An automated loading and positioning auxiliary device specifically for the sterilization and disinfection of laparoscopic endoscopes.

Abstract

This invention proposes an automated loading and positioning auxiliary device specifically for the sterilization and disinfection of laparoscopic instruments, belonging to the technical field of laparoscopic instrument sterilization and disinfection auxiliary equipment. It includes a laparoscopic instrument loading module, a hardware identification module, a loading control module, a management and decision-making module, a sterilization rack positioning module, and a loading inspection module. Through a highly automated design, this invention enables automated operation of multiple key stages, including loading, identification, grasping, and loading. Furthermore, by combining image recognition, RFID technology, and laser positioning methods, it ensures that each type of laparoscopic instrument is correctly processed and loaded according to its characteristics and requirements. It can automatically adjust the loading scheme based on the characteristics of different types of laparoscopic instruments and generate the optimal loading scheme in real time based on the equipment type and status, ensuring that laparoscopic instruments are processed and loaded in the most suitable way. Therefore, this invention has the capability to process multiple types of laparoscopic instruments.

Description

Technical Field

[0001] This invention relates to the field of auxiliary equipment for the disinfection and sterilization of laparoscopic instruments, and in particular to an automated loading and positioning auxiliary device specifically for the disinfection and sterilization of laparoscopic instruments. Background Technology

[0002] With the rapid development of medical technology, laparoscopic instruments, as common and important tools in modern medicine, play a crucial role in diagnosis and treatment. The use of laparoscopic instruments has become increasingly widespread, from traditional laparoscopes and arthroscopes to modern endoscopes. They are widely used in various medical fields such as surgery, internal medicine, gynecology, and urology, and provide technical support for the success of many complex surgeries. However, because laparoscopic instruments come into direct contact with internal tissues during surgery, they are inevitably susceptible to contamination by bacteria, viruses, and other microorganisms. Therefore, the requirements for the sterilization and disinfection of laparoscopic instruments are extremely high. The sterilization and disinfection of laparoscopic instruments must follow strict standards and procedures to ensure patient safety and prevent cross-infection.

[0003] Currently, the sterilization process of laparoscopic instruments relies on highly precise operation and strict management, involving multiple stages such as equipment cleaning, disinfection, sterilization, and packaging. Among these, the loading and positioning of laparoscopic instruments plays a crucial role in the sterilization process. The accuracy of loading and positioning directly affects not only the sterilization effect of laparoscopic instruments but also the lifespan of the equipment and the work efficiency of medical institutions. Traditional laparoscopic instrument loading and positioning usually rely on manual operation, which not only increases the complexity of the operation but may also lead to instrument damage or incomplete sterilization due to human error, thereby reducing the quality of sterilization. Therefore, this invention proposes an automated loading and positioning auxiliary device specifically for laparoscopic sterilization to solve the problems existing in the prior art. Summary of the Invention

[0004] To address the aforementioned problems, the present invention aims to provide an automated loading and positioning auxiliary device specifically for the disinfection and sterilization of laparoscopic instruments. This automated loading and positioning auxiliary device efficiently completes multiple steps such as feeding, identification, grasping, and loading through an automated system, reducing manual operation and equipment downtime, and solving the problems existing in the prior art.

[0005] To achieve the objectives of this invention, the invention is implemented through the following technical solution: an automated loading and positioning auxiliary device for endoscope disinfection and sterilization, including an endoscope loading module for transporting endoscopes to be disinfected;

[0006] The hardware identification module is used to identify endoscopic instruments and sterilization racks;

[0007] The loading control module is used to load endoscopic instruments onto the corresponding sterilization rack based on the information identified by the hardware identification module.

[0008] The management and decision-making module is used to dynamically plan the endoscope loading strategy based on the recognition data from the material loading and recognition module.

[0009] The sterilization rack positioning module is used to ensure the precise positioning of laparoscopic instruments on the sterilization rack and to maintain the stability of the laparoscopic instruments by locking them.

