Photoelectric fusion positioning error compensation method and system for surgical robot

Abstract

The invention belongs to the technical field of medical robots, and discloses a photoelectric fusion positioning error compensation method and system for a surgical robot. The system is composed of an optical positioning acquisition module, an electromagnetic interference detection and auxiliary positioning module, a photoelectric dynamic fusion and weight adaptive adjustment module, a real-time error dynamic modeling and feedback module and a motion compensation control and path adjustment module. The optical positioning acquisition module adopts the design of a multi-angle camera and three-dimensional distributed infrared identification points, and captures the pose information of the actuator in all directions; the electromagnetic interference detection and auxiliary positioning module monitors environmental interference in real time and calibrates electromagnetic positioning data by establishing an interference model; the photoelectric dynamic fusion and weight adaptive adjustment module effectively fuses two types of data by using extended Kalman filtering and a dynamic weight algorithm, can eliminate adverse factors such as a visual angle blind area and environmental interference in all directions, accurately obtains the pose of an actuator, and remarkably improves the accuracy and reliability of operation positioning.

Description

Technical Field

[0001] The present invention belongs to the technical field of medical robots, and specifically relates to a method and system for compensating for optoelectronic fusion positioning errors of surgical robots. Background Art

[0002] In the current clinical application of surgical robots, positioning accuracy is an important basis for ensuring the safety and effectiveness of surgery. However, the existing surgical robot positioning technology still has many technical bottlenecks, which seriously restricts its application effect and development prospects. First, at the data acquisition level, the existing optical positioning technology generally relies on monocular cameras or single-direction image acquisition methods, which have limited acquisition viewing angles and are difficult to achieve multi-angle and all-round accurate capture of surgical robot actuators in three-dimensional space. It is easy to produce blind spots in viewing angles, resulting in deviations in posture information.

[0003] Secondly, although electromagnetic positioning technology has strong real-time tracking capabilities, it is easily affected by metal instruments and complex electromagnetic interference signals in actual surgical environments. The interference signals are not effectively identified and calibrated, resulting in significant errors in the electromagnetic positioning data, reducing the accuracy and stability of positioning; in addition, in the data processing and error correction links, existing technologies mostly use fixed-parameter data fusion algorithms, which cannot dynamically adapt to real-time changes in the surgical environment, and it is difficult to adjust data weights based on the intensity of environmental interference and the motion status of the equipment, resulting in a lack of robustness and reliability in the fusion results.

[0004] At the same time, traditional error modeling mostly only compensates for static posture deviations, ignoring dynamic influencing factors such as movement speed and changes in the electromagnetic environment. It cannot fully reflect the actual error state, causing the compensation model to deviate from the actual operating conditions. Existing path correction methods mostly use open-loop control structures and lack real-time closed-loop feedback. They cannot continuously correct the motion path during surgery, resulting in continuous accumulation of errors, which seriously affects the motion accuracy and operational safety of the surgical robot. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and system for compensating for optoelectronic fusion positioning errors of a surgical robot to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above-mentioned objectives, the present invention provides the following technical solutions: a surgical robot optoelectronic fusion positioning error compensation system, which is composed of an optical positioning acquisition module, an electromagnetic interference detection and auxiliary positioning module, an optoelectronic dynamic fusion and weight adaptive adjustment module, a real-time error dynamic modeling and feedback module, and a motion compensation control and path adjustment module; Optical positioning acquisition module: This module uses multi-angle cameras to collect real-time images of the three-dimensional infrared marker points on the surgical robot actuator, outputting raw optical pose data and providing basic information for subsequent modules. Its multi-angle acquisition is the beginning of achieving precise positioning. Electromagnetic Interference Detection and Auxiliary Positioning Module: This module receives data from the optical module, uses a highly sensitive sensor array to detect environmental interference, and calibrates electromagnetic positioning data through modeling to eliminate interference effects, ensure the reliability of positioning data, and lay a solid foundation for data fusion. Photoelectric dynamic fusion and weight adaptive adjustment module: Based on the data from the first two modules, it uses extended Kalman filtering and adaptive algorithms for dynamic fusion, changes weights according to the environment, and outputs high-confidence poses. This is the key step in converting raw data into reliable pose data. Real-time error dynamic modeling and feedback module: Receives fused pose, integrates speed, environment and other factors to build a dynamic model, outputs error feedback parameters, accurately analyzes errors, provides a basis for path correction, and achieves precise control of error compensation; Motion compensation control and path adjustment module: Based on the error parameters, the motion path correction control formula is used, and the closed-loop transmission is returned to the execution system to adjust the path in real time to form a complete compensation control closed loop, ensuring the precise movement of the surgical robot and serving as the ultimate execution guarantee for error compensation.

[0007] Preferably, the optical positioning acquisition module includes: (1) Multi-angle optical image acquisition architecture: The optical positioning acquisition module achieves precise acquisition through innovative design. On the surgical robot actuator, the characteristic infrared marker points are distributed in three dimensions to ensure that they can be captured from different viewing angles. The camera array adopts a multi-angle arrangement, covering multiple horizontal and vertical angles, forming a full-range visual acquisition area. Multiple cameras work together to capture images of infrared marker points from different viewing angles. Compared with monocular or one-way acquisition, it can obtain richer image information, laying a solid foundation for subsequent positioning; (2) Optical data processing and pose calculation: The collected image information needs to be professionally processed to obtain pose data. Using image processing algorithms, the position information of the marker points in the image can be accurately extracted. Combined with the camera calibration parameters, the three-dimensional space pose calculation formula is used to back-project the optical image coordinates into three-dimensional space, thereby obtaining the preliminary position of the robot actuator in space. This formula serves as a basic conversion tool for the optical system, establishing a connection between the image information and the actual spatial position, and ultimately outputting the original optical data of the target pose, significantly improving the accuracy and reliability of positioning.

