Protection system for feeding back collision state of mechanical arm of surgical robot in real time

Abstract

The invention relates to the technical field of medical robots, in particular to a protection system for feeding back the collision state of a mechanical arm of a surgical robot in real time, and the system comprises a multi-mode sensing module, a dynamic safety boundary generation module, a central decision and control module and a man-machine cooperative feedback module. Surgical environment data are collected in real time through a force and torque sensor and an intracavity pressure sensor, active obstacle avoidance and flexible yielding of a mechanical arm are achieved based on an admittance-impedance composite control algorithm, and a virtual clamp is adjusted in a self-adaptive mode according to the real-time pressure data in combination with a dynamic safety boundary technology. And the risk of collision between the mechanical arm and tissues and between the mechanical arm and instruments in the urinary surgery is effectively solved. The system has the advantages of being comprehensive in perception, timely in response and smooth in control, and the safety of urinary surgery such as prostatic resection and partial kidney resection is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of medical robot technology, and more specifically to a protective system that provides real-time feedback on the collision status of a surgical robot arm. Background Technology

[0002] In urological surgeries, such as prostatectomy, partial nephrectomy, and ureteroscopic lithotripsy, surgical robots can improve operational precision, but they also bring safety challenges. Collision risk: In the narrow body cavity, multiple robotic arms may collide accidentally with each other, or with the patient's tissues or critical organs, such as the ureter and renal blood vessels.

[0003] Perception lag: Existing systems mostly rely on vision or preset paths for collision avoidance, lacking the ability to fuse perception and instantaneous response to multiple physical quantities such as real-time contact force and intracavity pressure.

[0004] Control rigidity: Traditional emergency stop or rerouting strategies can disrupt surgical continuity and affect surgical efficiency, especially when dealing with soft tissue deformation and physiological peristalsis, where they are not adaptable enough.

[0005] According to the search, CN112245014B discloses a medical robot, a method for detecting collisions of a robotic arm, and a storage medium, which performs collision detection by using a pre-set bounding box model of the execution component. Publication No. CN120884365A describes a multi-module collaborative real-time decision-making and planning system for surgical robots, which achieves collision detection by monitoring the current of the drive motor.

[0006] However, these methods struggle to achieve accurate real-time collision detection and compliant active protection in the complex and dynamic environment of urological surgery.

[0007] To overcome the above-mentioned shortcomings, the present invention provides a protection system that integrates real-time perception, dynamic boundary and active compliance control. Summary of the Invention

[0008] To address the aforementioned technical problems, this invention provides a protection system that provides real-time feedback on the collision status of a surgical robot arm, thereby mitigating the risk of collisions between the robot arm and tissues or instruments during urological surgery. Through dynamic safety boundaries and impedance control, it achieves active and compliant protection.

[0009] include: The multimodal sensing module is used to collect real-time pose information of the robotic arm, interaction force information between the robotic arm and tissues or instruments, and real-time pressure information within the urinary system cavities. The dynamic safety boundary generation module is used to construct a virtual clamp for the urological surgical area based on preoperative medical images, and dynamically adjust the safety boundary of the virtual clamp based on the real-time pressure information and the preset tissue deformation model. The central decision-making and control module, which is communicatively connected to the multimodal perception module and the dynamic safety boundary generation module, is used to calculate the target motion correction of the robotic arm based on the interactive force information and the safety boundary through an admittance-impedance composite control algorithm. The human-machine collaborative feedback module is used to provide real-time feedback on the collision status and risk information identified by the system to the surgical operator.

[0010] Preferably, the admittance-impedance composite control algorithm in the central decision-making and control module includes: During the admittance control phase, admittance control adjusts the desired motion through external contact force, and its dynamic relationship satisfies:

[0011] In the formula: , , The preset virtual mass, damping, and stiffness matrices; , , This provides the reference position, velocity, and acceleration of the robotic arm's end effector. , , These are the desired position, velocity, and acceleration calculated using the admittance control law. The external contact force detected by the multimodal sensing module (100); During the impedance control phase, impedance control generates a command force through motion deviation, and its control relationship is as follows:

[0012] In the formula: , , For impedance control, the mass, damping, and stiffness matrices are defined. , , This refers to the actual position, velocity, and acceleration of the robotic arm's end effector. , , The desired position, velocity, and acceleration; The calculated command force.

