A control method for low-latency teleoperation of a surgical robot

Abstract

The application discloses a control method for low-latency teleoperation of a surgical robot, which comprises the following steps: firstly, a low-latency communication channel with the latest data frame as the priority is established, a UDP protocol is used for data transmission between the master and the slave, and a fixed-length position queue is maintained; and pose information of a master hand is received in real time; subsequently, a flexible arm nonlinear kinematics mapping algorithm with an elliptical weighting mechanism is introduced to convert the pose of the master hand into a bending state of a slave flexible arm; finally, a coupling compensation amount required is calculated according to the bending state, and a final control instruction is generated by fusion. By using the application, the problems of communication latency accumulation, motion response lag and action coupling of the flexible arm caused by structural characteristics in the teleoperation process of the surgical robot are effectively solved. The application can be widely applied to the technical field of medical robot control.

Description

Technical Field

[0001] This invention relates to the field of medical robot control technology, and in particular to a control method for low-latency teleoperation of surgical robots. Background Technology

[0002] Minimally invasive surgical robot systems, as an important component of modern medical technology, have been widely used in various delicate surgeries. The master-slave teleoperation architecture is the core control mode of surgical robot systems. The master arm collects the surgeon's movement commands, which are then processed by the control system to drive the slave robotic arm to perform the corresponding actions. In existing technologies, surgical robot systems typically use a TCP / IP-based communication architecture for master-slave data transmission. The master control unit ensures communication reliability by establishing a connection and verifying the integrity of data packets. Furthermore, for the motion control of the flexible robotic arm, existing technologies generally employ impedance control models that include inertia, damping, and stiffness terms, calculating the motion trajectory and force feedback of the end effector through dynamic equations.

[0003] However, during the teleoperation of surgical robots, the accumulation of communication delay and the coupling phenomenon of flexible arm motion become key factors affecting system performance, making it difficult to achieve the ideal level of real-time tracking of master-slave operation and decoupling accuracy of motion control. Summary of the Invention

[0004] This application provides a control method for low-latency teleoperation of surgical robots, which can solve the problems of communication delay accumulation, motion response lag, and motion coupling caused by the structural characteristics of flexible arms during the teleoperation of surgical robots. To achieve the above objectives, this application provides the following technical solution: First, a low-latency communication channel prioritizing the latest data frame is established for remote control data transmission. Then, a flexible arm nonlinear kinematic mapping algorithm incorporating an elliptic weighting mechanism is used to transform the master arm pose into the bending shape of the slave flexible arm. Finally, the required coupling compensation is calculated based on this bending state, and the resulting data is fused to generate the final control command.

[0005] In some embodiments, the method further includes: performing kinematic parameter self-tuning based on visual feedback before remote control operation.

[0006] In some embodiments, to address the cumulative latency issue of traditional communication protocols, UDP is used for master-slave data transmission at the communication layer. The master control end starts an independent communication thread and sets it to listen on the port in non-blocking mode. Based on this, a latest-frame-first-out (LSF) data processing strategy is implemented: a fixed-length first-in-first-out (FIFO) position queue is maintained for each driving degree of freedom. When the communication thread parses and receives a new teleoperation command data packet, it directly overwrites the old data in the queue. This mechanism forces the control algorithm to read and process only the latest target pose in each loop, thereby reducing the latency introduced by the communication link to a low level.

[0007] Based on the above scheme, this invention provides a control method for low-latency teleoperation of surgical robots. By constructing an integrated response system of communication-calibration-solution-compensation, it effectively improves the real-time performance and control accuracy of the system. This method combines a bottom-level latest frame priority strategy with UDP non-blocking communication to optimize the data transmission mechanism. In network fluctuation environments, by prioritizing the processing of the latest instructions and discarding lagging data, it significantly reduces the cumulative latency of the communication link, thereby improving the follow-up performance of the slave hand to the master hand's instructions and reducing the lag in teleoperation. Furthermore, the introduced visual feedback parameter self-tuning stage calibrates the physical stiffness differences that may arise from manufacturing tolerances and material properties of the flexible robotic arm. Compensation parameters are obtained using visual inverse kinematics, improving the fitting degree of the theoretical model to the physical object. Simultaneously, a decoupling compensation model based on geometric relationships compensates for the "bending interference tension" phenomenon of the flexible arm. Combined with an elliptic weighted mapping algorithm, it enhances the robot's adaptability to asymmetric anatomical environments. In summary, this invention effectively improves the surgeon's operating feel and the system's automation level while ensuring the safety of surgical operations. Attached Figure Description

