System regulation and control method based on robot laparoscope cooperation and medium

Abstract

The invention provides a system regulation and control method based on robot laparoscope collaboration and a medium, and relates to the technical field of laparoscope collaboration. Extracting sample information and instrument information from the working image set, and determining an influence factor through the sample information and the instrument information; determining a prediction path and a prediction speed of the instrument in the next time period through the sample information and the influence factors; determining an initial adjustment path through the prediction path and the instrument spacing; acquiring the movement time of the instrument and the laparoscope, and determining the movement delay of the laparoscope; determining the time when the laparoscope moves to each point of the initial adjustment path through the predicted speed; intercepting an initial adjustment path in the moving delay to obtain an adjustment path; the laparoscope is moved along the adjustment path at a predicted speed by moving a delay ahead of time. And planning an adjustment route based on the predicted path, considering the movement delay of the laparoscope, extracting an execution adjustment instruction, reducing the time difference, and reducing the collision probability.

Description

Technical Field

[0001] The present invention relates to the field of laparoscopic collaboration technology, and in particular to a system control method and medium based on robot laparoscopic collaboration. Background Art

[0002] During the laparoscopic collaborative instrument test, the operating image of the instrument needs to be collected through the laparoscope lens. Traditional laparoscopic collaborative instruments require at least two operators to cooperate to complete the work, one or more operators hold the instrument to complete the operation, and one operator holds the laparoscope to assist in lighting and video recording. If the operators do not cooperate enough, there will be delays or the operation site cannot be seen. To solve this problem, a robot holding the scope is introduced. The robot adjusts the position of the laparoscope in real time according to the position of the instrument, so that the operator can see the corresponding operation site in time no matter how the instrument is held and worked. Because the robot needs to detect and analyze the position of the instrument before adjusting the position of the laparoscope, and then formulate the movement route of the laparoscope, and then control the movement of the laparoscope, the adjustment of the position of the laparoscope has a time lag, and the situation during operation is changeable. Although the corresponding operation site can be seen in time, there is also a situation where the laparoscope cannot be adjusted in time when the instrument moves, and there is a collision or resistance to the laparoscope, which interferes with the fine movements of the operation process and increases the risk and uncertainty of the operation. Summary of the invention

[0003] The purpose of the present invention is to provide a system control method and medium based on robot laparoscope collaboration. The technical problem to be solved is how to reduce the time difference between instrument movement and laparoscope adjustment, and reduce the probability of collision between the instrument and the laparoscope during work.

[0004] The present invention is achieved through the following technical solutions:

[0005] The first aspect provides a system control method based on robot laparoscope collaboration, comprising the following steps:

[0006] S100, presetting a working area, collecting images of the working area at a preset time, and obtaining a working image set;

[0007] Extracting sample information and device information corresponding to the sample information from the working image set, determining sample features that affect the device movement path through the sample information and the corresponding device information, and obtaining an influencing factor;

[0008] S200, predicting the moving path and moving speed of the device in the next period of time by using the above sample information and influencing factors of the previous period of time, and obtaining a predicted path and predicted speed;

[0009] S300, determining an initial adjustment path of the laparoscope through the predicted path and the preset instrument spacing;

[0010] S400, obtaining the movement time of the above-mentioned instruments and laparoscope, and determining the movement delay of the laparoscope;

[0011] S500, determining the time for the laparoscope to move to each point on the initial adjustment path by using the predicted speed;

[0012] Intercepting the initial adjustment path within the above movement delay to obtain an adjustment path;

[0013] S600, advance the above movement delay and move the laparoscope along the adjusted path at the predicted speed.

[0014] The movement path of the instrument is controlled by the operator's hand movements. First, a working area is determined, and image data is collected in this area. The sample features involved in the operation and the instruments used can be identified. By analyzing the working image set, key information such as sample features and instrument positions can be extracted to provide a basis for subsequent predictions. Based on the information previously obtained, the movement path and speed of the instrument in the future are predicted, and historical data are used to infer future instrument movements. According to the prediction results, not only can the movement route of the laparoscope be planned in advance, but also the delay time in the actual operation can be taken into account, so as to calculate the optimal adjustment time of the laparoscope, reduce the time difference between the laparoscope and the instrument, and avoid collision between the laparoscope and the moving instrument.