[0013] Preferably, the dynamic adjustment function of the dynamic security boundary generation module specifically includes: Contraction factor that defines the safety boundary Its relationship with real-time intracavitary pressure The relationship is:

[0014] in, For the safety pressure threshold, The maximum permissible pressure threshold; This is the scaling factor. It is the maximum contractility factor; Adjusted safety boundary From the initial boundary With contractile factor The decision is made jointly, as shown in the formula: .

[0015] Preferably, the tissue deformation model adopts a projection model based on the Lie group SE(3) to predict the deformation of soft tissue after being subjected to force, and its deformation field D(X) is approximately represented as:

[0016] in, Let X be the deformation Jacobian matrix of the organization at position X. The force and torque vectors acting on the organization are represented in the SE(3) Lie algebra space.

[0017] Preferably, the multimodal sensing module includes: Force and torque sensing unit, installed on the wrist of the robotic arm, is used to detect the contact force and torque between the robotic arm and tissues or instruments; The current sensing unit is used to monitor the current value of each joint motor; An intracavitary pressure sensing unit, integrated into a urological surgical instrument, is used to monitor fluid pressure within the kidney or body cavity in real time. An optical positioning unit is used to acquire the pose data of the robotic arm in the global coordinate system in real time.

[0018] Preferably, the human-machine collaborative feedback module includes: The tactile feedback unit is configured to generate tactile resistance or vibration at the main operating end when the robotic arm trajectory approaches the dynamic safety boundary; The visual alarm unit is configured to display the collision risk area and the safety boundary of the robotic arm in augmented reality on the surgical field monitor; The audible and visual warning unit is configured to issue an audible and visual alarm signal when the internal pressure exceeds the limit or a collision occurs.

[0019] Preferably, the tactile resistance generated by the tactile feedback unit Depth of the intrusion boundary Proportional

[0020] in This is the tactile gain coefficient.

[0021] Preferably, the central decision-making and control module further includes a collaborative planning unit, used to coordinate the motion paths and timing of each robotic arm in a multi-robotic arm scenario, so as to avoid motion interference between robotic arms.

[0022] Preferably, the virtual clamp includes a restricted area for marking inaccessible anatomical areas and a guide area for marking recommended instrument movement paths.

[0023] Preferably, the system is specifically applied to robot-assisted urological surgeries, including prostatectomy, partial nephrectomy, or ureteroscopic lithotripsy.

[0024] The technical effects and advantages of this invention are as follows: Multidimensional perception: By integrating force, current, intracavitary pressure and visual information, it achieves a more comprehensive perception of collision status and surgical environment, which is especially suitable for the complex needs of endoscopic urological surgery.

[0025] Intelligent boundary: Breaking through the limitations of static virtual fixtures, the safety boundary can be dynamically adjusted according to tissue deformation and physiological parameters, which significantly improves safety while ensuring the smoothness of the operation.

[0026] Compliant control: By adopting an admittance-impedance composite control strategy, the robotic arm exhibits human-like compliance and adaptability when avoiding collisions, reducing the impact of sudden stops and protecting fragile tissues.

[0027] Human-machine collaboration: Through multi-channel information feedback, the system status is intuitively transmitted to doctors, realizing the deep integration and safe coexistence of human and machine intelligence. Attached Figure Description

[0028] Figure 1 This is a block diagram of the overall architecture of a protective system for real-time feedback of the collision status of a surgical robot arm, provided in an embodiment of this application. Figure 2 This is a control block diagram of the admittance in a protection system for real-time feedback of the collision status of a surgical robot arm, provided in an embodiment of this application. Figure 3This is a control block diagram of impedance in a protection system for real-time feedback of the collision status of a surgical robot arm, provided in an embodiment of this application. Figure 4 This is a schematic diagram of the application environment of a protective system for real-time feedback of the collision status of a surgical robot arm, provided in an embodiment of this application; 100. Multimodal perception module; 200. Dynamic safety boundary generation module; 300. Central decision-making and control module; 400. Human-machine collaborative feedback module. Detailed Implementation

[0029] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments. The embodiments of the present invention are given for illustrative and descriptive purposes only, and are not intended to be exhaustive or to limit the invention to the forms disclosed. Many modifications and variations will be apparent to those skilled in the art. The embodiments were chosen and described to better illustrate the principles and practical application of the invention, and to enable those skilled in the art to understand the invention and design various embodiments with various modifications suitable for a particular purpose.