[0010] The loading inspection module is used to detect the posture of the loaded laparoscopic instruments by laser scanning.

[0011] A further improvement is that the endoscope loading module includes a vibration orientation submodule, which is used to align the endoscope with the conveyor belt in the same direction through directional vibration.

[0012] The conveyor belt transport submodule is used to transport endoscopic instruments via a conveyor belt.

[0013] The attitude pre-correction submodule is used in conjunction with the conveyor belt delivery submodule to initially adjust the orientation of the endoscopic instruments.

[0014] A further improvement is that the hardware recognition module includes an image recognition submodule, which is used to identify the types of endoscopic instruments using a convolutional neural network algorithm;

[0015] The RFID identification submodule is used to read the RFID tags on the sterilization rack using RFID methods.

[0016] The laser calibration submodule is used to generate the spatial coordinates of the instrument's gripping point.

[0017] A further improvement is that the feeding control module includes a six-degree-of-freedom robotic arm submodule, which is used to control the six-axis robotic arm to transport endoscopic instruments;

[0018] The airbag gripper submodule is used in conjunction with the six-degree-of-freedom robotic arm submodule to complete the gripping of laparoscopic instruments;

[0019] The robotic arm vision submodule is used to plan the motion trajectory of the robotic arm through vision algorithms;

[0020] The emergency stop feedback submodule is used to prevent the robotic arm from colliding during the loading process by monitoring with force sensors and ToF radar.

[0021] A further improvement is that the management and decision-making module includes an intelligent decision-making submodule, which is used to generate loading schemes for different types of endoscopic instruments through a reinforcement learning model;

[0022] The data storage submodule is used to store the operation data of endoscopic instruments via cloud storage, which facilitates subsequent traceability and management.

[0023] A further improvement is that the sterilization rack positioning module includes a positioning sub-module, which uses an infrared positioning grid to provide real-time feedback on the position of the endoscopic instruments on the sterilization rack.

[0024] The locking submodule secures the endoscopic instruments using pneumatic mechanisms and shape memory alloys.

[0025] A further improvement is that the feeding control module also includes an emergency pressure relief submodule, which is used to detect the working status of the airbag gripper submodule.

[0026] A further improvement is that the feeding control module also includes a force control submodule, which controls the force of the airbag gripper submodule during the gripping process by monitoring through a tactile sensor.

[0027] Further improvements are made in that the loading scheme includes the spacing of the endoscopic instruments, the orientation of the endoscopic instruments, the joint unfolding angle, and the suspension posture.

[0028] The beneficial effects of this invention are as follows:

[0029] (1) Through its highly automated design, this invention enables automated operation of multiple key processes, including feeding, identification, grasping, and loading. This not only reduces manual intervention but also greatly improves the overall system's operating efficiency, while also reducing errors and deviations that may be caused by human operation.

[0030] (2) This invention combines image recognition, RFID technology, and laser positioning methods to ensure that each type of endoscopic instrument is correctly processed and loaded according to its characteristics and requirements. It can automatically adjust the loading plan based on the characteristics of different types of endoscopic instruments. Through intelligent decision-making and reinforcement learning technology, the system can generate the optimal loading plan in real time based on the device type and status, ensuring that the endoscopic instruments are processed and loaded in the most suitable way. Therefore, this invention has the capability to process multiple types of endoscopic instruments. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of the structural process of the present invention. Detailed Implementation

[0032] To enhance understanding of the present invention, the present invention will be further described in detail below with reference to embodiments. These embodiments are only used to explain the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0033] Current sterilization processes rely heavily on manual operation, which presents the following problems:

[0034] Loading accuracy defects: Manual placement leads to instrument spacing errors >5mm and lumen orientation deviations >60°, resulting in a sterilization dead zone rate of 17%.

[0035] Frequent instrument damage: Hard gripping causes an average of 3.2 scratches per thousand instruments per year, and repair costs account for 12% of the total value of the instruments.