[0008] Three-dimensional space pose calculation formula:

[0009] Where: is the target spatial pose coordinates measured optically (unit: mm); is the camera internal parameter matrix (including focal length, optical center and other parameters); The pixel coordinate matrix of the infrared marker points in the image plane.

[0010] Preferably, the electromagnetic interference detection and auxiliary positioning module includes: (1) Electromagnetic interference monitoring and data acquisition architecture: The electromagnetic interference detection and auxiliary positioning module is closely connected to the optical positioning acquisition module. While receiving the original optical data, it also takes on the important task of monitoring the surgical environment. The module is equipped with a high-sensitivity electromagnetic sensor array that can capture parameters such as electromagnetic signal strength and frequency in the environment in real time, and conduct detection and analysis of the position and characteristics of metal equipment, accurately identifying the interference source, and providing a detailed data basis for subsequent processing, creating a new paradigm that combines real-time electromagnetic interference monitoring with auxiliary positioning; (2) Electromagnetic positioning data calibration and output: Based on the collected data, this module uses an electromagnetic interference model to separate useful electromagnetic positioning signals from interference signals. Using the electromagnetic positioning spatial transformation formula, the electromagnetic sensor data is converted to a spatial coordinate system consistent with the optical system through coordinate transformation, ensuring spatial consistency between the two data types. Combined with the original optical data, the electromagnetic positioning data is deeply calibrated and corrected, ultimately outputting high-precision electromagnetic-assisted positioning data, effectively eliminating the effects of environmental interference and significantly improving the accuracy and stability of electromagnetic positioning.

[0011] Electromagnetic positioning space transformation formula:

[0012] Where: The spatial pose coordinates calculated by the electromagnetic eye tracking system (unit: mm); Transformation matrix from electromagnetic beacon to global coordinate system; Relative pose data measured by electromagnetic sensors.

[0013] Preferably, the optoelectronic dynamic fusion and weight adaptive adjustment module includes: (1) Data fusion architecture based on extended Kalman filtering: The optoelectronic dynamic fusion and weight adaptive adjustment module is connected to the electromagnetic interference detection and auxiliary positioning module, with optical positioning and electromagnetic positioning data as input. With the help of the extended Kalman filter, a filtering algorithm suitable for nonlinear systems, the two types of data are dynamically fused. It can effectively handle the uncertainty in the data and integrate the optical and electromagnetic positioning information through prediction and update steps, laying the foundation for obtaining accurate posture data and building the core framework of data fusion; (2) Dynamic weight adjustment and high-confidence pose output: In the data fusion process, the environmental interference adaptive weight adjustment algorithm plays a key role. Based on changes in the surgical environment, such as the strength of electromagnetic interference and the optical acquisition status, the extended Kalman filter fusion formula (including dynamic weights) is used to dynamically adjust the weights of optical and electromagnetic data in real time. When electromagnetic interference increases, the formula reduces the weight of electromagnetic data; when optical acquisition is limited, the weight of optical data is reduced. By continuously monitoring environmental parameters and positioning accuracy, data adaptive fusion is achieved, and a high-confidence fusion pose that accurately reflects the actual position of the actuator is output.

[0014] Extended Kalman filter fusion formula (including dynamic weights): Status prediction:

[0015] Status Update:

[0016] Dynamic weight adjustment:

[0017] Where: is the predicted state quantity (unit: mm); is the control input at the previous moment; is the comprehensive Kalman gain at the current moment; is the observed value at the current moment; is the observation model function; is the optical data weight coefficient; is the electromagnetic data weight coefficient; 、 is the sub-Kalman gain for optics and electromagnetics.

[0018] Preferably, the real-time error dynamic modeling and feedback module includes: (1) Multi-source data integration and error influencing factor analysis: The real-time error dynamic modeling and feedback module is connected to the optoelectronic dynamic fusion module to receive high-precision fusion posture data. During the operation of the surgical robot, its movement speed, posture state and complex surgical environment will have a significant impact on the positioning error. This module uses high-precision sensors to collect actuator movement speed information in real time, combined with electromagnetic interference detection and electromagnetic environment data obtained by the auxiliary positioning module, to comprehensively integrate multi-source information, deeply analyze the mechanism of various factors affecting positioning errors, and provide rich and accurate data support for subsequent error modeling; (2) Dynamic error modeling and feedback parameter output: Based on the integrated multi-source data, the module uses the speed-posture-environment joint feedback mechanism to build an innovative dynamic error compensation system. The core speed-posture-environment coupled error dynamic equation innovatively couples the speed error and electromagnetic interference factor into the error dynamic feedback, abandoning the traditional static compensation mode. Through this equation, combined with fusion posture and other data, the error is dynamically calculated and the real-time feedback parameters of the motion error are accurately output. This parameter provides a reliable basis for subsequent motion compensation control and path adjustment, achieving dynamic and accurate compensation of the surgical robot's motion error.