[0030] Example 1

[0031] Please see Figures 1-4 This embodiment provides a protection system for real-time feedback of the collision status of a surgical robot arm, comprising four main modules: a multimodal perception module 100, a dynamic safety boundary generation module 200, a central decision-making and control module 300, and a human-machine collaborative feedback module 400.

[0032] The multimodal sensing module 100 is used to collect the pose information of the robotic arm, the interaction force information between the robotic arm and tissues or instruments, and the real-time pressure information in the urinary system cavity in real time. This module includes a force and torque sensing unit, a current sensing unit, an intracavity pressure sensing unit, and an optical positioning unit; The force and torque sensing unit is installed on the wrist of the robotic arm and uses a miniature six-dimensional force and torque sensor to detect the contact force and torque between the robotic arm and tissues or instruments in real time. The current sensing unit monitors the current value of each joint motor in real time and uses sudden changes in current to help determine collision events; The intracavitary pressure sensing unit is integrated into terminal instruments such as ureteral sheaths or nephroscopes, and uses hydraulic sensing technology to monitor intrarenal or intracavitary pressure at least 6 times per second. The optical positioning unit acquires the pose of the robotic arm in the global coordinate system in real time through the optical tracking system.

[0033] The dynamic safety boundary generation module 200 is used to construct a virtual clamp for the urological surgical area based on preoperative medical images, and dynamically adjust the safety boundary of the virtual clamp based on the real-time pressure information and the preset tissue deformation model. This module includes a virtual fixture building unit and a boundary adaptive unit; The virtual fixture construction unit is based on the preoperative CT / MRI images to reconstruct a 3D model of the urinary system, such as the kidneys, ureters, and prostate. On this model, prohibited areas and guiding areas are defined. Prohibited areas include areas with dense blood vessels and nerves, while guiding areas include surgical channels. The boundary adaptive unit dynamically adjusts the geometry and threshold of the safety boundary based on real-time intracavitary pressure data and tissue deformation prediction model; Boundary adaptive unit according to formula

[0034] and Dynamically adjust safety boundaries; For example, setting =20mmHg, =40mmHg, =0.1, ; When the pressure increases from 20 mmHg to 30 mmHg, the boundary will shrink to 80% of its original size, thus forcing the robotic arm to reduce its range of motion. To further improve accuracy, the module integrates a deformation prediction model based on the Lie group SE(3), as shown in the formula. As shown, the force is transferred through the Lie group SE(3). Mapped to tissue deformation D(X); This allows the system to predict the deformation that may occur when the robotic arm contacts or compresses tissue, and to make "pre-compensation" fine-tuning of the safety boundaries accordingly.

[0035] The central decision-making and control module 300 is communicatively connected to the multimodal sensing module 100 and the dynamic safety boundary generation module 200. It is used to calculate the target motion correction of the robotic arm based on the interactive force information and the safety boundary through an admittance-impedance composite control algorithm. This module includes a collision risk assessment unit, an admittance-impedance composite control unit, and a collaborative planning unit; The collision risk assessment unit integrates multimodal perception data and uses a time automata model to detect online whether the robotic arm trajectory violates current safety constraints; once a potential collision or pressure exceeding the limit is detected, an early warning is immediately triggered.

[0036] The implementation flow of the admittance-impedance composite control unit is shown in the figure: In the non-contact phase, admittance control is employed, and its equation of motion is derived from... definition; The system is based on virtual dynamic parameters , , The detected minute contact force or virtual repulsive force "Converted" into a smooth position and velocity correction amount ( ); This correction will be added to the original instruction. This allows the robotic arm to automatically avoid prohibited areas; During the contact phase, impedance control is employed, and its control law is as follows: definition; By setting a smaller The robotic arm is subjected to force At that time, a certain positional deviation is allowed. This allows it to exhibit "soft" and "compliant" characteristics, avoiding damage to fragile tissues from rigid impacts.

[0037] In multi-robotic arm scenarios, the collaborative planning unit coordinates the movements of each arm through the central processing module to ensure spatiotemporal synchronization and avoid interference between arms.