[0015] Furthermore, the specific steps of S100 include:

[0016] S110, arranging the working image set in chronological order, extracting sample information and instrument information from the working image of the previous time to obtain the previous sample information and the previous instrument information; extracting instrument information from the working image of the next time to obtain the next instrument information; wherein the sample features in the sample information include the three-dimensional coordinates of the arm key points, the wrist key points, the finger key points and the corresponding key points; the instrument features in the instrument information include the three-dimensional coordinates of the instrument;

[0017] S120, determining the moving path of the device through the previous device information and the next device information;

[0018] S130, determining the relationship between the sample features in the previous sample information and the instrument movement path through the previous sample information and the instrument movement path; traversing the above working image set to determine the relationship between the sample features and the instrument movement path;

[0019] S140, establishing an influencing factor model based on the relationship between the above sample characteristics and the device movement path;

[0020] S150, inputting the sample feature data into an influencing factor model to obtain the influence value of the sample feature on the moving path of the device;

[0021] S160: When the above influence value is greater than a preset influence threshold, the sample feature is an influence factor.

[0022] By analyzing the working image set, key time series data are extracted, including sample features (such as key points and three-dimensional coordinates of the arm, wrist, and fingers) and device features (such as the three-dimensional coordinates of the device), and the dynamic changes of sample features and device features are captured; based on the three-dimensional coordinates of the device at the previous moment and the next moment, the actual device movement path is calculated; by analyzing the relationship between sample features and the device movement path, the system understands how different postures affect the device movement path, and helps identify which actions have a significant impact on device movement.

[0023] Furthermore, the specific steps of obtaining the predicted path in S200 include:

[0024] S210, creating a feature relationship table, adding the influencing factor, influencing value and sample feature data of the influencing factor of the above-mentioned instrument movement path to the feature relationship table, and associating the instrument movement path, influencing factor, influencing value and sample feature data of the influencing factor;

[0025] S220, obtaining the sample information of the previous time, and extracting sample features and sample feature data from the sample information;

[0026] S230, matching the sample feature with the influencing factor in the feature relationship table, and when the match is successful, matching the sample feature data with the sample feature data of the matched influencing factor, and when the match is successful, obtaining the device movement path associated with the influencing factor and the sample feature data;

[0027] S240: After traversing all sample features and sample feature data in the sample information at the previous time, filter out the device movement path to obtain a predicted path.

[0028] Establish an associated database or table (i.e., a feature relationship table) to record various factors that affect the movement path of the device, including the influencing factors, their corresponding influencing values, and sample feature data. Obtain sample information from the most recent time point, extract the sample features and corresponding data (such as three-dimensional coordinates, etc.) contained therein, quickly search and match related sample features and sample feature data in the feature relationship table, preliminarily screen out several device movement paths, traverse all sample features and their data, screen out the device movement path that meets all sample features and sample feature data, and obtain the final predicted path.

[0029] Furthermore, the specific steps of obtaining the predicted speed in S200 include:

[0030] S250, obtaining the distance of the predicted path and the time taken by the device to move along the predicted path; wherein the device characteristics of the device information also include the time taken by the device to move along the device moving path;

[0031] S260: Calculate the moving speed of the device according to the distance and duration of the predicted path to obtain a predicted speed.

[0032] Furthermore, the specific steps of S300 include:

[0033] S310, the above-mentioned instrument spacing includes an upper limit spacing and a lower limit spacing, the above-mentioned upper limit spacing is the maximum spacing between the laparoscope and the instrument, and the above-mentioned lower limit spacing is the minimum spacing between the laparoscope and the instrument;

[0034] S320: The distance between the predicted path and the initial adjusted path is greater than a lower limit distance and less than an upper limit distance.

[0035] Considering that in actual operation, if the distance between the instrument and the laparoscope is too large, the field of view of the laparoscope may be insufficient, affecting the operation; if the distance is too small, the risk of collision between the laparoscope and the instrument may increase, thus improving the safety of the operation.

[0036] Furthermore, the distance between the laparoscope and the instrument is obtained in real time;

[0037] When the distance between the laparoscope and the instrument is equal to the lower limit distance, a distance instruction is generated to control the laparoscope to move away from the instrument;

[0038] When the distance between the laparoscope and the instrument is equal to the upper limit distance, an approach instruction is generated to control the laparoscope to approach the instrument.

[0039] Providing real-time distance feedback enables the system to respond quickly according to the current situation, ensuring the safety of the operation process and the field of view of laparoscopic photography.

