Surgical robot, control device, storage medium and product

Abstract

The present disclosure relates to the field of surgical robots. Embodiments of the present disclosure provide a surgical robot, a control device, a storage medium and a product. A processor in the surgical robot is configured to perform the following steps: acquiring collision degree data of the mechanical arm during movement, acquiring an actual speed of the operating master hand, determining a feedback force acting on the operating master hand based on the actual speed of the operating master hand and the collision degree data; and controlling the operating master hand to generate the feedback force, the feedback force being used for operation guidance of an operator to eliminate the collision of the mechanical arm during movement. By setting and outputting the feedback force for the operating master hand, the collision state of the mechanical arm of the surgical robot is intuitively transmitted to the operator in the form of tactile force feedback, so that the operator can perceive whether the mechanical arm collides and the severity of the collision in real time without relying on visual observation or additional prompts.

Description

Technical Field

[0001] This disclosure relates to the field of surgical robot technology, and more particularly to a surgical robot, control device, storage medium, and product. Background Technology

[0002] Surgical robots are essential equipment in the field of minimally invasive surgery, such as laparoscopic surgical robots. A surgical robot consists of three parts: a control console, an imaging carriage, and a surgical platform. Its typical operating mode is as follows: the surgeon operates the main control arm at the control console, remotely driving multiple robotic arms on the surgical platform through a master-slave control algorithm to complete delicate surgical procedures.

[0003] In actual surgery, due to the limited operating space and the complexity of the coordinated movement of multiple robotic arms, the robotic arms are prone to obstructing or colliding with each other. There is also a risk of the robotic arms squeezing or colliding with the tissues and organs of the surgical patient. Such collisions not only disrupt the surgical procedure but may also cause tissue damage to the surgical patient or damage to the robotic arm structure, seriously affecting surgical safety and operational efficiency.

[0004] Currently, in cases where the robotic arm collides during surgery, the surgical operator usually controls the robotic arm to remove the collision based on their experience. The process of removing the collision is highly dependent on the surgical operator's experience, and if the collision cannot be removed in time, the impact of the collision may be amplified. Summary of the Invention

[0005] This disclosure provides a surgical robot, control device, storage medium, and product that, in the event of a collision involving the robotic arm, generates a feedback force by controlling the main operating hand to intuitively transmit the collision state of the surgical robot's robotic arm to the operator in the form of tactile force feedback, allowing the operator to perceive in real time whether a collision has occurred and the severity of the collision.

[0006] According to one aspect of this disclosure, a surgical robot is provided, the surgical robot including a robotic arm and a master hand, wherein surgical instruments are disposed at the end of the robotic arm, and the master hand is used to control the movement of the robotic arm; the surgical robot further includes at least one processor configured to perform the following steps: The collision degree data of the robotic arm during its movement is obtained, and the collision degree data represents whether the robotic arm collides and the magnitude of the collision when it does. The actual speed of the main operating hand is obtained, and the feedback force acting on the main operating hand is determined based on the actual speed of the main operating hand and the collision degree data. The control arm generates the feedback force, which is used to guide the operator to eliminate collisions during the movement of the robotic arm.

[0007] According to another aspect of this disclosure, a control device is provided, integrated into a surgical robot, the surgical robot including a robotic arm and a master hand, the robotic arm having surgical instruments disposed at its end cap, and the master hand being used to control the movement of the robotic arm; the device includes: The collision severity data acquisition module is used to acquire collision severity data of the robotic arm during its movement. The collision severity data characterizes whether the robotic arm collides and the magnitude of the collision when it does. The feedback force determination module is used to acquire the actual speed of the main operating hand and determine the feedback force acting on the main operating hand based on the actual speed of the main operating hand and the collision degree data. The control module is used to control the main operating hand to generate the feedback force, which is used to guide the operator to eliminate collisions during the movement of the robotic arm.

[0008] According to another aspect of this disclosure, a computer-readable storage medium is provided storing computer instructions for causing a processor to perform the following steps: acquiring collision severity data of the robotic arm during movement, the collision severity data characterizing whether the robotic arm collides and the magnitude of the collision when it does; acquiring the actual speed of the operator's hand, determining a feedback force acting on the operator's hand based on the actual speed of the operator's hand and the collision severity data; controlling the operator's hand to generate the feedback force, the feedback force being used to guide the operator to eliminate collisions of the robotic arm during movement.

[0009] According to another aspect of this disclosure, a computer program product is provided, wherein the computer program, when executed by a processor, performs the following steps: acquiring collision severity data of the robotic arm during its movement, the collision severity data characterizing whether the robotic arm collides and the magnitude of the collision when it does; acquiring the actual speed of the operating hand, determining a feedback force acting on the operating hand based on the actual speed of the operating hand and the collision severity data; controlling the operating hand to generate the feedback force, the feedback force being used to guide the operator to eliminate collisions of the robotic arm during its movement.