[0019] Velocity-pose-environment coupling error dynamic equation:

[0020]

[0021] is the current positioning error (unit: mm); Fusion target pose (unit: mm); Expected speed (unit: mm / s); Actual speed (unit: mm / s); Real-time detection value of electromagnetic interference field strength; is the speed error weight coefficient; Environmental interference error weight coefficient.

[0022] Preferably, the motion compensation control and path adjustment module includes: (1) Error feedback driven path correction architecture: The motion compensation control and path adjustment module is closely connected with the error dynamic modeling and feedback module, and receives the motion error feedback parameters as the basis for path correction. This module uses the motion path correction control formula to automatically correct the robot's control path based on the error feedback information. By adjusting the parameters such as the motion angle and speed of each joint of the robot, the robot can move according to the corrected path, realizing the initial control from error feedback to path correction, laying the foundation for subsequent closed-loop optimization; (2) Dynamic closed-loop control and precise motion output: After completing the initial path correction, the motion compensation control and path adjustment module transmits the correction instructions back to the surgical robot execution system in a closed loop, while monitoring the actual motion of the robot in real time. The motion path correction control formula is used again to incorporate the deviation between the actual motion and the corrected path into the calculation. The motion control path is dynamically corrected through error feedback, and precise correction instructions are output again to form a full-process closed-loop control. This formula is continuously iterated and optimized to ensure that the robot can adjust the path in time according to the real-time error during the surgical operation, effectively compensate for the motion error, significantly improve the motion control precision and accuracy of the surgical robot, and ensure the smooth progress of the surgical operation.

[0023] Motion path correction control formula:

[0024] Where: is the control input (motion command) after motion compensation; Original motion control instructions; Path gain adjustment matrix; It is the motion error (unit: mm) output by the error dynamic modeling module.

[0025] The present invention also provides a method for compensating for the positioning error of a surgical robot using optoelectronic fusion. The method employs the above-mentioned optoelectronic fusion positioning error compensation system for a surgical robot. The specific steps of the method are as follows: S1. Real-time multi-source data acquisition: The optical positioning acquisition module collects the surgical robot actuator's optical posture data in real time, and the electromagnetic interference detection and auxiliary positioning module collects environmental electromagnetic interference data in real time to ensure data reliability and lay a solid foundation for subsequent processing; S2. Photoelectric Fusion and Error Modeling: Based on the data collected in the previous step, the photoelectric dynamic fusion module dynamically fuses the data to generate a high-confidence pose. The error modeling module then constructs a coupling model and outputs error feedback parameters to provide a basis for path correction. S3. Motion compensation path correction: Based on the error feedback parameters, the motion compensation module corrects the robot path in real time and transmits the closed-loop instruction back to the execution system. By comparing the actual and corrected paths, continuous adjustments are made to achieve precise motion control and ensure the accuracy of surgical operations.

[0026] Preferably, the specific steps of real-time multi-source data collection in step S1 are as follows: S11. Dual-module collaborative data acquisition mechanism: The optical positioning acquisition module and the electromagnetic interference detection module work together to achieve real-time multi-source data acquisition. The optical module uses a multi-angle camera to capture images of the three-dimensionally distributed characteristic infrared marking points on the surgical robot actuator at a preset frequency. After image processing and calculation, it outputs raw optical data. The electromagnetic module uses a high-sensitivity sensor array to monitor metal equipment and electromagnetic signals in the surgical environment in real time. After interference model analysis and processing, it outputs electromagnetic-assisted positioning data. The parallel acquisition of the dual modules provides the basis for subsequent processing; S12. Ensuring Data Acquisition Reliability: This synchronized acquisition method combines real-time electromagnetic interference detection with assisted positioning for the first time. Optical data provides actuator position information, while electromagnetic data takes into account environmental interference. The two complement each other to ensure the dynamic reliability of the data source. This provides a reliable data foundation for subsequent optoelectronic fusion, error modeling, and motion compensation, improving the overall reliability of surgical robot positioning and control from the source.

[0027] Preferably, the specific steps of photoelectric fusion and error modeling in step S2 are as follows: S21. Dynamic fusion processing of optoelectronic data: The optical data and electromagnetic data obtained from real-time multi-source data collection are input into the optoelectronic dynamic fusion and weight adaptive adjustment module. With the help of the extended Kalman filter algorithm, the two types of data are deeply fused. It is suitable for nonlinear systems and can effectively handle the uncertainty in the data. At the same time, the environmental interference adaptive weight adjustment algorithm comes into play. According to the changes in the surgical environment, such as the intensity of electromagnetic interference and the optical acquisition status, the weights of the optical and electromagnetic data in the fusion are dynamically adjusted in real time, thereby generating a high-confidence fusion posture in real time, providing an accurate data foundation for subsequent error modeling; S22. Dynamic Error Modeling and Parameter Output: The high-confidence fusion posture obtained by optoelectronic dynamic fusion is transmitted to the error dynamic modeling and feedback module. Based on a combined velocity-posture-environment feedback mechanism, this module introduces velocity feedback and electromagnetic environment factors to construct a mathematical model for dynamic error compensation. Combining real-time motion velocity information and electromagnetic environment information, the module comprehensively considers the impact of multiple factors on the error and outputs motion error feedback parameters through mathematical calculation and analysis. This dual closed-loop structure of environmentally adaptive weight adjustment and dynamic error modeling significantly improves the adaptability and accuracy of error compensation in complex surgical environments.