[0008] Figure 1 This is a flowchart of the steps of a control method for low-latency teleoperation of a surgical robot according to the present invention; Figure 2 This is a structural schematic diagram of a specific embodiment of the surgical robot of the present invention; Figure 3 This is a schematic diagram of the self-tuning process of the present invention; Figure 4 This is a schematic diagram of the decoupling compensation parameters for the clamping action of the present invention.

[0009] In the image: 1. Positioning arm; 2. Flexible surgical robot; 3. High-performance computer; 4. Operating hand; 5. Self-adjusting binocular camera. Detailed Implementation

[0010] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0011] It should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0012] It should be understood that the terms "system," "apparatus," "unit," and / or "module" used in this application are a method of distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0013] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "a," and / or "the" are not specifically singular and may include the plural. Generally, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements. An element defined by the phrase "comprising an..." does not exclude the presence of other identical elements in the process, method, product, or apparatus that includes the element.

[0014] In the description of the embodiments of this application, "a plurality of" refers to two or more. The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0015] Furthermore, flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, the steps can be processed in reverse order or simultaneously. Additionally, other operations can be added to these processes, or one or more steps can be removed from them.

[0016] Reference Figure 1 This is a flowchart illustrating an optional example of the control method for low-latency teleoperation of a surgical robot proposed in this invention. This method can be applied to computer devices, and the control method proposed in this embodiment may include, but is not limited to, the following steps: Step S1: Construct a low-latency communication link based on the latest frame priority strategy; Step S2: Self-tuning of kinematic parameters based on visual feedback; Step S3: Receive master hand pose data based on low-latency communication link; Step S4: Based on the main hand pose data, perform elliptical weighted nonlinear kinematic mapping of the flexible arm to obtain the bending state; Step S5: Calculate the coupling compensation amount and generate the final control command based on the bending state.

[0017] The above method is applied to a surgical robot system with a master-slave teleoperation architecture. This system includes a positioning arm 1, a flexible surgical robot 2, a high-performance computer 3, and a master operator 4. The positioning arm 1 is fixed to the ground or a trolley to support and roughly position the surgical robot. The base of the flexible surgical robot 2 is fixed to the end of the positioning arm 1, and its front end is a continuous robotic arm with multi-degree-of-freedom bending capabilities. The master operator 4 is used to collect the surgeon's hand movement commands. The high-performance computer 3 serves as the system's control core and is connected to both the flexible surgical robot 2 and the master operator 4 via communication cables. This computer is responsible for running the low-latency control algorithm of this invention, including kinematic parameter self-tuning, nonlinear mapping calculation, and communication scheduling. Furthermore, during system initialization, a self-tuning binocular camera 5 is placed within the visible range of the flexible robotic arm's end effector for parameter calibration.

[0018] In some feasible embodiments, step S1 specifically includes: To address the cumulative latency issue caused by the handshake confirmation and packet loss retransmission mechanism in the traditional TCP communication protocol, this invention employs the UDP protocol at the communication layer for master-slave data transmission.

[0019] "UDP protocol" is an abbreviation for User Datagram Protocol, which is a connectionless, unreliable but low-overhead transport layer communication protocol. Its inherent characteristics are that it does not perform handshake to establish a connection, does not guarantee the delivery of data packets, and does not provide retransmission and ordering mechanisms. In this embodiment, the protocol is used to transmit pose commands between the master end and the slave end of the surgical robot. Its role is to eliminate the random queuing delay introduced by the TCP protocol due to acknowledgment and packet loss retransmission, so that the data transmission delay is stable and controllable, and depends only on the one-way network propagation time and processing delay. The high-performance computer 3 starts an independent communication thread and sets the port to non-blocking mode for listening.