[0010] The technical solution provided in this disclosure quantifies the degree of collision of the robotic arm through collision intensity data in the event of a collision, providing a data basis for accurately resolving the collision. By setting and outputting feedback force for the operator's main hand, the collision state of the surgical robot arm can be intuitively transmitted to the operator in the form of tactile force feedback, allowing the operator to perceive in real time whether a collision has occurred and the severity of the collision without relying on visual observation or additional prompts.

[0011] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0012] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of this disclosure and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart of the control method executed by the processor in the surgical robot in this embodiment of the present disclosure; Figure 2 This is a schematic diagram of the structure of an operating master hand provided in this disclosure; Figure 3 This is a flowchart of another control method executed by the processor in the surgical robot in this embodiment of the present disclosure; Figure 4 This is a schematic diagram of the structure of a robotic arm provided in this disclosure; Figure 5 This is a schematic diagram of the structure of a control device according to an embodiment of this disclosure; Figure 6 This is a schematic diagram of the structure of a surgical robot according to an embodiment of this disclosure. Detailed Implementation

[0014] To enable those skilled in the art to better understand the present disclosure, the technical solutions of the present disclosure will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present disclosure, and not all embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present disclosure.

[0015] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0016] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0017] The surgical robot includes a control console, an imaging trolley, and a surgical platform. The control console is equipped with a master hand. The surgical platform includes at least one robotic arm, with surgical instruments attached to its end effector. These instruments include, but are not limited to, forceps, electrocautery hooks, needle holders, and scalpels. The master hand controls the movement of the robotic arm. Specifically, the surgical operator operates the master hand from the control console. A pre-configured control algorithm in the console's processor maps the motion signals from the master hand to the robotic arm, which then moves the surgical instruments to perform the surgical procedure.

[0018] Collisions during the movement of the robotic arm can include collisions between the robotic arm and other robotic arms, collisions between the robotic arm and tissue, etc. To reduce the adverse effects of collisions during robotic arm movement, this disclosure provides a control method for rapid and precise control of collisions during robotic arm movement, prompting surgical personnel to quickly resolve such collisions.

[0019] This disclosure provides a surgical robot that includes at least one processor configured to perform a control method. Figure 1This is a flowchart illustrating a control method executed by a processor in a surgical robot according to an embodiment of this disclosure. This embodiment is applicable to situations where a collision event is detected during the movement of a robotic arm. Based on collision severity data corresponding to the collision event, a feedback force is determined to act on the operator's hand, guiding the operator to resolve the collision event. This method can be executed by a control device according to this disclosure, which can be implemented in software and / or hardware and can be integrated into the surgical robot. For example, this device can be integrated into the control console of the surgical robot.

[0020] like Figure 1 As shown, the control method for the robotic arm executed by the processor specifically includes the following steps: S110, acquire collision degree data of the robotic arm during its movement, the collision degree data characterizing whether the robotic arm collides and the magnitude of the collision when it does.

[0021] S120, obtain the actual speed of the main operating hand, and determine the feedback force acting on the main operating hand based on the actual speed of the main operating hand and the collision degree data.

[0022] S130, control the main operating hand to generate the feedback force, the feedback force is used to guide the operator to eliminate collisions of the robotic arm during movement.

[0023] During the surgery, real-time collision detection is performed on the robotic arms to determine whether collisions occur during their movement. The surgical robot may include multiple robotic arms, and collision detection is performed on each arm separately. In this embodiment, the collision detection method is not limited; any data on the degree of collision during the robotic arm's movement is sufficient.

[0024] The collision severity data of the robotic arm during its movement can be understood as the collision detection result of the robotic arm. This collision severity data characterizes whether the robotic arm has collided and the magnitude of the collision when it has occurred. In some embodiments, the collision severity data is scalar data greater than or equal to zero, and the numerical value of the collision severity data characterizes the magnitude of the collision when it has occurred. If the collision severity data is zero or within the allowable error range, it is determined that the robotic arm has not collided. If the collision severity data is greater than a first threshold, it is determined that the robotic arm has collided, and the collision severity is positively correlated with the numerical value of the collision severity data. In some embodiments, the collision severity data is three-dimensional vector data. The numerical value of the collision severity data can be determined by the magnitude of the collision severity data, and the collision direction can be determined by the direction corresponding to the collision severity data. Accordingly, if the magnitude of the collision severity data is zero or within the allowable error range, it is determined that the robotic arm has not collided. If the magnitude of the collision severity data is greater than the first threshold, it is determined that the robotic arm has collided, and the collision severity is positively correlated with the magnitude of the collision severity data.