[0028] Preferably, the specific steps of correcting the motion compensation path in step S3 are as follows: S31. Error-driven real-time path correction: The motion compensation path correction link is driven by the motion error feedback parameters output in step 2. The motion compensation control and path adjustment module is equipped with an advanced path planning algorithm. After receiving the error parameters, it immediately corrects the robot control path in real time. By precisely adjusting the motion angle and speed parameters of each joint of the robot, it generates control instructions that meet the correction requirements and transmits them to the surgical robot execution system, driving the robot to move along the new path to complete the initial error compensation. S32. Closed-loop feedback optimized motion control: When the robot executes the corrected path motion, the motion compensation control and path adjustment module continuously monitors its actual motion trajectory in real time. By frequently comparing the actual motion with the corrected target path, the deviation data between the two is captured. Based on the motion path correction control logic, the path planning is adjusted again and the control instructions are updated, forming a full-process closed-loop compensation mechanism of "monitoring-comparison-correction-feedback". Compared with traditional offline correction methods, this closed-loop control can dynamically respond to error changes, significantly improving the surgical robot's motion control accuracy and surgical operation reliability.

[0029] The beneficial effects of the present invention are as follows: 1. The present invention greatly improves the positioning accuracy of surgical robots through multi-module collaborative innovation. The optical positioning acquisition module breaks through the limitations of traditional monocular or unidirectional acquisition, and adopts a multi-angle camera and a three-dimensional distributed infrared identification point design to capture the actuator posture information in all directions; the electromagnetic interference detection and auxiliary positioning module monitors environmental interference in real time and calibrates the electromagnetic positioning data by establishing an interference model; the optoelectronic dynamic fusion and weight adaptive adjustment module uses extended Kalman filtering and dynamic weight algorithm to effectively fuse the two types of data, which can eliminate adverse factors such as blind spots and environmental interference in all directions, accurately obtain the actuator posture, and significantly improve the accuracy and reliability of surgical positioning.

[0030] 2. This invention establishes a dual environmental adaptation mechanism. The electromagnetic interference detection and auxiliary positioning module uses a highly sensitive sensor array to monitor metal equipment and electromagnetic signals in the surgical environment in real time, separates useful signals through an interference model, and reduces the impact of environmental interference on electromagnetic positioning. The optoelectronic dynamic fusion and weight adaptive adjustment module can adjust the weights of optical and electromagnetic data in real time according to environmental changes to ensure the accuracy of the fused posture. It can operate stably in complex electromagnetic environments and when optical acquisition is obstructed, greatly enhancing the surgical robot's environmental adaptability in different surgical scenarios.

[0031] 3. The present invention achieves a leap in the accuracy of surgical robot motion control through dynamic error modeling and closed-loop control system. The real-time error dynamic modeling and feedback module integrates multiple factors such as speed, posture and environment to construct a dynamic error compensation model and accurately calculate the motion error feedback parameters. After receiving the parameters, the motion compensation control and path adjustment module uses advanced path planning algorithms to correct the path in real time, and transmits the command closed-loop back to the execution system, forming a "monitoring-feedback-correction" dynamic closed-loop control, which can respond to motion errors in real time, continuously optimize the robot's motion path, greatly improve the surgical robot's motion control accuracy, and effectively reduce the risk of surgical operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a flow chart of the optoelectronic fusion positioning error compensation system of the surgical robot of the present invention; Figure 2 This is a flow chart of the optoelectronic fusion positioning error compensation method for surgical robots of the present invention. DETAILED DESCRIPTION

[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0034] like Figures 1 to 2 As shown, an embodiment of the present invention provides a surgical robot optoelectronic fusion positioning error compensation system, which is composed of an optical positioning acquisition module, an electromagnetic interference detection and auxiliary positioning module, an optoelectronic dynamic fusion and weight adaptive adjustment module, a real-time error dynamic modeling and feedback module, and a motion compensation control and path adjustment module; Optical positioning acquisition module: This module collects infrared marker images through multi-angle cameras, combines them with a specific spatial distribution design, and outputs raw optical data, providing basic information for subsequent modules. Its multi-angle acquisition is the beginning of achieving precise positioning. Electromagnetic Interference Detection and Auxiliary Positioning Module: This module receives data from the optical module, uses a highly sensitive sensor array to detect environmental interference, and calibrates electromagnetic positioning data through modeling to eliminate interference effects, ensure the reliability of positioning data, and lay a solid foundation for data fusion. Photoelectric dynamic fusion and weight adaptive adjustment module: Based on the data from the first two modules, it uses extended Kalman filtering and adaptive algorithms for dynamic fusion, changes weights according to the environment, and outputs high-confidence poses. This is the key step in converting raw data into reliable pose data. Real-time error dynamic modeling and feedback module: Receives fused pose, integrates speed, environment and other factors to build a dynamic model, outputs error feedback parameters, accurately analyzes errors, provides a basis for path correction, and achieves precise control of error compensation; Motion compensation control and path adjustment module: Based on the error parameters, the motion path correction control formula is used, and the closed-loop transmission is returned to the execution system to adjust the path in real time to form a complete compensation control closed loop, ensuring the precise movement of the surgical robot and serving as the ultimate execution guarantee for error compensation.