[0020] Among them, "independent communication thread" refers to an execution unit created and scheduled separately for communication tasks in the operating system running on a high-performance computer (3), which is physically isolated from the main control algorithm thread; "non-blocking mode" means that when the thread calls the socket receive function (such as recvfrom()), if there is no data to be read at present, it immediately returns an error code instead of suspending and waiting; the role of this technical feature is to avoid communication waiting causing the main control loop to be interrupted, and to ensure that the core control logic such as kinematic calculation and state update is executed continuously with a constant period, thereby improving the real-time performance and determinism of the system; Based on this, the system implements a "latest frame priority" data processing strategy: for each driving degree of freedom of the flexible surgical robot, a first-in-first-out position queue of fixed length 1 is maintained in memory.

[0021] Among them, "drive degrees of freedom" refers to the number of motion axes in a flexible surgical robot controlled by independent motors or actuators, such as pitch, yaw, telescoping, and gripping; "fixed-length first-in-first-out position queue" is a buffer structure that only retains the target pose data of the most recent N frames. Its length is set to a constant (such as 1) during the system initialization phase and does not dynamically expand with the running time; the function of this structure is to limit the instruction cache depth and provide a data organization basis for the subsequent "latest frame first" strategy; The working logic is as follows: when the communication thread parses and receives a new teleoperation command data packet, it directly overwrites the old data in the queue. This mechanism forces the control algorithm to only read and process the latest target pose in each control loop, actively discarding lagging data, thereby minimizing the latency introduced by the communication link.

[0022] "Covering" means that the newly parsed target pose data is directly written to the head of the queue (or the only valid slot), regardless of whether the original position already contains historical data. This operation does not trigger queue movement or memory reallocation, and only completes an atomic assignment. Its purpose is to enforce the "latest frame priority" strategy - that is, to ensure that the algorithm always obtains the latest parsed result from the communication thread when it reads, thus completely avoiding the instruction lag problem caused by network jitter or processing delay. This embodiment eliminates the uncertainty and latency caused by connection management and retransmission mechanisms by replacing the traditional TCP protocol with the UDP protocol; it decouples the execution rhythm of data reception and motion control by using an independent non-blocking communication thread; and it constructs a low-latency communication link that strictly follows the "latest frame first" principle by combining a fixed-length FIFO queue divided by degrees of freedom and its forced overlay mechanism. On this basis, the control algorithm always generates response instructions based on the master's intention closest to the current moment, which significantly suppresses the cumulative latency and instruction obsolescence during teleoperation, thus providing a high-fidelity, low-perceived-latency real-time control foundation for the flexible surgical robot.

[0023] In some feasible embodiments, step S2 specifically includes: To address the anisotropy of physical stiffness in flexible robotic arms caused by manufacturing tolerances, uneven wire rope tension, or material properties, this invention introduces a visual self-tuning process before formal remote operation.

[0024] like Figure 3 As shown, the specific process is as follows: The flexible robotic arm is controlled to execute multiple preset planar circular trajectory motion commands in an open-loop state; the actual spatial coordinate sequence of the robotic arm's end effector is captured in real time using a binocular vision acquisition device; the actual response of the steel wire rope is calculated using an inverse kinematics model, and a least-squares optimization objective function is constructed; the geometric error between the "theoretical standard circular trajectory" and the "actual visually captured trajectory" is compared, and the optimal asymmetric weighting coefficient is iteratively solved. This process transforms the nonlinear deviations of physical objects into precise mathematical parameters, which are then used in subsequent kinematic mapping steps.

[0025] In some feasible embodiments, step S4 specifically includes: During teleoperation, the parameters obtained by S2 self-tuning are used to perform kinematic mapping that combines elliptic weighting algorithm with soft limiting.