[0025] If a collision is detected during the robotic arm's movement, the operator must promptly perform a collision clearance operation on the master hand to control the robotic arm and prevent it from colliding with the surgical instruments, in order to minimize the impact of the collision. After the robotic arm has cleared the collision, the operator can continue to operate on the master hand to control the robotic arm and perform the surgical procedure.

[0026] In this embodiment, by controlling the master hand to generate feedback force, the operator is prompted to adjust the operation of the master hand to resolve the collision of the robotic arm. For example, when the operator performs the first operation on the master hand, controlling the robotic arm to move from point A to point B, a collision is detected. The master hand is then controlled to generate feedback force. The operator, sensing this feedback force, can perform a collision resolution operation on the master hand based on the direction and magnitude of the feedback force, thereby controlling the movement of the robotic arm to resolve the collision.

[0027] The aforementioned feedback force can be understood as a force determined based on collision intensity data and the motion information of the operating hand, and applied to the operator's hand to guide the operator's actions. Optionally, the feedback force is in the form of a three-dimensional vector, the direction of the feedback force is consistent with the collision resolution direction of the robotic arm, and the magnitude of the feedback force is positively correlated with the distance the robotic arm travels to resolve the collision.

[0028] The motion information of the operating hand is acquired, and the feedback force is determined based on the motion information and collision intensity data. The motion information of the operating hand can be understood as relevant information generated by the operation of the operating hand under the control of the surgical operator, such as, but not limited to, the actual position, actual posture angle, actual velocity, actual acceleration, actual distance traveled, and actual trajectory of the operating hand's end effector. Optionally, the motion information of the operating hand includes the actual velocity of the operating hand.

[0029] In some embodiments, the motion information and collision intensity data of the operator's hand are analyzed based on a pre-built feedback force analysis model to obtain the feedback force. This feedback force analysis model can be a machine learning model or a deep learning model, etc.

[0030] In some embodiments, determining the feedback force acting on the operator's hand based on the actual speed of the operator's hand and the collision intensity data includes: determining a velocity damping force component based on the actual speed of the operator's hand and the damping coefficient; determining a collision force component based on the collision intensity data and the collision force gain ratio; and obtaining the feedback force of the operator's hand based on the velocity damping force component and the collision force component.

[0031] The velocity damping force component can be understood as a component set based on the actual velocity of the operating hand. It is used to smoothly constrain the movement of the operating hand, suppressing excessively rapid movement, shaking, or impact during operation, thus improving the stability and accuracy of the doctor's operation. The direction of this velocity damping force component is opposite to the direction of the operating hand's movement, preventing the operating hand from continuing in its original direction and thus avoiding aggravating the collision of the robotic arm. The velocity damping force component can be determined based on the product of the actual velocity of the operating hand and the damping coefficient. Here, the actual velocity of the operating hand can be three-dimensional data carrying the direction and magnitude of the movement, and the damping coefficient is a numerical value representing the magnitude of damping. The collision force component can be understood as a component set based on the collision severity data. The magnitude of the collision force component is positively correlated with the magnitude of the collision severity data. By setting a collision force component that matches the collision severity, force feedback prompts for the robotic arm's collision status can be achieved. By superimposing the velocity damping force component and the collision force component, the feedback force of the operator's hand is obtained, enabling the operator's hand to simultaneously output motion damping and collision warning effects. This ensures operational stability while improving the efficiency and safety of collision detection and collision resolution.

[0032] In some embodiments, the calculation process of feedback force can be expressed by the following formula: ; ; ; in, For the velocity damping force component, The actual speed of the operating hand. The damping coefficient; The components of the collision force; This represents the collision force gain ratio. This is collision level data, which is presented as a three-dimensional vector. For feedback force.

[0033] Based on the above embodiments, to ensure the safety of the surgical robot control process, a pre-set safety protection mechanism is implemented during the calculation of the feedback force to prevent excessive feedback force from interfering with the operator. This safety protection mechanism can be understood as setting safety upper limits for the feedback force calculation process, such as a collision force safety upper limit and a feedback force safety upper limit. The collision force safety upper limit is the maximum value of the collision force component, and the feedback force safety upper limit is the maximum value of the feedback force; here, the maximum value is the maximum magnitude of the force.

[0034] The method further includes: obtaining a pre-set upper limit value for collision force and an upper limit value for feedback force; judging the collision force component and the velocity damping force component based on the upper limit value for collision force and the upper limit value for feedback force; and updating the collision force component and / or the velocity damping force component when the magnitude of the collision force component and / or the velocity damping force component exceeds the corresponding upper limit value.