[0036] With the rapid development of automation, robotics, and artificial intelligence (AI) technologies, automated loading and positioning technologies have provided new solutions for the sterilization of endoscopic instruments. By introducing automated loading and positioning systems, the identification, loading, positioning, and transfer of endoscopic instruments during the sterilization process can be automated, significantly improving the efficiency and accuracy of sterilization. Especially in the busy environments of medical institutions, automated loading and positioning technologies not only reduce manual operations and operational risks but also improve the overall accuracy of sterilization, ensuring that every endoscopic instrument is sterilized under optimal conditions.

[0037] Therefore, according to Figure 1 As shown, this embodiment proposes an automated loading and positioning auxiliary device specifically for endoscope disinfection and sterilization. It is equipped with a central control system (PLC or industrial PC) for centralized scheduling and coordination of operations. Furthermore, the device includes:

[0038] The endoscope loading module is used to transport endoscopes to be sterilized. It is responsible for conveying the endoscopes from their initial position to the subsequent processing area, ensuring precise transport of the instruments. Through vibration orientation, conveyor belt transport, and posture pre-correction technologies, it ensures the accurate orientation and position of the endoscopes throughout the transport process, providing reliable assurance for subsequent sterilization and disinfection. It includes:

[0039] The vibration orientation submodule is used to align the endoscope with the conveyor belt through directional vibration. Specifically, it applies controlled, directional vibration to the endoscope instruments stacked in the initial machine posture. Using guide channels, it makes the long axis of the instrument tend to be aligned with the movement direction of the conveyor belt, reducing interference caused by instrument rotation, misalignment, or tilting.

[0040] The conveyor belt conveying submodule is used to transport endoscopic instruments via a conveyor belt. In this embodiment, the instruments are transported to the attitude pre-correction submodule. Furthermore, the conveyor belt is driven by a servo motor, which adjusts the conveying speed and transmission time according to system requirements. At the same time, it integrates a speed / position encoder to provide real-time feedback and closed-loop control of the belt speed, ensuring smooth and vibration-free transport. This prevents the endoscopic instruments from shifting, stacking, or getting blocked during transport.

[0041] The attitude pre-correction submodule is used in conjunction with the conveyor belt delivery submodule to initially adjust the orientation of the endoscopic instruments. It is itself a two-degree-of-freedom rotary table, which can then further adjust the orientation of the instruments to reduce the subsequent adjustment range of the six-axis robotic arm.

[0042] Therefore, the endoscope loading module, through the coordinated operation of multiple sub-modules such as vibration orientation, conveyor belt transport, and attitude pre-correction, can efficiently and stably complete the transport and positioning of endoscope instruments. This optimized design ensures that the endoscope instruments maintain the correct orientation and position throughout the transport process, providing reliable support for subsequent processing (such as loading and sterilization).

[0043] The hardware identification module is used to identify endoscopic instruments and sterilization racks. Through the collaborative work of multiple technologies such as image recognition, RFID identification, and laser calibration, the hardware identification module can accurately identify the type of endoscopic instruments, the status and position of the sterilization racks, and generate corresponding operation instructions, providing a decision-making basis for subsequent automatic loading, positioning, and other steps. It includes:

[0044] The image recognition submodule is used to identify the types of endoscopic instruments using a convolutional neural network (CNN) algorithm. Specifically, this submodule is equipped with an industrial camera to acquire image data of the endoscopic instruments in real time, preprocess the data, and then input it into the CNN for analysis. A CNN is a deep learning algorithm that excels at extracting features from images and performing classification. In the application of endoscopic instruments, the CNN algorithm can identify features such as the instrument's shape, size, and identifiers to determine its type and model. The CNN algorithm is pre-trained, meaning it learns the characteristics of different endoscopic instruments by training on a large amount of image data, enabling the model to accurately identify different types of endoscopic instruments in real-world environments.