[0035] The present invention significantly improves the performance of surgical robots through multi-module collaboration and dual mechanism innovation. In terms of positioning accuracy, the optical positioning acquisition module uses multi-angle cameras and three-dimensional infrared marking points to break through the limitations of traditional acquisition and fully capture the actuator posture; the electromagnetic interference detection and auxiliary positioning module monitors environmental interference in real time and calibrates electromagnetic positioning data; the optoelectronic dynamic fusion and weight adaptive adjustment module uses extended Kalman filtering and dynamic weighting algorithms to effectively fuse data, eliminate perspective and environmental interference, and accurately locate. In terms of environmental adaptability, the electromagnetic interference detection and auxiliary positioning module relies on a high-sensitivity sensor array and interference model to reduce the impact of the environment on electromagnetic positioning; the optoelectronic dynamic fusion module adjusts data weights in real time according to environmental changes to ensure the accuracy of the fusion posture, so that the surgical robot can operate stably in complex electromagnetic and optical obstruction scenarios, broadening its application range.

[0036] Among them, the optical positioning acquisition module adopts a multi-angle optical image acquisition mode in its acquisition architecture, sets characteristic infrared identification points with a three-dimensional distribution on the surgical robot actuator, and cooperates with the multi-angle arranged camera array to construct a full-range visual acquisition area from different horizontal and vertical angles. The collaborative operation of multiple cameras greatly improves the richness of image information acquisition, which is more advantageous than traditional monocular or one-way acquisition.

[0037] Image processing algorithms are used to accurately extract the position information of the identification points in the image. Combined with the camera calibration parameters, the optical image coordinates are back-projected into three-dimensional space with the help of three-dimensional spatial posture calculation formulas, realizing effective association between image information and actual spatial position, and then outputting high-precision target posture original optical data, significantly enhancing the accuracy and reliability of positioning, and providing a solid data foundation for subsequent data fusion and error compensation.

[0038] Among them, the electromagnetic interference detection and auxiliary positioning module is deeply connected with the optical positioning acquisition module on the electromagnetic interference monitoring and data acquisition architecture. While receiving the original optical data, it uses a high-sensitivity electromagnetic sensor array to monitor the electromagnetic signal intensity, frequency and other parameters in the surgical environment in real time, and analyze the position and characteristics of metal equipment to accurately identify the interference source and provide rich and accurate data for subsequent processing.

[0039] During the electromagnetic positioning data calibration and output phase, the module applies an electromagnetic interference model to process the collected data, separating useful electromagnetic positioning signals from interference signals. Using the electromagnetic positioning spatial transformation formula, the electromagnetic sensor data is transformed into a spatial coordinate system consistent with the optical system, ensuring spatial consistency between the two types of data. Combined with the original optical data, the electromagnetic positioning data is deeply calibrated and corrected, ultimately outputting high-precision electromagnetic-assisted positioning data. This effectively eliminates the effects of environmental interference on electromagnetic positioning and significantly improves its accuracy and stability.

[0040] The optoelectronic dynamic fusion and adaptive weight adjustment module is deeply connected to the electromagnetic interference detection and auxiliary positioning module. Using optical and electromagnetic positioning data as input, the extended Kalman filter algorithm forms the core data fusion framework. This algorithm addresses the nonlinear characteristics of surgical scenarios and, through iterative prediction and update steps, effectively eliminates data uncertainty and completes the initial integration of optical and electromagnetic positioning information.

[0041] On this basis, an adaptive environmental interference weight adjustment algorithm, based on the dynamic changes in the surgical environment, utilizes an extended Kalman filter fusion formula (including dynamic weighting) to sense parameters such as electromagnetic interference intensity and optical acquisition stability in real time. When the number of electromagnetic devices in the operating room increases dramatically, the system automatically reduces the weight of electromagnetic data; when encountering optical occlusion, it dynamically increases the confidence of optical data. Through the synergistic operation of this dual mechanism, the module continuously optimizes the data fusion strategy, ultimately outputting a high-confidence fusion result that closely matches the actual actuator position, providing accurate data support for subsequent error compensation.

[0042] The real-time error dynamic modeling and feedback module achieves high-precision error analysis and parameter output through an innovative two-stage architecture. For multi-source data integration and error influencing factor analysis, this module is deeply integrated with the optoelectronic dynamic fusion module, receiving high-confidence fused posture data. It also relies on high-precision sensors to collect actuator motion speed information in real time, and simultaneously integrates electromagnetic environment data obtained by the electromagnetic interference detection and auxiliary positioning module. Through a systematic analysis of multi-dimensional factors such as motion speed, posture state, and surgical environment, the mechanism of their influence on positioning error is deeply explored.

[0043] In the dynamic error modeling and feedback parameter output stages, the module utilizes a velocity-pose-environment joint feedback mechanism, employing the core velocity-pose-environment coupled error dynamic equation to innovatively integrate velocity error and electromagnetic interference factors into the error dynamic feedback system. This equation dynamically calculates and outputs real-time motion error feedback parameters, providing a reliable basis for subsequent motion compensation control and path adjustment. This enables dynamic and precise compensation of surgical robot motion errors, significantly improving the timeliness and accuracy of error compensation.

[0044] The Motion Compensation Control and Path Adjustment module achieves precise control of the motion path through an innovative two-tiered architecture. Deeply interconnected with the Error Dynamic Modeling and Feedback module, this module uses the received motion error feedback parameters as the core driver for path correction. Based on the motion path correction control formula, the module automatically corrects the robot's control path. By precisely adjusting key parameters such as the motion angle and speed of each joint, it generates adaptive control instructions and transmits them to the execution system, driving the robot along the corrected path, completing initial error compensation and establishing a foundational framework for subsequent closed-loop optimization.