[0035] During the feedback force calculation process, based on the calculated collision force components, the magnitude of the collision force components is determined according to the upper limit of the collision force safety value. If the magnitude of the collision force component is less than or equal to the upper limit of the collision force safety value, the collision force component is maintained; if the magnitude of the collision force component is greater than the upper limit of the collision force safety value, the collision force component is updated. The direction of the updated collision force component remains unchanged, and the magnitude of the updated collision force component is the upper limit of the collision force safety value.

[0036] Similarly, based on the calculated velocity-damping force component and the calculated feedback force, the safety upper limit of the velocity-damping force is determined based on the safety upper limit of the feedback force and the magnitude of the determined collision force component. The safety upper limit of the velocity-damping force is the difference between the safety upper limit of the feedback force and the magnitude of the determined collision force component, which can be specifically expressed as: ;in, This is the upper limit of the safety value for feedback force. The magnitude of the collision force component is already determined. If the magnitude of the velocity-damped force component is less than or equal to the upper safety limit of the velocity-damped force, the velocity-damped force component is maintained, and the feedback force is determined based on the velocity-damped force component and the collision force component. If the magnitude of the velocity-damped force component is greater than the upper safety limit of the velocity-damped force, the velocity-damped force component is updated. The direction of the updated velocity-damped force component remains unchanged, and the direction of the updated velocity-damped force component is the upper safety limit of the velocity-damped force. The feedback force is determined based on the updated velocity-damped force component and the determined collision force component.

[0037] In this embodiment, a safety protection mechanism is set up to improve the safety of the surgical procedure.

[0038] Based on the above embodiments, and after determining the feedback force, the operator controls the main hand to generate the feedback force, so as to intuitively transmit the feedback to the operator in the form of tactile force feedback, thereby guiding the operator to control the robotic arm to resolve the collision through the main hand.

[0039] This can be understood as follows: the master manipulator comprises multiple joints, each corresponding to a joint motor. Each joint motor drives its corresponding joint via current. The coordinated operation of multiple joints in the master manipulator generates feedback force. The master manipulator can be an RRR structure (Revolute-Revolute-Revolute manipulator structure, a three-degree-of-freedom rotation-rotation-rotation mechanical structure), for example, see [link to example]. Figure 2 , Figure 2 This is a schematic diagram of the structure of an operating master hand provided in this disclosure.

[0040] Controlling the operating master hand to generate the feedback force includes: converting the feedback force into the drive current of each joint motor in the operating master hand, applying the drive current of each joint motor to the corresponding joint motor, so that the joint motor drives the corresponding joint based on the drive current, so that the operating master hand generates the feedback force.

[0041] Optionally, converting the feedback force into the drive current of each joint motor in the master hand includes: obtaining the Jacobian matrix corresponding to the master hand; generating joint space torque based on the Jacobian matrix and the feedback force; and converting the joint space torque into a current vector based on the torque-current conversion coefficient matrix, wherein the current vector includes the drive current of each joint motor. Here, the Jacobian matrix J is related to the structure of the master hand, and the joint space torque can be expressed as... ,in, For joint space torque, This is a feedback force. The joint space torque is located here. It is in vector form, including the control torque components corresponding to each joint in the operator's hand. The current vector can be determined as follows: ,in, This is a torque-to-current conversion coefficient matrix. This matrix is ​​pre-calibrated and is a key proportional parameter connecting the joint torque and the motor drive current. This is a current vector, which includes the drive current of each joint motor.

[0042] Optionally, the method for determining the drive current of each joint motor includes: obtaining the Jacobian matrix corresponding to the main operating hand; generating a target joint spatial torque based on the Jacobian matrix and the feedback force; collecting the actual joint torque in real time through a joint torque sensor set at each joint; determining the torque error corresponding to each joint based on the difference between the target joint spatial torque and the actual joint torque; and determining the drive current of each joint based on the torque error corresponding to each joint using a PID algorithm or an adaptive controller.

[0043] The driving current for each joint is determined using any of the methods described above and applied to the corresponding joints to generate feedback force through the coordinated action of multiple joints. The operator performs corresponding operations on the master hand based on the sensed feedback force, controlling the robotic arm to move and resolve the collision. During the collision resolution process, the collision severity data of the robotic arm is acquired in real time, and a new feedback force is determined based on this new data. This new feedback force, along with the new collision severity data and the actual speed of the master hand, is redefined until the collision is resolved and the master hand is no longer generating feedback force.