[0045] The RFID identification submodule is used to read RFID tags on the sterilization racks using RFID methods. Since different laparoscopic instruments require different sterilization racks (used to load the endoscopes and then place them in the corresponding sterilization equipment), each rack is pre-attached with an RFID tag. Each tag contains unique identification information to distinguish between different racks. Furthermore, the RFID identification submodule includes an RFID reader and an antenna for wirelessly scanning the RFID tags on the sterilization racks, ensuring that each laparoscopic instrument is processed according to the correct rack position.

[0046] The laser calibration submodule generates the spatial coordinates of the instrument gripping point, ensuring that the robotic arm can accurately grasp the endoscopic instruments. Furthermore, the laser calibration submodule is equipped with a high-precision laser sensor, which generates the coordinate information of the endoscopic instrument in three-dimensional space by scanning the position and size data of the endoscopic instrument. Thus, the laser sensor scans the outline of the endoscopic instrument in real time, and combined with image recognition data, accurately calculates the gripping point and corresponding spatial coordinate data of the instrument. The spatial coordinate data is then provided to the six-degree-of-freedom robotic arm submodule for precise positioning of the gripping point of the endoscopic instrument, ensuring that the endoscopic instrument can be accurately grasped by the robotic arm and transferred to the next processing stage.

[0047] The loading control module, used to load endoscopic instruments onto the corresponding sterilization racks based on information identified by the hardware recognition module, includes:

[0048] The six-degree-of-freedom robotic arm submodule is used to control the six-axis robotic arm to transport endoscopic instruments. The six-axis robotic arm performs movements along a specified path and angle through servo motors and drive devices, ensuring that the endoscopic instruments are accurately moved from one position to another.

[0049] The airbag gripper submodule works in conjunction with the six-degree-of-freedom robotic arm submodule to grasp endoscopic instruments. Employing pneumatic technology, the airbag gripper submodule uses the expansion and contraction of the airbag to generate gripping force, reducing mechanical stress and damage to the endoscopic instruments. Specifically, the airbag gripper submodule uses a three-chamber zoned pressure control system: a central chamber (grabbing the main shaft) + side chambers (covering the joints), with independent PID pressure control (adjustable from 0.3 to 1.5 N) and equipped with biomimetic silicone finger sleeves.

[0050] The robotic arm vision submodule is used to plan the movement trajectory of the robotic arm through visual algorithms. Specifically, it is equipped with an Eye-in-Hand system (camera integrated into the end of the robotic arm). Based on visual feedback, the system dynamically adjusts the movement trajectory of the robotic arm to ensure the stability and accuracy of the endoscopic instruments during the grasping process.

[0051] The emergency stop feedback submodule uses force sensors and Time-of-Flight (ToF) radar to prevent collisions with the robotic arm during the loading process. Specifically, a force sensor installed at the end of the robotic arm monitors the contact between the arm and the endoscope instruments and the working environment in real time. When an abnormal collision or excessive force is detected, the emergency stop feedback submodule immediately triggers an emergency stop command, quickly halting the robotic arm's movement to prevent equipment damage or loss of endoscope instruments. The ToF radar scans the surrounding environment, identifying potential obstacles and collision risks in advance, and works in conjunction with the force sensors to further enhance collision prevention capabilities.

[0052] The emergency decompression submodule is used to detect the working status of the airbag gripper submodule, ensuring that the airbag does not over-inflate during the gripping process, thus avoiding damage to the instrument. Accordingly, the emergency decompression submodule uses a piezoelectric sensor (0-5kPa) with a sampling rate of 1kHz to identify pressure changes >2N / ms, and monitors the air pressure of the airbag gripper in real time. If the inflation rate is >50ml / s, it is determined that decompression is required, and the decompression submodule will immediately release the excess air pressure to prevent the airbag from over-inflating, which could lead to an overly tight grip or damage to the endoscopic instrument.

[0053] The force control submodule is used to monitor the force during the grasping process of the airbag gripper submodule by generating a grasping force cloud map (resolution 0.01N) through a tactile sensor (64-unit piezoresistive matrix (2mm spacing). When the sensor detects that the contact force between the surface of the endoscopic instrument and the airbag gripper is too large, the system will automatically reduce the expansion pressure of the airbag gripper to avoid excessive pressure on the endoscopic instrument.