[0038] The human-machine collaborative feedback module 400 is used to provide real-time feedback of the collision status and risk information identified by the system to the surgical operator. This module includes a tactile feedback unit, a visual alarm unit, and an audible and visual warning unit; The haptic feedback unit is configured to generate haptic resistance at the main operating end when the robotic arm trajectory approaches a dynamic safety boundary, the magnitude of which is determined by... Calculation, where This is the tactile gain coefficient. The depth of the intrusion boundary; The visual alarm unit is configured to highlight the collision risk area, the real-time position of the robotic arm, and its relative relationship to the dynamic safety boundary in augmented reality on the surgical field monitor.

[0039] The audible and visual warning unit is configured to issue an audible and visual alarm when the intracavitary pressure exceeds the limit or a collision occurs, and can automatically suspend infusion or suction according to a preset strategy.

[0040] The virtual clamp includes a restricted area for marking inaccessible anatomical regions and a guide area for marking recommended instrument movement paths.

[0041] The system is specifically used in robot-assisted urological surgeries, including prostatectomy, partial nephrectomy, or ureteroscopic lithotripsy.

[0042] When using this solution: Taking robot-assisted ureteroscopic lithotripsy as an example, the implementation process of this system is as follows: Before surgery, the patient's abdominal CT images are imported to reconstruct a three-dimensional model of the renal pelvis and ureter. The doctor marks prohibited and guiding areas on the model to generate an initial virtual clamp. .

[0043] During the procedure, the robotic arm carries the flexible ureteroscope into the body. The pressure sensing unit integrated at the front end of the ureteroscopic manometry guide sheath begins to work, monitoring the intrarenal pressure in real time. At the same time, the six-dimensional force sensor at the wrist of the robotic arm and the current sensor at the joint continuously collect interactive force and load data.

[0044] The dynamic safety boundary generation module fine-tunes the boundaries of the virtual fixture based on real-time pressure data and a soft tissue deformation model. For example, when the system detects a sudden increase in pressure approaching the 40 mmHg warning level, it will automatically reduce the allowable operating space at the end of the robotic arm.

[0045] During normal operation, the doctor sends commands to the main control terminal, and the robotic arm moves smoothly along the safe walking path defined by the virtual fixture under admittance control. When the end of the robotic arm approaches the dynamic boundary due to tissue drift or the doctor's operation, the collision risk judgment unit is triggered, and the main control handle generates tactile resistance to alert the doctor.

[0046] If the robotic arm makes slight contact with the tissue, the impedance control unit adjusts the compliance of the robotic arm based on feedback from the force sensor, causing it to slide away along the tissue surface.

[0047] If the system detects that multiple robotic arms pose a risk of interference, the collaborative planning unit will replan the paths of each arm to ensure synchronized movements. All warning information is displayed in real time on the screen of the doctor's console.

[0048] Through the aforementioned hardware and software collaborative design, this invention provides a real-time safety protection solution for urological surgical robots, covering the entire process from perception and decision-making to execution, effectively reducing intraoperative risks and alleviating the cognitive load on doctors.

[0049] In this solution, unless otherwise explicitly specified and limited, the terms "installation", "setting", "connection", "fixing", "screw connection", etc., should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; they can refer to the internal connection of two components or the interaction between two components. Unless otherwise explicitly limited, those skilled in the art can understand the specific meaning of the above terms in this solution according to the specific circumstances.

[0050] In the description of this invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0051] Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art and related fields based on the embodiments of the present invention without inventive effort should fall within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described and explained in the present invention, unless otherwise specified or limited, shall be implemented according to conventional means in the art.

Claims

1. A safeguard system for real-time feedback of a collision state of a surgical robotic arm, characterized in that, The system comprises: a multi-modal perception module (100) configured to collect in real time pose information of a robot arm, interaction force information between the robot arm and a tissue or an instrument, and real-time pressure information in a urinary system cavity; a dynamic safety boundary generation module (200) configured to construct a virtual clamp of a urinary surgery area based on preoperative medical images, and dynamically adjust a safety boundary of the virtual clamp based on the real-time pressure information and a preset tissue deformation model; a central decision and control module (300) communicatively connected to the multi-modal perception module (100) and the dynamic safety boundary generation module (200), and configured to calculate a target motion correction amount of the robot arm based on the interaction force information and the safety boundary by using a hybrid admittance-impedance control algorithm; a human-machine collaborative feedback module (400) configured to feed back collision states and risk information recognized by the system to a surgical operator in real time.