[0044] The technical solution provided in this disclosure quantifies the degree of collision of the robotic arm through collision intensity data in the event of a collision, providing a data foundation for precise collision resolution. By setting and outputting feedback force to the operator's hand, the collision state of the surgical robot arm can be intuitively transmitted to the operator in the form of tactile force feedback. This allows the operator to perceive in real time whether a collision has occurred and the severity of the collision without relying on visual observation or additional prompts, significantly improving the safety and reliability of surgical operations. By applying the feedback force to the operator's hand, the operator's movement can be guided in real time, enabling them to quickly and accurately adjust the direction and range of motion, effectively shortening the collision resolution time, avoiding compression or damage to patient tissues by the robotic arm, and improving the safety of the surgical procedure.

[0045] Figure 3 This is a flowchart of another control method executed by the processor in the surgical robot provided in this disclosure embodiment. Based on the above embodiment, the scheme has been optimized, and a method for determining the collision degree data of the robotic arm is provided. The method specifically includes: S210, based on the motion information of the master hand, determine the desired motion information of the robotic arm, the desired motion information including the desired position and the desired speed; obtain the actual motion information of the robotic arm, the actual motion information including the actual position and the actual speed.

[0046] S220, Based on the desired motion information and the actual motion information, determine the collision degree data of the robotic arm.

[0047] S230, determine the feedback force acting on the operating hand based on the actual speed of the operating hand and the collision degree data.

[0048] S240, control the main operating hand to generate the feedback force, the feedback force is used to guide the operator to eliminate collisions of the robotic arm during movement.

[0049] During the operation of the surgical robot, the movement of the robotic arm is controlled by the master hand, and a motion mapping relationship exists between the end effector of the robotic arm and the end effector of the master hand. For example, if the master hand moves a distance m in direction A, the controlled robotic arm moves a distance n in direction A. During the above movement, the distance, speed, and other motion information of the master hand and the robotic arm satisfy the above motion mapping relationship. Under the desired state, the desired motion information of the robotic arm can be calculated from the operation information of the master hand through the motion mapping relationship.

[0050] The motion information of the master arm is acquired, and then mapped to the desired motion information of the master arm by leveraging the motion mapping relationship between the end effector of the robotic arm and the end effector of the master arm. This motion mapping relationship can be represented by a motion mapping matrix.

[0051] Optionally, determining the desired motion information of the robotic arm based on the motion information of the master hand includes: acquiring the motion mapping relationship between the master hand and the robotic arm; mapping the actual position of the master hand based on the mapping relationship to obtain the desired position of the robotic arm; and mapping the actual speed of the master hand based on the mapping relationship to obtain the desired speed of the robotic arm.

[0052] The motion mapping relationship between the master hand and the robotic arm can be pre-calibrated. The calibration process includes: constructing a first coordinate system containing the master hand and a second coordinate system containing the robotic arm; controlling the robotic arm's movement through the master hand; acquiring first motion information of the master hand in the first coordinate system and second motion information of the robotic arm in the second coordinate system during the control process; and fitting the first motion information and second motion data to obtain the motion mapping relationship between the master hand and the robotic arm. Optionally, since the physical meaning and control objectives of the motion information such as position, velocity, and acceleration between the master hand and the robotic arm are different, corresponding motion mapping relationships can be set for different motion information. For example, different motion mapping relationships can be set for position and velocity to achieve mapping for different motion information.

[0053] Optionally, the master hand can be an RRR structure, and the motion information of the master hand can be obtained by calculating the joint angles of each joint in the master hand using orthogonal kinematics. Figure 2 The master manipulator consists of three rotary joints, 1, 2, and 3. Specifically, a DH coordinate system for the RRR structure and a homogeneous transformation matrix T between adjacent joints are established. i Obtain the joint angles of each joint in the master hand, and calculate the homogeneous transformation matrix T of the end effector of the master hand relative to the base based on the joint angles. The homogeneous transformation matrix can be represented as: ,in, The orientation rotation matrix for manipulating the end effector is a 3×3 matrix. The position vector of the end effector is a 3×1 three-dimensional coordinate matrix. Based on The actual position of the operator can be determined.

[0054] Optionally, during the surgical operator's control operation of the main hand, the starting and ending positions of the main hand, the starting timestamp at the starting position and the ending timestamp at the ending position are determined in the above manner. The movement distance is determined based on the starting and ending positions, the movement duration is determined based on the starting and ending timestamps, and the actual speed of the main hand can be determined based on the ratio of the movement distance to the movement duration.

[0055] The desired motion information of the robotic arm is obtained by mapping the motion of the master hand to the robotic arm through the motion mapping relationship between the master hand and the robotic arm. This desired motion information includes the desired position and the desired velocity. Specifically, based on the motion mapping relationship corresponding to the position, the actual position of the master hand is mapped to obtain the desired position of the robotic arm. Based on the motion mapping relationship corresponding to the velocity, the actual velocity of the master hand is mapped to obtain the desired velocity of the robotic arm. Here, the desired velocity and desired position of the robotic arm can be understood as the desired velocity and desired position of the robotic arm's end effector.