[0054] The management and decision-making module is used to dynamically plan the endoscope loading strategy based on the recognition data from the material loading and identification module. It includes:

[0055] The intelligent decision-making submodule is used to generate loading plans for different types of endoscopic instruments through a reinforcement learning model. The specific process for generating loading plans is as follows:

[0056] Step 1: Input data, including instrument type (laparoscopy / arthroscopy, etc.), physical dimensions (length / diameter / number of joints), sterilization rack type (high-temperature steam / low-temperature ethylene oxide), and available slots in the sterilization rack;

[0057] Step 2: Policy generation, using a reinforcement learning model (PPO algorithm), which includes an input layer (state vector), a hidden layer (3 fully connected layers, 256 nodes, ReLU activation) and an output layer (action probability distribution, each action corresponds to a loading policy, such as the position, orientation, and angle of the endoscopic instrument).

[0058] Step 3: Reward calculation, constructing a multi-objective reward function, the formula is shown below:

[0059] R 总 =w1R1+w2R2+w3R3+w4R4

[0060] In the formula, R1, R2, R3, and R41 are the sterilization effectiveness reward, instrument safety reward, loading efficiency reward, and frame balance reward, respectively; w1, w2, w3, and w4 are the corresponding weights.

[0061] Step 4: Action Execution and Learning. Based on the feedback data after execution, the system calculates the reward obtained by the current action. The PPO algorithm determines the optimal policy update direction by calculating the difference between the current policy and the old policy (i.e., the probability ratio) and the expected value of the reward. Thus, through multiple iterations, the model continuously updates its policy and learns how to select a more efficient loading scheme. Finally, through multiple rounds of training and adjustment, the model gradually learns how to automatically generate the most suitable loading scheme according to different types of endoscopic instruments and environmental conditions, thereby improving the efficiency and accuracy of the entire endoscopic instrument disinfection and sterilization process.

[0062] Step 5: Loading plan output, including the spacing of laparoscopic instruments (minimum interval between adjacent instruments), the orientation of laparoscopic instrument installation (angle between the lumen axis and the sterilizing agent flow direction), the joint deployment angle (ensuring the interior of the lumen is exposed), and the suspension posture (inverted angle of the endoscope).

[0063] The data storage submodule is used to store the operation data of endoscopic instruments via cloud storage, which facilitates subsequent traceability and management.

[0064] A sterilization rack positioning module, used to ensure the precise positioning of laparoscopic instruments on the sterilization rack and to maintain the stability of the laparoscopic instruments by locking, includes:

[0065] The positioning submodule uses an infrared positioning grid to provide real-time feedback on the position of the endoscopic instruments on the sterilization rack. Specifically, the infrared positioning grid method involves placing infrared light sources and receivers above or around the sterilization rack to generate real-time three-dimensional coordinate data of the endoscopic instruments' position. This data is then connected to the degree-of-freedom robotic arm submodule to provide real-time position information, ensuring the accurate placement of the endoscopic instruments on the sterilization rack.

[0066] The locking submodule secures the endoscopic instruments using pneumatic mechanisms and shape memory alloys. Specifically, the pneumatic system uses cylinders and air pressure to adjust the opening and closing of the locking device, automatically clamping or releasing according to the shape of the endoscopic instrument to ensure that the instrument does not shift during sterilization. The shape memory alloy adjusts its shape through heating or cooling, automatically adapting to the shape of the instrument when it is loaded. When the system sends a signal, the alloy material deforms and fixes the position of the endoscopic instrument, further ensuring its stability.

[0067] Therefore, by combining pneumatic and shape memory alloy methods, the fixation method can be automatically adjusted according to different endoscopic instruments, which has high adaptability and flexibility.