2. The protection system of real-time feedback collision status of surgical robot manipulator according to claim 1, characterized in that, The hybrid admittance-impedance control algorithm in the central decision and control module (300) comprises: an admittance control stage, which adjusts a desired motion through an external contact force, and a dynamic relationship thereof satisfies: In the formula: , , are preset virtual mass, damping and stiffness matrices; , , Reference position, velocity, acceleration of the end of the robot arm; , , are the desired position, velocity and acceleration calculated by the admittance control law; an external contact force detected by the multi-modal perception module (100); an impedance control stage, which generates an instruction force through a motion deviation, and a control relationship thereof is: In the formula: , , Mm, Mm, Mm, Mm, Mm, Mm, Mm, Mm, Mm, Mm, Mm, Mm, Mm, Mm, Mm, Mm, Mm, , , are the actual position, velocity and acceleration of the end of the robot arm; , , desired position, velocity, and acceleration; The calculated command force.

3. The safety system for a real-time feedback of a collision state of a surgical robot manipulator according to claim 2, characterized in that, The dynamic adjustment function of the dynamic safety boundary generation module (200) is specifically: Contraction factor defining a safety margin which is related to the real-time intracavity pressure as follows: wherein, is a safety pressure threshold, is a maximum allowed pressure threshold; for the scaling coefficients, is the maximum shrinkage factor; adjusted security boundary from the initial boundary with the shrinkage factor are jointly determined, as shown in the formula: 。 4. The system of claim 1, wherein the system further comprises a force sensor coupled to the robotic arm. The tissue deformation model adopts a projection model based on Lie group SE3, which is used to predict the deformation of soft tissue after being subjected to force, and a deformation field D(X) thereof is approximately expressed as: wherein, is the deformation Jacobian matrix of the tissue at position X, is the representation of the force and moment vectors acting on the tissue in the SE3 Lie algebra space.

5. The safety system for a real-time feedback of a collision state of a surgical robot manipulator according to claim 1, wherein, The multi-modal perception module (100) comprises: a force and torque sensing unit installed on a wrist of the robot arm, and configured to detect a contact force and torque between the robot arm and the tissue or the instrument; a current sensing unit configured to monitor current values of motors of joints; an intracavity pressure sensing unit integrated on a urinary surgery end instrument, and configured to monitor fluid pressure in a kidney or a body cavity in real time; an optical positioning unit configured to acquire in real time pose data of the robot arm in a global coordinate system.

6. The safety system for a real-time feedback of a collision state of a surgical robot manipulator according to claim 1, wherein, The human-machine collaborative feedback module (400) comprises: a tactile feedback unit configured to generate tactile resistance or vibration at a main operation end when a trajectory of the robot arm approaches the dynamic safety boundary; a visual alarm unit configured to display a collision risk area and a safety boundary of the robot arm in the form of augmented reality on a surgical field monitor; an audible and light warning unit configured to emit an audible and light alarm signal when the intracavity pressure is out of limit or a collision occurs.

7. The safety system of real-time feedback of collision status of surgical robot manipulator according to claim 6, characterized in that, The haptic feedback unit generates a haptic resistance is proportional to the depth of the intrusion boundary is proportional, wherein is a haptic gain coefficient.

8. The safety system for a real-time feedback of a collision state of a surgical robot manipulator according to claim 1, wherein, The central decision and control module (300) further comprises a collaborative planning unit configured to coordinate motion paths and time sequences of robot arms in a multi-robot arm scenario, so as to avoid motion interference between the robot arms.

9. The safety system for a real-time feedback of a collision state of a surgical robot manipulator according to claim 1, wherein, The virtual clamp comprises a forbidden area for identifying an inaccessible anatomical region and a guide area for identifying a recommended instrument movement path.

10. The safety system for a real-time feedback of a collision state of a surgical robot manipulator according to claim 1, wherein, The system is specifically applied to robot-assisted urinary surgery, including prostatectomy, partial nephrectomy or ureteroscopy lithotripsy.

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