[0056] The actual motion information of a robotic arm can be understood as the motion information generated by the robotic arm's actual movement in space in response to the control commands of the master operator. This actual motion information includes the actual position and actual velocity. The actual motion information of the robotic arm may be the same as or different from the expected motion information. When there are no obstacles during the robotic arm's movement, the actual motion information and the expected motion information may be the same. However, if an obstacle collision occurs during the robotic arm's movement, the actual motion information and the expected motion information may differ.

[0057] The robotic arm has an RRPR structure (Revolute-Revolute-Prismatic-Revolute manipulator structure, a four-degree-of-freedom rotation-rotation-translation-rotation robotic arm structure). Figure 4 This is a schematic diagram of the structure of a robotic arm provided in an embodiment of this disclosure. The robotic arm includes four joints: rotary joints 4, 5, and 7, and a translational joint 6. The actual motion information of the robotic arm can be obtained by forward kinematics calculation of the parameters of each joint in the robotic arm. The actual motion information includes the actual position and the actual velocity. Specifically, a DH coordinate system of the RRPR structure and a homogeneous transformation matrix A between adjacent joints are established. i The system obtains the joint parameters of each joint in the master arm, including the rotation angle of the rotary joints and the displacement of the translating joints. Based on these joint parameters, it calculates the homogeneous transformation matrix T of the robotic arm's end effector relative to the base. The homogeneous transformation matrix can be represented as: ,in, Let be the attitude rotation matrix of the robotic arm's end effector, which is a 3×3 matrix. Let be the position vector of the robotic arm's end effector, and be a 3×1 three-dimensional coordinate matrix. Based on The actual position of the robotic arm can be determined.

[0058] Optionally, the starting and ending positions of the robotic arm during the process, as well as the starting timestamp at the starting position and the ending timestamp at the ending position, are used to determine the movement distance and the movement duration. The actual speed of the robotic arm can be determined based on the ratio of the movement distance to the movement duration.

[0059] If the expected motion information and the actual motion information of the robotic arm are consistent, or if the error between the expected motion information and the actual motion information is within the allowable error range, it is determined that there is no collision event during the movement of the robotic arm. If the expected motion information and the actual motion information of the robotic arm are inconsistent, or if the difference between the expected motion information and the actual motion information exceeds the allowable error range, it is determined that there is a collision event during the movement of the robotic arm. Collision detection is performed based on the difference between the expected motion information and the actual motion information to obtain the collision detection result.

[0060] In some embodiments of this disclosure, determining the collision severity data of the robotic arm based on the desired motion information and the actual motion information includes: determining a position deviation term based on the desired position and the actual position; determining a velocity weighting term based on the desired velocity and the actual velocity; and determining the collision severity data of the robotic arm based on the position deviation term and the velocity weighting term.

[0061] The position deviation term can be determined by the difference between the expected and actual positions, where the expected and actual positions are three-dimensional coordinate data, and the position deviation term is three-dimensional vector data. Optionally, a velocity weighting term can be determined by the velocity difference between the expected and actual velocities, using this difference as the weight of the position deviation term. Alternatively, the velocity weighting term can be determined by the sum of the reciprocals of the expected and actual velocities. Alternatively, the velocity weighting term can be determined by the sum of the reciprocals of the absolute values ​​of the expected and actual velocities.

[0062] The collision severity data of the robotic arm is determined using the following formula: ;in, For the position deviation term, For the desired position, The actual location; For the speed weighting term, The desired speed; The actual speed is denoted by K; K is the proportional gain coefficient, which is a pre-set hyperparameter.

[0063] The technical solution provided in this embodiment acquires expected and actual motion data during the movement of the robotic arm, and calculates collision severity data using these data to characterize whether a collision occurs and the magnitude of the collision. This collision severity data quantifies the degree of collision, providing a data foundation for precise collision mitigation. Furthermore, the collision severity data determines the feedback force, and the operator's hand is controlled to generate this force, allowing the collision state of the surgical robot arm to be intuitively transmitted to the operator in the form of tactile feedback.

[0064] Figure 5 This is a schematic diagram of a control device provided in an embodiment of the present disclosure. The device can be implemented using software and / or hardware. It is integrated into a surgical robot, which includes a robotic arm and a master hand. Surgical instruments are disposed at the end of the robotic arm, and the master hand is used to control the movement of the robotic arm, such as… Figure 5 As shown, the device specifically includes: a collision intensity data acquisition module 310, a feedback force determination module 320, and a control module 330.

