System Control Method and Medium Based on Robot-Laparoscope Collaboration

Abstract

The present invention provides a system control method and medium based on robot-laparoscope cooperation, which relates to the technical field of laparoscope cooperation. The method includes: collecting working images; extracting sample information and instrument information from the set of working images, and determining influencing factors through the sample information and the instrument information; determining the predicted path and predicted speed of the instrument for the next time period through the sample information and the influencing factors; determining the initial adjustment path through the predicted path and the instrument spacing; obtaining the movement time of the instrument and the laparoscope, and determining the movement delay of the laparoscope; determining the time for the laparoscope to move to each point of the initial adjustment path through the predicted speed; intercepting the initial adjustment path within the movement delay to obtain the adjustment path; advancing the movement delay and moving the laparoscope along the adjustment path at the predicted speed. Planning the adjustment route based on the predicted path, considering the movement delay of the laparoscope, extracting and executing adjustment instructions, reducing the time difference, and reducing the collision probability.

Description

Technical Field

[0001] The present invention relates to the technical field of laparoscopic cooperation, and specifically relates to a system control method and medium based on robot-laparoscope cooperation. Background Art

[0002] When conducting laparoscopic cooperation instrument tests, it is necessary to collect the operation images of the instruments through the laparoscopic lens. When traditional laparoscopic cooperation instruments work, at least two or more operators are required to cooperate. One or more operators hold the instruments to complete the operation, and one operator holds the laparoscope to assist in lighting and imaging. If the operators do not cooperate well, there will be delays or the operation site cannot be seen. To solve this problem, a robot is introduced to hold the lens. 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 regardless of how the instrument is held. Since the robot needs to first detect and analyze the position of the instrument, then formulate the movement route of the laparoscope, and then control the movement of the laparoscope, the adjustment of the laparoscope position 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, resulting in collisions or conflicts with the laparoscope, interfering with the fine movements of the operation process and increasing the operation risk and uncertainty. Summary of the Invention

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

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

[0005] In the first aspect, a system control method based on robot-laparoscope cooperation is provided, including the following steps:

[0006] S100. Preset a working area, and collect images of the working area at a preset time to obtain a set of working images;

[0007] Extract sample information and the corresponding instrument information from the above set of working images, and determine the sample features affecting the movement path of the instrument through the above sample information and the corresponding instrument information to obtain an influencing factor;

[0008] S200. Predict the movement path and movement speed of the instrument in the next time period through the above sample information and influencing factor at the previous time to obtain a predicted path and a predicted speed;

[0009] S300. Determine the initial adjustment path of the laparoscope through the above 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 instrument features (such as three-dimensional coordinates of the instrument), and the dynamic changes of the sample features and instrument features are captured; based on the three-dimensional coordinates of the instrument at the previous moment and the next moment, the actual instrument movement path is calculated; by analyzing the relationship between the sample features and the instrument movement path, how different postures affect the instrument movement path is understood, helping the system identify which actions have a significant impact on the instrument movement.

[0023] Further, the specific steps to obtain the predicted path in S200 include:

[0024] S210. Create a feature relationship table, add the influence factor, influence value of the above instrument movement path, and sample feature data of this influence factor to the feature relationship table, and associate the instrument movement path, influence factor, influence value, and sample feature data of this influence factor;

[0025] S220. Obtain the above sample information at the previous time, and extract the sample features and sample feature data from this sample information;

[0026] S230. Match the above sample features with the influence factors in the feature relationship table. When the match is successful, match the above sample feature data with the sample feature data of the matched influence factor. When the match is successful, obtain the instrument movement path associated with this influence factor and sample feature data;

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

[0028] Establish an associated database or table (i.e., the feature relationship table) to record various factors affecting the instrument movement path, including the influence factor, its corresponding influence value, and sample feature data. Obtain the 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 the relevant sample features and sample feature data in the feature relationship table, initially filter out several instrument movement paths, traverse all sample features and their data, and filter out the instrument movement paths that meet all sample features and sample feature data to obtain the final predicted path.

[0029] Further, the specific steps to obtain the predicted speed in S200 include:

[0030] S250. Obtain the distance of the above-mentioned predicted path and the time taken for the instrument to move along the predicted path; wherein, the instrument characteristics of the above-mentioned instrument information further include the time taken for the instrument to move along the instrument movement path.

[0031] S260. Calculate the moving speed of the instrument based on the distance and time of the above-mentioned predicted path to obtain the predicted speed.

[0032] Further, 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 spacing between the above-mentioned predicted path and the initial adjustment path is greater than the lower limit spacing and less than the upper limit spacing.

[0035] Considering the actual operation, if the spacing between the instrument and the laparoscope is too large, it may lead to insufficient field of view captured by the laparoscope, affecting the operation; if the distance is too small, it may increase the risk of collision between the laparoscope and the instrument, improving the operation safety.

[0036] Further, obtain the distance between the above-mentioned laparoscope and the instrument in real time.

[0037] When the distance between the above-mentioned laparoscope and the instrument is equal to the lower limit spacing, generate a remote instruction to control the laparoscope to move away from the instrument.