[0045] Based on the preliminary correction, the module builds a dynamic closed-loop control system, which transmits the correction instructions back to the execution system while continuously monitoring the actual motion trajectory of the robot in real time. Using the motion path correction control formula again, the system incorporates the deviation between the actual motion and the target path into the iterative calculation, and dynamically optimizes the motion control path through the error feedback mechanism. This formula is continuously updated iteratively to achieve real-time optimization and output of control instructions, forming a full-process closed-loop control of "monitoring-feedback-correction-execution". Compared with traditional open-loop correction technology, this dynamic closed-loop architecture can quickly and accurately adjust the robot's motion path based on the errors generated in real time during the surgical process, significantly improving the motion control accuracy of the surgical robot and providing a solid guarantee for the safety and effectiveness of surgical operations.

[0046] The embodiment of the present invention further provides a method for compensating for the optoelectronic fusion positioning error of a surgical robot, which uses the above-mentioned optoelectronic fusion positioning error compensation system of the surgical robot. The specific steps of the method are as follows: S1. Real-time multi-source data acquisition: The optical positioning acquisition module and the electromagnetic interference detection module operate synchronously. The former collects optical data of the actuator's position from multiple angles, while the latter monitors the environment to obtain electromagnetic positioning data, ensuring data reliability and laying a solid foundation for subsequent processing. S2. Photoelectric Fusion and Error Modeling: Based on the data collected in the previous step, the photoelectric dynamic fusion module dynamically fuses the data to generate a high-confidence pose. The error modeling module then constructs a coupling model and outputs error feedback parameters to provide a basis for path correction. S3. Motion compensation path correction: Based on the error feedback parameters, the motion compensation module corrects the robot path in real time and transmits the closed-loop instruction back to the execution system. By comparing the actual and corrected paths, continuous adjustments are made to achieve precise motion control and ensure the accuracy of surgical operations.

[0047] The present invention relies on dynamic error modeling and closed-loop control systems to achieve a breakthrough improvement in the motion control accuracy of surgical robots. The real-time error dynamic modeling and feedback module integrates multiple factors such as speed, posture, and environment to construct a dynamic error compensation model and accurately output motion error feedback parameters. After receiving the parameters, the motion compensation control and path adjustment module uses advanced path planning algorithms to correct the path in real time, and transmits the command closed loop back to the execution system to form a "monitoring-feedback-correction" dynamic closed loop. The system can respond to errors in real time and continuously optimize the path. Compared with traditional technologies, it greatly improves the accuracy of motion control and significantly reduces the risk of surgical operations.

[0048] The real-time multi-source data acquisition in step S1 refers to the collaborative operation of the optical positioning acquisition module and the electromagnetic interference detection module. The optical positioning acquisition module uses cameras arranged at multiple angles to capture images of the three-dimensionally distributed characteristic infrared markers on the surgical robot actuator at a preset frequency. Through image processing algorithms and calculations, it outputs precise raw optical data and obtains actuator pose information. The electromagnetic interference detection module uses a highly sensitive electromagnetic sensor array to monitor the status of metal equipment and electromagnetic signals in the surgical environment in real time. Through electromagnetic interference model analysis and processing, it outputs electromagnetic-assisted positioning data to understand the environmental interference situation.

[0049] This synchronous acquisition method realizes the innovative combination of real-time electromagnetic interference detection and auxiliary positioning. The two types of data complement and verify each other, ensuring the dynamic credibility of the collected data source. It provides solid and reliable data support for subsequent key links such as optoelectronic data fusion, error modeling analysis, and motion compensation control, and improves the overall reliability of surgical robot positioning and control from the source of data acquisition.

[0050] Among them, the optoelectronic fusion and error modeling in step S2 refers to the construction of an environmentally adaptive double-closed-loop structure through the two major links of dynamic fusion processing of optoelectronic data and dynamic error modeling. First, the optical and electromagnetic data obtained by real-time acquisition of multi-source data are input into the optoelectronic dynamic fusion and weight adaptive adjustment module. Using the extended Kalman filter algorithm, the uncertainty in the data is effectively processed according to the nonlinear characteristics of the surgical scene, and the deep fusion of the two types of data is achieved. At the same time, the environmental interference adaptive weight adjustment algorithm dynamically adjusts the weight ratio of optical and electromagnetic data in the fusion in real time according to the changes in the intensity of electromagnetic interference in the surgical environment, whether the optical acquisition is blocked, and other conditions, thereby generating a high-confidence fusion posture, laying a solid and accurate data foundation for subsequent error modeling.

[0051] The high-confidence fused pose is then transmitted to the error dynamic modeling and feedback module. Based on a combined velocity-pose-environment feedback mechanism, this module innovatively incorporates velocity feedback and electromagnetic environmental factors to construct a dynamic error compensation mathematical model. Combining real-time velocity and electromagnetic environmental information, it comprehensively analyzes the impact of multiple factors on the error and outputs motion error feedback parameters through precise mathematical calculations and analysis. This dual closed-loop structure significantly improves the adaptability and accuracy of error compensation in complex environments based on dynamic changes in the surgical environment, ensuring the reliability of surgical robot positioning.