[0040] Furthermore, the specific steps of S400 include:

[0041] Obtaining the start time of the movement of the above-mentioned instruments and the start time of the movement of the laparoscope;

[0042] The movement delay of the laparoscope is determined by the start time of the above-mentioned instrument movement and the start time of the laparoscope movement.

[0043] According to the calculated movement delay, a corresponding adjustment strategy is formulated to advance or delay the movement of the laparoscope to ensure the synchronization between the two; by adjusting the delay, the movement synchronization between the laparoscope and the instrument is ensured, which reduces the waiting time and movement delay, thereby reducing the risk of collision between the laparoscope and the instrument.

[0044] A second aspect provides a computer-readable storage medium having computer program instructions stored thereon, and the computer program instructions implement the above-mentioned system control method when executed by a processor.

[0045] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0046] The movement path of the instrument is controlled by the surgeon's hand movements. First, a working area is determined and image data is collected in the area. The sample features involved in the operation and the instruments used can be identified. By analyzing the working image set, key information such as sample features and instrument positions can be extracted to provide a basis for subsequent predictions. Based on previously acquired information, the movement path and speed of the instrument in the future are predicted, and historical data are used to infer future instrument movements. According to the prediction results, not only can the movement route of the laparoscope be planned in advance, but also the delay time in actual operation can be taken into account, so as to calculate the optimal adjustment time of the laparoscope, reduce the time difference between the laparoscope and the instrument, and avoid collision between the laparoscope and the moving instrument. The laparoscope moves at the predicted speed, so that the laparoscope and the instrument move synchronously, reducing collision problems caused by different movement speeds and response times of the laparoscope and the instrument. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other relevant drawings can be obtained based on these drawings without creative work. In the drawings:

[0048] Figure 1 Main flow chart. DETAILED DESCRIPTION

[0049] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0050] First embodiment:

[0051] System control method based on robot laparoscopy collaboration, combined with Figure 1 , including the following steps:

[0052] S100, presetting a working area, collecting images of the working area at a preset time, and obtaining a working image set;

[0053] Extracting sample information and device information corresponding to the sample information from the working image set, determining sample features that affect the device movement path through the sample information and the corresponding device information, and obtaining an influencing factor;

[0054] S200, predicting the moving path and moving speed of the device in the next period of time by using the above sample information and influencing factors of the previous period of time, and obtaining a predicted path and predicted speed;

[0055] S300, determining an initial adjustment path of the laparoscope through the predicted path and the preset instrument spacing;

[0056] S400, obtaining the movement time of the above-mentioned instruments and laparoscope, and determining the movement delay of the laparoscope;

[0057] S500, determining the time for the laparoscope to move to each point on the initial adjustment path by using the predicted speed;

[0058] Intercepting the initial adjustment path within the above movement delay to obtain an adjustment path;

[0059] S600, advance the above movement delay and move the laparoscope along the adjusted path at the predicted speed. Plan the movement path of the laparoscope based on the predicted instrument movement path, move the laparoscope in advance according to the movement delay of the laparoscope, so that the laparoscope and the instrument move at the same time, reducing the collision problem caused by the different response times of the laparoscope and the instrument; the laparoscope moves at the predicted speed, so that the laparoscope and the instrument move at the same frequency, reducing the collision problem caused by the different movement speeds of the laparoscope and the instrument.

[0060] Considering that the moving path of the instrument is controlled by the operator's hand movements, we first determine a working area and collect image data in this area, so that we can identify the sample features and instrument features involved in the operation; by analyzing the working image set, we can extract key information such as sample features and instrument position, providing a basis for subsequent predictions; based on the previously acquired information, we predict the moving path and speed of the instrument in the future, and use historical data to infer future instrument movements; according to the prediction results, we can not only plan the moving route of the laparoscope in advance, but also take into account the delay time in the actual operation, so as to calculate the optimal adjustment time of the laparoscope, reduce the time difference between the laparoscope and the instrument, and avoid collision between the laparoscope and the moving instrument.