[0065] The collision degree data acquisition module 310 is used to acquire the collision degree data of the robotic arm during its movement. The collision degree data represents whether the robotic arm collides and the magnitude of the collision when it does. The feedback force determination module 320 is used to acquire the actual speed of the operating hand and determine the feedback force acting on the operating hand based on the actual speed of the operating hand and the collision degree data. The control module 330 is used to control the main operating hand to generate the feedback force, which is used to guide the operator to eliminate collisions during the movement of the robotic arm.

[0066] The technical solution in this embodiment quantifies the degree of collision of the robotic arm by using collision intensity data, providing a data basis for accurately resolving the collision. By setting and outputting feedback force for the operator's hand, the collision status of the surgical robot arm can be intuitively transmitted to the operator in the form of tactile force feedback. This allows the operator to perceive in real time whether a collision has occurred and the severity of the collision without relying on visual observation or additional prompts, significantly improving the safety and reliability of surgical operations.

[0067] Based on the above embodiments, optionally, the feedback force determination module 320 is further configured to: determine the velocity damping force component based on the actual speed and damping coefficient of the operating hand; determine the collision force component based on the collision degree data and the collision force gain ratio; and obtain the feedback force of the operating hand based on the velocity damping force component and the collision force component.

[0068] Optionally, the feedback force determination module 320 is further configured to: obtain a preset upper limit value for collision force and an upper limit value for feedback force; determine the collision force component and the velocity damping force component based on the upper limit value for collision force and the upper limit value for feedback force, and update the collision force component and / or the velocity damping force component when the magnitude of the collision force component and / or the velocity damping force component exceeds the corresponding upper limit value.

[0069] Based on the above embodiments, optionally, the operating master hand includes multiple joints, each joint corresponding to a joint motor, and the joint motor drives the corresponding joint; The control module 330 is also used to: convert the feedback force into the drive current of each joint motor in the operating master hand, and apply the drive current of each joint motor to the corresponding joint motor so that the joint motor drives the corresponding joint based on the drive current, so that the operating master hand generates the feedback force.

[0070] Optionally, the control module 330 is further configured to: obtain the Jacobian matrix corresponding to the main operating hand; generate joint space torque based on the Jacobian matrix and the feedback force; and convert the joint space torque into a current vector based on the torque-current conversion coefficient matrix, wherein the current vector includes the drive current of each joint motor.

[0071] Optionally, the feedback force is in the form of a three-dimensional vector, and the direction of the feedback force is consistent with the collision release direction of the robotic arm.

[0072] Optionally, the collision degree data acquisition module 310 is further configured to: determine the expected motion information of the robotic arm based on the motion information of the operating master hand, the expected motion information including the expected position and the expected speed; acquire the actual motion information of the robotic arm, the actual motion information including the actual position and the actual speed; and determine the collision degree data of the robotic arm based on the expected motion information and the actual motion information.

[0073] The above-described products can perform the methods provided in any embodiment of this disclosure, and have the corresponding functional modules and beneficial effects for performing the methods.

[0074] Figure 6 A schematic diagram of a surgical robot 10 that can be used to implement embodiments of the present disclosure is shown. The surgical robot includes a console, an imaging carriage, and a surgical platform. A control hand is provided on the console. The surgical platform includes at least one robotic arm, and surgical instruments are provided at the end of the robotic arm. The surgical instruments include, but are not limited to, forceps, electric hooks, needle holders, and scalpels. The control hand is used to control the movement of the robotic arm. Figure 6 The above structures are not shown in the diagram. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of this disclosure described and / or required herein.

[0075] like Figure 6As shown, the surgical robot 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 and a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer programs stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the surgical robot 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0076] Multiple components in the surgical robot 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, optical disk, etc.; and a communication unit 19, such as a network card, modem, wireless transceiver, etc. The communication unit 19 allows the surgical robot 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0077] Processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as control methods. The control method includes: acquiring collision severity data of the robotic arm during movement, the collision severity data characterizing whether the robotic arm collides and the magnitude of the collision when it does; acquiring the actual speed of the operator's hand, determining a feedback force acting on the operator's hand based on the actual speed of the operator's hand and the collision severity data; controlling the operator's hand to generate the feedback force, the feedback force being used to guide the operator to eliminate collisions of the robotic arm during movement.

[0078] In some embodiments, the control method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted onto the surgical robot 10 via read-only memory (ROM) 12 and / or communication unit 19. When the computer program is loaded into random access memory (RAM) 13 and executed by processor 11, one or more steps of the control method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to execute the control method by any other suitable means (e.g., by means of firmware).