[0052] Among them, the motion compensation path correction in step S3 refers to the construction of an efficient and accurate motion control system through the two core links of error-driven real-time correction and closed-loop feedback optimization. First, with the motion error feedback parameters output in step S2 as the driving source, the motion compensation control and path adjustment module relies on advanced path planning algorithms to quickly carry out real-time correction of the robot control path at the moment of obtaining the error parameters. By precisely controlling the motion angles and speed parameters of each joint of the robot, accurate control instructions are generated and transmitted to the surgical robot execution system to drive the robot to move according to the corrected path, completing the preliminary compensation of the motion error and laying the foundation for subsequent optimization.

[0053] After the initial correction, the system enters the closed-loop feedback optimization phase. The motion compensation control and path adjustment module continuously monitors the robot's actual motion trajectory in real time, frequently comparing it with the corrected target path, and sensitively capturing the deviation data between the two. Based on the motion path correction control logic, the path planning is readjusted and the control instructions are updated, forming a complete closed-loop compensation mechanism of "monitoring-comparison-correction-feedback". This mechanism can dynamically respond to error changes that occur at any time during the surgical process. Compared with traditional offline correction methods, it significantly improves the motion control accuracy of the surgical robot and provides a solid guarantee for the reliability of surgical operations.

[0054] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0055] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. The optoelectronic fusion positioning error compensation system of the surgical robot is characterized by: The system consists of an optical positioning acquisition module, an electromagnetic interference detection and auxiliary positioning module, an optoelectronic dynamic fusion and weight adaptive adjustment module, a real-time error dynamic modeling and feedback module, and a motion compensation control and path adjustment module. Optical positioning acquisition module: This module uses cameras arranged at multiple angles to collect three-dimensional images of infrared marker points on the surgical robot actuator in real time and outputs raw optical position data. Electromagnetic interference detection and auxiliary positioning module: Receives raw optical data, uses a highly sensitive sensor array to detect environmental interference, and calibrates electromagnetic positioning data through modeling to eliminate interference effects; Photoelectric dynamic fusion and weight adaptive adjustment module: Based on the output data of the optical positioning acquisition module and the electromagnetic interference detection and auxiliary positioning module, it uses the extended Kalman filter and adaptive algorithm for dynamic fusion, changes the weight according to the environment, and outputs a high-confidence fusion pose; Real-time error dynamic modeling and feedback module: receives fused pose, integrates speed and environmental factors to build a dynamic model, and outputs error feedback parameters; Motion compensation control and path adjustment module: Based on the error feedback parameters, the motion path correction control formula is used, and the closed loop is transmitted back to the execution system to adjust the path in real time to form a compensation control closed loop.

2. The optoelectronic fusion positioning error compensation system for surgical robots according to claim 1, characterized in that: The optical positioning acquisition module includes: (1) Multi-angle optical image acquisition architecture: On the surgical robot actuator, characteristic infrared identification points are distributed in three dimensions, and the camera array is arranged at multiple angles to form a full range of visual acquisition areas; (2) Optical data processing and pose calculation: Using image processing algorithms, accurately extract the position information of the marker points in the image. Combined with the camera calibration parameters, the three-dimensional space pose calculation formula is used to back-project the optical image coordinates into three-dimensional space, thereby obtaining the preliminary position of the robot actuator in space. Three-dimensional space pose calculation formula: Where: is the target space pose coordinates measured optically; is the camera intrinsic parameter matrix; The pixel coordinate matrix of the infrared marker points in the image plane.

3. The optoelectronic fusion positioning error compensation system for surgical robots according to claim 1, characterized in that: The electromagnetic interference detection and auxiliary positioning module includes: (1) Electromagnetic interference monitoring and data acquisition architecture: Equipped with a high-sensitivity electromagnetic sensor array, it can capture the electromagnetic signal strength and frequency parameters in the environment in real time, and conduct detection and analysis on the location and characteristics of metal equipment to accurately identify the interference source; (2) Electromagnetic positioning data calibration and output: Use the electromagnetic interference model to separate the useful electromagnetic positioning signal from the interference signal. With the help of the electromagnetic positioning space transformation formula, the electromagnetic sensor data is converted into a spatial coordinate system that is unified with the optical system through coordinate transformation. Combined with the original optical data, the electromagnetic positioning data is deeply calibrated and corrected. Electromagnetic positioning space transformation formula: Where: The spatial pose coordinates calculated by the electromagnetic eye tracking system; Transformation matrix from electromagnetic beacon to global coordinate system; Relative pose data measured by electromagnetic sensors.

4. The optoelectronic fusion positioning error compensation system for surgical robots according to claim 1, characterized in that: The optoelectronic dynamic fusion and weight adaptive adjustment module includes: (1) Data fusion architecture based on extended Kalman filter: Based on optical positioning and electromagnetic positioning data, the two types of data are dynamically fused with the help of the filtering algorithm of the extended Kalman filter nonlinear system, and the optical and electromagnetic positioning information are integrated through prediction and update steps; (2) Dynamic weight adjustment and high-confidence pose output: Based on changes in the surgical environment, the extended Kalman filter fusion formula is used to dynamically adjust the weights of optical and electromagnetic data in real time. By continuously monitoring environmental parameters and positioning accuracy, a high-confidence fusion pose reflecting the actual position of the actuator is output; Extended Kalman filter fusion formula: Status prediction: Status Update: Dynamic weight adjustment: Where: is the predicted state quantity; is the control input at the previous moment; is the comprehensive Kalman gain at the current moment; is the observed value at the current moment; is the observation model function; is the optical data weight coefficient; is the electromagnetic data weight coefficient; 、 is the sub-Kalman gain for optics and electromagnetics.