[0061] A usage scenario for reference, in a urology experiment, carbon dioxide is injected into the abdominal cavity of a target (the target can be a human model) through a pneumoperitoneum needle to make the target's abdomen bulge, and a laparoscope and instruments are inserted into the abdominal cavity to collect a working image, which covers the laparoscope, instruments and the upper limbs of the operator. The image outside the abdominal cavity can be collected by an external device, and the image inside the abdominal cavity can be collected by a laparoscope. The working image is spliced ​​by the external image and the internal image, and the splicing method can adopt the existing image processing, which is not elaborated in the present invention; extract sample features in the working image, and predict the moving path and moving speed of the instrument based on the extracted sample features and influencing factors; plan the adjustment path of the laparoscope based on the predicted instrument moving path and the set instrument spacing; in order to reduce the problem of laparoscope response delay, move the laparoscope at the predicted speed in advance to reduce the collision problem caused by time difference and speed difference.

[0062] Second embodiment:

[0063] Based on the first embodiment, the specific steps of S100 include:

[0064] S110, arranging the above-mentioned working image set in chronological order, extracting sample information and instrument information from the working image of the previous time to obtain the previous sample information and the previous instrument information; extracting instrument information from the working image of the next time to obtain the next instrument information; wherein the sample information includes sample features and sample feature data, the sample features include arm key points, wrist key points and finger key points, and the sample feature data includes the three-dimensional coordinates of the arm key points, wrist key points and finger key points; the instrument information includes instrument features and instrument feature data, and the instrument feature data includes the three-dimensional coordinates of the instrument;

[0065] S120, determining the moving path of the device through the previous device information and the next device information;

[0066] S130, determining the relationship between the sample features in the previous sample information and the instrument movement path through the previous sample information and the instrument movement path; traversing the above working image set to determine the relationship between the sample features and the instrument movement path;

[0067] S140, establishing an influencing factor model based on the relationship between the above sample characteristics and the device movement path;

[0068] S150, inputting the numerical value of the above sample feature into the influencing factor model to obtain the influencing value of the above sample feature on the moving path of the instrument;

[0069] S160: When the above influence value is greater than a preset influence threshold, the sample feature is an influence factor.

[0070] By analyzing the working image set, key time series data are extracted, including sample features (such as key points and three-dimensional coordinates of the arm, wrist, and fingers) and device features (such as the three-dimensional coordinates of the device), and the dynamic changes of sample features and device features are captured; based on the three-dimensional coordinates of the device at the previous moment and the next moment, the actual device movement path is calculated; by analyzing the relationship between sample features and the device movement path, the system understands how different postures affect the device movement path, and helps identify which actions have a significant impact on device movement.

[0071] A usage scenario for reference, in a urology surgery experiment, a first working image is collected at time t, a second working image is collected at time t+1, and a third working image is collected at time t+2, and the first working image, the second working image and the third working image constitute a working image set; when determining the influencing factor of the instrument, firstly extract the three-dimensional coordinates of the key points of the arm, the three-dimensional coordinates of the key points of the wrist, the three-dimensional coordinates of the key points of the fingers and the three-dimensional coordinates of the instrument from the first working image, and obtain the three-dimensional coordinates of the first key points of the arm, the first three-dimensional coordinates of the key points of the wrist, the first three-dimensional coordinates of the key points of the fingers and the first three-dimensional coordinates of the instrument, and then extract the three-dimensional coordinates of the instrument from the second working image to obtain the second three-dimensional coordinates of the instrument; the moving path of the instrument from time t to time t+1 is obtained through the three-dimensional coordinates of the first instrument and the three-dimensional coordinates of the second instrument, and the moving path is a vector and can be moved as a whole; the relative relationship between the coordinates of the key points (such as the extension length of the arm, the rotation angle of the wrist, the bending angle of the finger, etc.) is determined through the three-dimensional coordinates of the key points of the arm, the three-dimensional coordinates of the key points of the wrist and the three-dimensional coordinates of the key points of the fingers, so as to obtain the relative relationship between the corresponding key point coordinates when the instrument moves along the moving path of the instrument, thereby avoiding the individual differences of the surgeon;

[0072] Similarly, determine the relative relationship between the instrument movement path from time t+1 to time t+2 and the coordinates of the key points corresponding to the movement of the instrument along this instrument movement path, and integrate the relationship between the sample features from time t to time t+2 and the instrument movement path; establish an influencing factor model based on the integrated relationship, and calculate the degree of influence of each sample feature on the instrument movement path based on the influencing factor model.