[0079] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0080] Computer programs used to implement the methods of this disclosure may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0081] In the context of this disclosure, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0082] To provide interaction with the user, the systems and techniques described herein can be implemented on a surgical robot having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the surgical robot. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0083] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0084] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0085] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this disclosure can be achieved, and this is not limited herein.

[0086] This disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the control method according to any embodiment of this disclosure.

[0087] In implementing a computer program product, computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed 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 can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0088] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A surgical robot, characterized in that, The surgical robot includes a robotic arm and a master hand. Surgical instruments are mounted at the end of the robotic arm, and the master hand is used to control the movement of the robotic arm. The surgical robot also includes at least one processor configured to perform the following steps: The collision degree data of the robotic arm during its movement is obtained. The collision degree data characterizes whether the robotic arm collides and the magnitude of the collision when it does. The collision degree data is determined by a position deviation term and a velocity weighting term. The velocity weighting term is used as the weight of the position deviation term. The position deviation term is determined based on the expected position and the actual position of the robotic arm. The velocity weighting term is determined based on the expected velocity and the actual velocity of the robotic arm. The actual speed of the main operating hand is obtained, and the feedback force acting on the main operating hand is determined based on the actual speed of the main operating hand and the collision degree data. The feedback force is determined based on the velocity damping force component and the collision force component. Obtain the pre-set upper limit values ​​for collision force and feedback force; Based on the upper limit of the collision force safety and the upper limit of the feedback force safety, the collision force component and the velocity damping force component are judged, and when the magnitude of the collision force component and / or the velocity damping force component exceeds the corresponding upper limit, the collision force component and / or the velocity damping force component are updated. The control arm generates the feedback force, which is used to guide the operator to eliminate collisions during the movement of the robotic arm.

2. The surgical robot according to claim 1, characterized in that, The feedback force acting on the operator's hand is determined based on the actual speed of the operator's hand and the collision intensity data, including: The velocity damping force component is determined based on the actual speed and damping coefficient of the operating master hand. The collision force components are determined based on the collision intensity data and the collision force gain ratio. The feedback force of the operator's main hand is obtained based on the velocity damping force component and the collision force component.

3. The surgical robot according to claim 1, characterized in that, The main operating hand includes multiple joints, each joint corresponds to a joint motor, and the joint motor drives the corresponding joint. Controlling the main hand to generate the feedback force includes: The feedback force is converted into the drive current of each joint motor in the operator's hand, and the drive current of each joint motor is applied to the corresponding joint motor so that the joint motor drives the corresponding joint based on the drive current, thereby generating the feedback force in the operator's hand.

4. The surgical robot according to claim 3, characterized in that, Converting the feedback force into drive current for each joint motor in the operator's hand includes: Obtain the Jacobian matrix corresponding to the main operator; Joint space torque is generated based on the Jacobian matrix and the feedback force; Based on the torque-current conversion coefficient matrix, the joint space torque is converted into a current vector, which includes the drive current of each joint motor.

5. The surgical robot according to claim 1, characterized in that, The feedback force is in the form of a three-dimensional vector, and the direction of the feedback force is consistent with the collision release direction of the robotic arm.

6. A control device, characterized in that, Integrated into a surgical robot as described in any one of claims 1-5, the surgical robot includes a robotic arm and a master hand, with surgical instruments disposed at the end of the robotic arm, and the master hand used to control the movement of the robotic arm; the device includes: The collision severity data acquisition module is used to acquire collision severity data of the robotic arm during its movement. The collision severity data characterizes whether the robotic arm collides and the magnitude of the collision when it does. The collision severity data is determined by a position deviation term and a velocity weighting term. The velocity weighting term serves as the weight of the position deviation term. The position deviation term is determined based on the expected position and the actual position of the robotic arm. The velocity weighting term is determined based on the expected velocity and the actual velocity of the robotic arm. The feedback force determination module is used to acquire the actual speed of the operating hand and determine the feedback force acting on the operating hand based on the actual speed of the operating hand and the collision degree data; the feedback force is determined based on the velocity damping force component and the collision force component. The feedback force determination module is further configured to obtain a pre-set upper limit value for collision force and an upper limit value for feedback force; based on the upper limit value for collision force and the upper limit value for feedback force, to determine the collision force component and the velocity damping force component, and to update the collision force component and / or the velocity damping force component when the magnitude of the collision force component and / or the velocity damping force component exceeds the corresponding upper limit value. The control module is used to control the main operating hand to generate the feedback force, which is used to guide the operator to eliminate collisions during the movement of the robotic arm.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a processor to perform steps performed by a processor in a surgical robot as described in any one of claims 1-5.

8. A computer program product, characterized in that, The computer program product includes a computer program that is executed by a processor in the surgical robot as described in any one of claims 1-5.

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