[0026] First, obtain the normalized coordinates of the main and mobile devices. Using self-tuned optimized asymmetric weighting coefficients Calculate the weighted coordinates: Then the weighted amplitude is calculated. and direction angle : Finally, the hyperbolic tangent function is used to measure the amplitude. A soft saturation process is performed to obtain the final target bending angle. This method achieves differentiated bending response sensitivity of the flexible arm in different directions while ensuring operational accuracy, and avoids the control shock caused by hard limiting.

[0027] The hyperbolic tangent function is a bounded continuous function with S-shaped monotonically increasing characteristics. In its technical field, this function is often used as a smoothing limiter to replace hard threshold truncation and avoid system oscillation caused by abrupt changes in the control signal. In this embodiment, the function is configured to nonlinearly compress the weighted amplitude to map it to the maximum bending angle range allowed by the flexible arm, while retaining the high sensitivity of small-amplitude operations and the asymptotic convergence characteristics of large-amplitude operations. "Target bending angle" refers to the final angle command value output after soft saturation processing, which is used to drive the flexible arm bending actuator. Its technical meaning is the steady-state bending degree that the robotic arm should achieve under the current operating intention. In this embodiment, this angle serves as a key amplitude dimension of the bending state, which together with the direction angle constitutes a complete description of the bending state. Moreover, its smooth transition characteristics effectively suppress the step impact caused by traditional hard limiting, and improve the smoothness of the doctor's operation. This embodiment introduces asymmetric weighting coefficients to map the master hand pose data to an ellipsoidal operating space that matches the anisotropic stiffness of the flexible arm. Based on this, by calculating the weighted amplitude and orientation angle, the three-dimensional input is decoupled into two independently adjustable kinematic dimensions: intensity and orientation. Furthermore, a hyperbolic tangent function is used to apply soft saturation processing to the amplitude, ensuring that the target bending angle maintains a monotonic, continuous, and asymptotic response across the entire operating range. Finally, the orientation angle and the target bending angle together constitute the bending state, which not only accurately reflects the actual bending capability boundary of the flexible arm but also provides a clear, stable, and differentiable state interface for subsequent coupling compensation. This significantly improves the accuracy and compliance of teleoperation mapping without increasing model complexity.

[0028] In some feasible embodiments, step S5 specifically includes: To address the unique "bending interference opening and closing" phenomenon of flexible arms—that is, when the arm bends, it pulls on the clamping wire rope, causing malfunctions—this invention establishes a decoupling compensation model. During the control loop, the model is updated in real-time based on the bending state of the flexible arm. Calculate the change in coupling length caused by the clamp driving wire rope. And perform differential compensation on the end clamping command.

[0029] Here, "bending state" refers to a set of two-dimensional parameters used to fully characterize the bending morphology of the end effector of a flexible surgical robot. Technically, it means mapping the three-dimensional master hand pose to a low-dimensional kinematic state that directly corresponds to the physical configuration of the flexible arm. In the relevant technical field, this state is usually used as the input basis for subsequent decoupling control, trajectory planning, or force feedback calculation. In this embodiment, by separating the two orthogonal degrees of freedom of bending intensity (target bending angle) and bending orientation (direction angle), this state achieves efficient modeling of the nonlinear motion characteristics of the flexible arm, which not only meets the real-time requirements but also retains key geometric constraint information. The specific calculation formula is as follows: in, This is the final control signal sent to the gripper motor. This refers to the clamping action command input from the main handpiece. The coupling compensation amount... The calculation follows the following model: In the formula, The radius of the wire rope distribution. The installation angle of the gripper drive wire rope on the cross-section. This reverse compensation mechanism ensures that the opening and closing state of the end effector remains stable during the large-angle bending of the robotic arm.

[0030] The parameters involved in the design, in real-world scenarios, are as follows: Figure 4 As shown.