[0073] Third embodiment:

[0074] Based on the second embodiment, the specific steps of obtaining the predicted path in S200 include:

[0075] S210, creating a feature relationship table, adding the influencing factor, influencing value and sample feature data of the influencing factor of the above-mentioned instrument movement path to the feature relationship table, and associating the instrument movement path, influencing factor, influencing value and sample feature data of the influencing factor;

[0076] S220, obtaining the sample information of the previous time, and extracting sample features and sample feature data from the sample information;

[0077] S230, matching the sample features with the influencing factors in the feature relationship table;

[0078] When the sample feature matching is successful, the sample feature data is matched with the sample feature data of the matched influencing factor;

[0079] When the sample feature data is successfully matched, the device movement path associated with the influencing factor and the sample feature data is obtained;

[0080] When the above sample feature data fails to match, it means that the sample feature data does not meet the requirements for affecting the movement path of the device;

[0081] When the above sample feature matching fails, it means that the sample feature is a non-influencing factor;

[0082] S240: After traversing all sample features and sample feature data in the sample information at the previous time, filter out the device movement path to obtain a predicted path.

[0083] Establish an associated database or table (i.e., a feature relationship table) to record various factors that affect the movement path of the device, including the influencing factors, their corresponding influencing values, and sample feature data. Obtain sample information from the most recent time point, extract the sample features and corresponding data (such as three-dimensional coordinates, etc.) contained therein, quickly search and match related sample features and sample feature data in the feature relationship table, preliminarily screen out several device movement paths, traverse all sample features and their data, screen out the device movement path that meets all sample features and sample feature data, and obtain the final predicted path.

[0084] In a specific embodiment, the specific steps of obtaining the predicted speed in S200 include:

[0085] S250, obtaining the distance of the predicted path and the time taken by the device to move along the predicted path; wherein the device characteristics of the device information also include the time taken by the device to move along the device moving path;

[0086] S260: Calculate the moving speed of the device according to the distance and duration of the predicted path to obtain a predicted speed.

[0087] A usage scenario for reference is to extract the three-dimensional coordinates of the instrument from the third working image to obtain the third three-dimensional coordinates of the instrument, calculate the distance S of the instrument movement path from time t to time t+2 by using the first three-dimensional coordinates of the instrument, the second three-dimensional coordinates of the instrument and the third three-dimensional coordinates of the instrument, and calculate the predicted speed by using the following formula;

[0088] , where the first device three-dimensional coordinates , the second instrument three-dimensional coordinates , the third instrument three-dimensional coordinates , Indicates the prediction speed.

[0089] Fourth embodiment:

[0090] Based on any of the above embodiments, the specific steps of S300 include:

[0091] S310, the above-mentioned instrument spacing includes an upper limit spacing and a lower limit spacing, the above-mentioned upper limit spacing is the maximum spacing between the laparoscope and the instrument, and the above-mentioned lower limit spacing is the minimum spacing between the laparoscope and the instrument;

[0092] S320: The distance between the predicted path and the initial adjusted path is greater than a lower limit distance and less than an upper limit distance.

[0093] Considering that in actual operation, if the distance between the instrument and the laparoscope is too large, the field of view of the laparoscope may be insufficient, affecting the operation; if the distance is too small, the risk of collision between the laparoscope and the instrument may increase, thus improving the safety of the operation.

[0094] In a specific embodiment, the distance between the laparoscope and the instrument is obtained in real time;

[0095] When the distance between the laparoscope and the instrument is equal to the lower limit distance, a distance instruction is generated to control the laparoscope to move away from the instrument;

[0096] When the distance between the laparoscope and the instrument is equal to the upper limit distance, an approach instruction is generated to control the laparoscope to approach the instrument.

[0097] Providing real-time distance feedback enables the system to respond quickly according to the current situation, ensuring the safety of the operation process and the field of view of laparoscopic photography.

[0098] Fifth embodiment:

[0099] Based on any of the above embodiments, the specific steps of S400 include:

[0100] Obtaining the start time of the movement of the above-mentioned instruments and the start time of the movement of the laparoscope;

[0101] The movement delay of the laparoscope is determined by the start time of the above-mentioned instrument movement and the start time of the laparoscope movement.

[0102] According to the calculated movement delay, a corresponding adjustment strategy is formulated to advance or delay the movement of the laparoscope to ensure the synchronization between the two; by adjusting the delay, the movement synchronization between the laparoscope and the instrument is ensured, which reduces the waiting time and movement delay, thereby reducing the risk of collision between the laparoscope and the instrument.