5. The optoelectronic fusion positioning error compensation system for surgical robots according to claim 1, characterized in that: The real-time error dynamic modeling and feedback module includes: (1) Multi-source data integration and error influencing factor analysis: During the operation of the surgical robot, the actuator motion speed information is collected in real time through high-precision sensors. Combined with the electromagnetic interference detection and electromagnetic environment data obtained by the auxiliary positioning module, multi-source information is fully integrated to deeply analyze the mechanism of various factors affecting positioning error; (2) Dynamic error modeling and feedback parameter output: Based on the integrated multi-source data and with the help of the velocity-pose-environment joint feedback mechanism, an innovative dynamic error compensation system is constructed. The core velocity-pose-environment coupled error dynamic equation is used, combined with the fused pose data, to dynamically calculate the error and accurately output the motion error feedback parameters; Velocity-pose-environment coupling error dynamic equation: is the positioning error at the current moment; Fusion target pose; Expected speed; Actual speed; Real-time detection value of electromagnetic interference field strength; is the speed error weight coefficient; Environmental interference error weight coefficient.

6. The optoelectronic fusion positioning error compensation system for surgical robots according to claim 1, characterized in that: The motion compensation control and path adjustment module includes: (1) Error feedback driven path correction architecture: After receiving the motion error feedback parameters, the motion path correction control formula is used to automatically correct the robot's control path based on the error feedback information, and the motion angle and speed parameters of each joint of the robot are adjusted; (2) Dynamic closed-loop control and precise motion output: After completing the initial path correction, the correction command is transmitted back to the surgical robot execution system in a closed loop. At the same time, the actual movement of the robot is monitored in real time. The motion path correction control formula is used again to incorporate the deviation between the actual movement and the corrected path into the calculation, and the motion control path is dynamically corrected through error feedback. Motion path correction control formula: Where: is the control input after motion compensation; Original motion control instructions; Path gain adjustment matrix; The motion error is output by the Error Dynamics Modeling module.

7. A method for compensating for optoelectronic positioning errors of a surgical robot, comprising: The specific steps of this method are as follows: S1. Real-time acquisition of multi-source data: The optical positioning acquisition module collects the surgical robot actuator's optical posture data in real time, and the electromagnetic interference detection and auxiliary positioning module collects the environmental electromagnetic interference data in real time; S2, optoelectronic fusion and error modeling: Based on the data collected in step S1, the optoelectronic dynamic fusion and weight adaptive adjustment module realizes dynamic data fusion to generate a high-confidence pose. The real-time error dynamic modeling and feedback module then constructs a coupling model and outputs error feedback parameters. S3. Motion compensation path correction: Based on the error feedback parameters, the motion compensation module corrects the robot path in real time, transmits the command closed-loop back to the execution system, and continuously adjusts by comparing the actual and corrected paths to achieve precise motion control.

8. The method for compensating for optoelectronic fusion positioning errors of a surgical robot according to claim 7, characterized in that: The specific steps for real-time multi-source data acquisition in step S1 are as follows: S11. Dual-module collaborative data acquisition mechanism: The optical positioning acquisition module captures images of the three-dimensionally distributed characteristic infrared marking points on the surgical robot actuator at a preset frequency, and outputs raw optical data after image processing and calculation; The electromagnetic interference detection and auxiliary positioning module monitors the metal equipment and electromagnetic signals in the surgical environment in real time, analyzes and processes the interference model, and outputs electromagnetic auxiliary positioning data; S12. Reliability of data acquisition: For the first time, real-time electromagnetic interference detection is combined with assisted positioning. Optical data provides actuator posture information, and electromagnetic assisted positioning data takes into account environmental interference conditions. The two complement each other.

9. The method for compensating for optoelectronic fusion positioning errors of a surgical robot according to claim 8, characterized in that: The specific steps of photoelectric fusion and error modeling in step S2 are as follows: S21. Dynamic fusion processing of optoelectronic data: After receiving optical data and electromagnetic-assisted positioning data acquired in real time from multiple sources, the extended Kalman filter algorithm is used to deeply fuse the two types of data to address data uncertainty. Simultaneously, the environmental interference adaptive weight adjustment algorithm dynamically adjusts the weights of the optical and electromagnetic data in the fusion process based on changes in the surgical environment, thereby generating a high-confidence fusion pose in real time. S22. Dynamic error modeling and parameter output: After receiving the high-confidence fusion posture obtained by optoelectronic dynamic fusion, based on the speed-posture-environment joint feedback mechanism, velocity feedback and electromagnetic environment factors are introduced to construct a dynamic error compensation mathematical model. Through mathematical calculation and analysis, the motion error feedback parameters are output.

10. The method for compensating for optoelectronic fusion positioning errors of a surgical robot according to claim 9, characterized in that: The specific steps of motion compensation path correction in step S3 are as follows: S31, Error-driven real-time path correction: Using the motion error feedback parameters output from step S2 as the driving core, the robot control path is immediately corrected in real time. By precisely adjusting the motion angles and speed parameters of each joint of the robot, control instructions that meet the correction requirements are generated and transmitted to the surgical robot execution system; S32. Closed-loop feedback optimization motion control: When the robot performs corrected path motion, the actual motion situation is compared with the corrected target path at high frequency to capture the deviation data between the two. Based on the motion path correction control logic, the path planning is adjusted again and the control instructions are updated, forming a full-process closed-loop compensation mechanism of monitoring-comparison-correction-feedback.

Images