controller receives the operator's instructions and predicts the new position that the arms will reach based on the instructions; S5, set force feedback and command processing: According to the current position of the robot arm and the damping force field obtained in step S3, corresponding force feedback is applied to the hand controller. According to the current virtual wall stiffness, the motion command is processed to achieve safe control.

4. The dual-arm teleoperation method based on a variable stiffness virtual wall and a damping force field as claimed in claim 3, characterized in that: In step S2, the normal vector direction of the virtual wall is determined according to the direction vector formed by the end of one robotic arm and the nearest point of the other robotic arm, and the two virtual walls are parallel to each other.

5. The dual-arm teleoperation method based on a variable stiffness virtual wall and a damping force field as claimed in claim 4, characterized in that: The virtual wall in step S2 is composed of a dynamic safety factor Determine the virtual wall stiffness, when the dynamic safety factor When the virtual wall is completely impenetrable; when the dynamic safety factor When the virtual wall does not exist; when the dynamic safety factor Between 0 and 1, the virtual wall is in a variable stiffness state.

6. The dual-arm teleoperation method based on a variable stiffness virtual wall and a damping force field as claimed in claim 5, characterized in that: The dynamic safety factor Factors related to the robot's moving speed , preset safety factor for current operation task , environmental factors and the positional factors of the relationship between the current position of the robot and the workspace Related, specifically: ； in, is the weight of each factor.

7. The dual-arm teleoperation method based on a variable stiffness virtual wall and a damping force field according to claim 5 or 6, characterized in that: In step S3, when the dynamic safety factor When changing from 1 to 0, the virtual wall is in a variable stiffness state, and the damping force field is along the direction of the normal vector of the dynamic virtual wall. There is a transition area from 0 to the maximum damping force on the boundary of the virtual wall. , the maximum damping force varies with the dynamic safety factor The damping force field increases with the increase of , virtual wall thickness , Distance from point to virtual wall generate.

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