[0068] The loading inspection module is used to detect the posture of the loaded endoscopic instruments using laser scanning. Specifically, it determines the position and angle of the target object by emitting a laser beam and receiving the reflected light. It then uses triangulation (accurately calculating the object's position in three-dimensional space by measuring the reflection angle between the laser beam and the target object) to calculate the precise coordinates of the target object. The real-time captured data is then compared with preset loading standards to determine whether the loading posture of the endoscopic instruments meets the requirements.

[0069] When the loading posture of the endoscopic instrument is detected to be non-compliant with the standard, the loading inspection module sends feedback data to the management and decision-making module, and then readjusts the position.

[0070] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the present invention without departing from its framework and scope of application, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. An automated loading and positioning auxiliary device specifically for the disinfection and sterilization of laparoscopic endoscopes, characterized in that: Includes a laparoscope loading module for transporting laparoscopes to be sterilized; The hardware identification module is used to identify endoscopic instruments and sterilization racks; The loading control module is used to load endoscopic instruments onto the corresponding sterilization rack based on the information identified by the hardware identification module. The loading control module includes a six-degree-of-freedom robotic arm sub-module, which is used to control the six-axis robotic arm to transport endoscopic instruments. The management and decision-making module is used to dynamically plan the endoscope loading strategy based on the recognition data from the material loading and recognition module. The sterilization rack positioning module is used to ensure the precise positioning of laparoscopic instruments on the sterilization rack and to maintain the stability of the laparoscopic instruments by locking them. The loading inspection module is used to detect the posture of the loaded laparoscopic instruments by laser scanning. The management and decision-making module includes an intelligent decision-making submodule, which is used to generate loading schemes for different types of endoscopic instruments through a reinforcement learning model; The data storage submodule is used to store the operation data of endoscopic instruments via cloud storage, which facilitates subsequent traceability and management. The sterilization rack positioning module includes a positioning sub-module, which uses an infrared positioning grid to provide real-time feedback on the position of the endoscopic instruments on the sterilization rack. The locking submodule secures the endoscopic instruments using pneumatic mechanisms and shape memory alloy fixation. The loading scheme includes the spacing of the laparoscopic instruments, the orientation of the laparoscopic instruments, the joint deployment angle, and the suspension posture.

2. The automated loading and positioning auxiliary device for endoscope disinfection and sterilization according to claim 1, characterized in that: The endoscope loading module includes a vibration orientation submodule, which is used to align the endoscope with the conveyor belt in the same direction through directional vibration. The conveyor belt transport submodule is used to transport endoscopic instruments via a conveyor belt. The attitude pre-correction submodule is used in conjunction with the conveyor belt delivery submodule to initially adjust the orientation of the endoscopic instruments.

3. The automated loading and positioning auxiliary device for endoscope disinfection and sterilization according to claim 1, characterized in that: The hardware identification module includes an image recognition submodule, which is used to identify the types of endoscopic instruments using a convolutional neural network algorithm; The RFID identification submodule is used to read the RFID tags on the sterilization rack using RFID methods. The laser calibration submodule is used to generate the spatial coordinates of the instrument's gripping point.

4. The automated loading and positioning auxiliary device for endoscope disinfection and sterilization according to claim 1, characterized in that: The feeding control module also includes an airbag gripper sub-module, which works in conjunction with the six-degree-of-freedom robotic arm sub-module to complete the gripping of endoscopic instruments; The robotic arm vision submodule is used to plan the robotic arm's motion trajectory through visual algorithms; The emergency stop feedback submodule is used to prevent the robotic arm from colliding during the loading process by monitoring with force sensors and ToF radar.

5. The automated loading and positioning auxiliary device for endoscope disinfection and sterilization according to claim 1, characterized in that: The feeding control module also includes an emergency pressure relief submodule, which is used to detect the working status of the airbag gripper submodule.

6. The automated loading and positioning auxiliary device for endoscope disinfection and sterilization according to claim 1, characterized in that: The feeding control module also includes a force control submodule, which controls the force of the airbag gripper submodule during the gripping process by monitoring with a tactile sensor.

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