[0031] Based on the above methods, this invention achieves high-speed response across the entire communication, computation, and execution chain of surgical robot teleoperation control; it solves the problem of data packet accumulation and latency buildup caused by handshake confirmation and packet loss retransmission mechanisms when the existing teleoperation control system relies on the TCP protocol for data transmission, and eliminates the lag in master-slave operation; at the same time, it solves the problems of low kinematics calculation efficiency and severe motion coupling of flexible robotic arms, using a high-efficiency analytical algorithm to replace cumbersome iterative optimization and dynamic model calculation, and compensates for changes in the gripper wire rope path caused by arm bending in real time and accurately, eliminating mechanical coupling errors caused by bending interference with opening and closing, ensuring the consistency and absolute stability of the end effector's movements in complex dynamic environments, and ultimately significantly improving the system's real-time performance while ensuring the safety of surgical operations and the surgeon's immersive operating experience.

[0032] A control system for low-latency teleoperation of a surgical robot, comprising: Link construction unit, used to perform step S1; The parameter self-tuning unit is used to execute step S2; The communication unit is used to execute step S3; A bending state calculation unit is used to execute step S4; The compensation unit is used to perform step S5.

[0033] The content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0034] A storage medium storing processor-executable instructions, which, when executed by a processor, are used to implement a control method for low-latency teleoperation of a surgical robot as described above.

[0035] The content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0036] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A control method for low-latency teleoperation of a surgical robot, characterized in that, Includes the following steps: Construct a low-latency communication link based on the latest frame priority strategy; Based on the aforementioned low-latency communication link, receive master hand pose data; Based on the main hand pose data, an elliptical weighted nonlinear kinematic mapping of the flexible arm is performed to obtain the bending state; Based on the bending state, the coupling compensation amount is calculated and the final control command is generated; The low-latency communication link includes: Data transmission between the master and slave ends is performed using the UDP protocol. The main control unit starts an independent communication thread and sets it to non-blocking mode to listen on the port; An independent communication thread refers to an execution unit created and scheduled separately for communication tasks within the operating system of a high-performance computer, physically isolated from the main control algorithm thread; non-blocking mode means that when the thread calls the socket receive function, if there is no data to be read, it immediately returns an error code instead of suspending and waiting; For each driving degree of freedom, maintain a fixed-length first-in-first-out position queue; When the communication thread parses and receives a new teleoperation instruction data packet, it overwrites the old data in the queue. Also includes: Control the robotic arm to execute preset motion commands, and calculate the actual spatial coordinate sequence of the robotic arm's end effector based on binocular vision; Based on the actual spatial coordinate sequence, the actual response of the wire rope is calculated by combining the inverse kinematics model, and the actual visual capture trajectory is obtained. Construct a least-squares optimization objective function, compare the geometric error between the theoretical trajectory and the actual visual capture trajectory, and solve for the optimal asymmetric weighting coefficients. The step of performing elliptical-weighted nonlinear kinematic mapping of the flexible arm based on the master hand pose data to obtain the bending state specifically includes: The main hand pose data is weighted based on asymmetric weighting coefficients to obtain the weighted coordinates; Calculate the weighted magnitude and direction angle based on the weighted coordinates; The target bending angle is obtained by performing soft saturation processing on the weighted amplitude based on the hyperbolic tangent function. The bending state of the robotic arm is defined by the direction angle and the target bending angle. The formula for calculating the weighted magnitude and direction angle based on the weighted coordinates is as follows: in, This represents the weighted amplitude. This represents the weighted coordinates. Indicates the direction angle; The formula for calculating the coupling compensation amount is as follows: in, This represents the coupling compensation amount. Indicates the radius of the wire rope distribution. This indicates the installation angle of the clamp-driven wire rope on the cross-section. Indicates the bending angle. Indicates the direction angle.

2. A control system for low-latency teleoperation of a surgical robot, characterized in that, A control method for performing low-latency teleoperation of a surgical robot as described in claim 1, comprising: Link building unit, used to build low-latency communication links based on the latest frame priority strategy; The communication unit receives master hand pose data based on the low-latency communication link; The bending state calculation unit performs elliptical weighted nonlinear kinematic mapping of the flexible arm based on the main hand pose data to obtain the bending state; The compensation unit is used to calculate the coupling compensation amount and generate the final control command based on the bending state.

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