[0103] Sixth embodiment:

[0104] A computer-readable storage medium stores computer program instructions, which implement the above-mentioned system control method when executed by a processor.

[0105] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A system control method based on robot laparoscopy collaboration, characterized in that: The following steps are involved: S100, presetting a working area, collecting images of the working area at a preset time, and obtaining a working image set; Extracting sample information and instrument information corresponding to the sample information from the working image set, determining sample features that affect the instrument movement path through the sample information and the corresponding instrument information, and obtaining an influencing factor; S200, predicting the moving path and moving speed of the device in the next period of time by using the sample information and influencing factors of the previous period of time, and obtaining a predicted path and a predicted speed; S300, determining an initial adjustment path of the laparoscope through the predicted path and the preset instrument spacing; S400, obtaining the movement time of the instrument and the laparoscope, and determining the movement delay of the laparoscope; S500, determining the time for the laparoscope to move to each point on the initial adjustment path according to the predicted speed; intercepting an initial adjustment path within the movement delay to obtain an adjustment path; S600, advancing the movement delay to move the laparoscope along the adjusted path at the predicted speed.

2. The system control method according to claim 1, characterized in that: The specific steps of S100 include: S110, arranging the working image set in chronological order, extracting sample information and instrument information from the working image of the previous time to obtain the previous sample information and the previous instrument information; extracting instrument information from the working image of the next time to obtain the next instrument information; wherein the sample features in the above sample information include the three-dimensional coordinates of the arm key points, the wrist key points, the finger key points and the corresponding key points; the instrument features in the above instrument information include the three-dimensional coordinates of the instrument; S120, determining the instrument movement path through the previous instrument information and the next instrument information; S130, determining the relationship between the sample features in the previous sample information and the instrument movement path through the previous sample information and the instrument movement path; traversing the working image set to determine the relationship between the sample features and the instrument movement path; S140, establishing an influencing factor model based on the relationship between the sample characteristics and the device movement path; S150, inputting the sample feature data into an influence factor model to obtain an influence value of the sample feature on the movement path of the device; S160: When the influence value is greater than a preset influence threshold, the sample feature is an influence factor.

3. The system control method according to claim 2, characterized in that: The specific steps of obtaining the predicted path in S200 include: S210, creating a feature relationship table, adding the influencing factor, influencing value and sample feature data of the influencing factor of the device movement path to the feature relationship table, and associating the device movement path, influencing factor, influencing value and sample feature data of the influencing factor; S220, obtaining the sample information of the previous time, and extracting sample features and sample feature data from the sample information; S230, matching the sample feature with the influencing factor in the feature relationship table, and when the match is successful, matching the sample feature data with the sample feature data of the matched influencing factor, and when the match is successful, obtaining the device movement path associated with the influencing factor and the sample feature data; S240: After traversing all sample features and sample feature data in the sample information of the previous time, the moving path of the device is screened out to obtain a predicted path.

4. The system control method according to claim 1, characterized in that: The specific steps of obtaining the predicted speed in S200 include: S250, obtaining the distance of the predicted path and the time taken by the device to move along the predicted path; wherein the device characteristics of the device information also include the time taken by the device to move along the device movement path; S260: Calculate the moving speed of the device according to the distance and duration of the predicted path to obtain a predicted speed.

5. The system control method according to claim 1, characterized in that: The specific steps of S300 include: S310, the instrument spacing includes an upper spacing and a lower spacing, the upper spacing is the maximum spacing between the laparoscope and the instrument, and the lower spacing is the minimum spacing between the laparoscope and the instrument; S320: The distance between the predicted path and the initial adjusted path is greater than a lower limit distance and less than an upper limit distance.

6. The system control method according to claim 5, characterized in that: Acquiring the distance between the laparoscope and the instrument in real time; When the distance between the laparoscope and the instrument is equal to the lower limit distance, a distance instruction is generated to control the laparoscope to move away from the instrument; When the distance between the laparoscope and the instrument is equal to the upper limit distance, an approach instruction is generated to control the laparoscope to approach the instrument.

7. The system control method according to claim 1, characterized in that: The specific steps of S400 include: Obtaining the start time of the movement of the instrument and the start time of the movement of the laparoscope; The movement delay of the laparoscope is determined by the start time of the movement of the instrument and the start time of the movement of the laparoscope.

8. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the system control method according to any one of claims 1 to 7 is implemented.

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