[0038] When the distance between the above-mentioned laparoscope and the instrument is equal to the upper limit spacing, generate a close instruction to control the laparoscope to move closer to the instrument.

[0039] Provide real-time distance feedback, enabling the system to make a quick response according to the current situation, ensuring the safety of the operation process and the field of view range captured by the laparoscope.

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

[0041] Obtain the start time of the above-mentioned instrument movement and the start time of the laparoscope movement.

[0042] Determine the movement delay of the laparoscope based on the start time of the above-mentioned instrument movement and the start time of the laparoscope movement.

[0043] According to the calculated movement delay, formulate corresponding adjustment strategies to advance or postpone the movement of the laparoscope to ensure the synchronization between the two; by adjusting the delay, the synchronization of actions between the laparoscope and the instrument is ensured, reducing the waiting time and action delay, and thus reducing the risk of collision between the laparoscope and the instrument.

[0044] The second aspect provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the above-mentioned system control method is implemented.

[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 hand movement of the surgeon holding the knife. First, a working area is determined, and image data is collected within this area. It can identify the sample characteristics involved in the operation and the instruments used; by analyzing the working image set, key information such as sample characteristics and instrument positions can be extracted, providing a basis for subsequent prediction; based on the previously obtained information, the movement path and movement speed of the instrument in the next period of time are predicted, and historical data is used to speculate on the future actions of the instrument; according to the prediction results, not only can the movement route of the laparoscope be planned in advance, but also the delay duration in actual operation can be considered, thereby calculating the optimal adjustment time of the laparoscope, reducing the time difference between the laparoscope and the instrument, and avoiding collisions between the laparoscope and the moving instrument; the laparoscope moves at the predicted speed, enabling the laparoscope and the instrument to move synchronously, reducing the collision problems caused by different movement speeds and response times between 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 will briefly introduce the drawings required in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts. In the drawings:

[0048] Figure 1 is the main flow chart. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in combination with the embodiments and the drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and do not limit the present invention.

[0050] First Embodiment:

[0051] A system control method based on robot-laparoscope cooperation, combined with Figure 1 , includes the following steps:

[0052] S100. Preset a working area, and collect images of the working area at a preset time to obtain a set of working images;

[0053] Extract sample information from the above work image set and the corresponding instrument information. Determine the sample features affecting the movement path of the instrument based on the above sample information and the corresponding instrument information to obtain the influencing factors.

[0054] S200. Predict the movement path and movement speed of the instrument in the next time period based on the above sample information and influencing factors at the previous time to obtain the predicted path and predicted speed.

[0055] S300. Determine the initial adjustment path of the laparoscope based on the above predicted path and the preset instrument spacing.

[0056] S400. Obtain the movement time of the above instrument and laparoscope to determine the movement delay of the laparoscope.

[0057] S500. Determine the time for the laparoscope to move to each point of the initial adjustment path based on the above predicted speed.

[0058] Intercept the initial adjustment path within the above movement delay to obtain the adjustment path.

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

[0060] Considering that the movement path of the instrument is controlled by the hand movement of the operator, first determine a working area and collect image data within this area, which can identify the sample features and instrument features involved in the operation; by analyzing the work image set, key information such as sample features and instrument positions can be extracted, providing a basis for subsequent prediction; based on the previously obtained information, predict the movement path and movement speed of the instrument in the next period of time, and use historical data to infer future instrument actions; according to the prediction results, not only can the movement route of the laparoscope be planned in advance, but also the actual operation delay duration can be considered, so as to calculate the optimal adjustment time of the laparoscope, reduce the time difference between the laparoscope and the instrument, and avoid collisions between the laparoscope and the moving instrument.

[0061] A reference usage scenario is as follows. In a urological surgery experiment, carbon dioxide is injected into the abdominal cavity of a target (which can be a human model) through a pneumoperitoneum needle to inflate the abdomen of the target. Then, a laparoscope and instruments are inserted into the abdominal cavity to collect working images. The working images cover the laparoscope, the instruments, and the upper limbs of the operator. Images outside the abdominal cavity can be collected by external devices, and images inside the abdominal cavity can be collected by the laparoscope. The working images are composed of external images and internal images, and the splicing method can adopt existing image processing, which will not be elaborated in this invention. Sample features are extracted from the working images, and based on the extracted sample features and influencing factors, the movement path and movement speed of the instruments are predicted. Based on the predicted movement path of the instruments, the adjustment path of the laparoscope is planned in combination with the set instrument spacing. To reduce the problem of laparoscope response delay, the laparoscope is moved in advance at the predicted speed 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. Arrange the above-mentioned working image set in chronological order, extract sample information and instrument information from the working image of the previous time to obtain the previous sample information and the previous instrument information; extract instrument information from the working image of the next time to obtain the next instrument information. Among them, the sample information includes sample features and sample feature data. The sample features include arm key points, wrist key points, and finger key points. 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. The instrument feature data includes the three-dimensional coordinates of the instrument.

[0065] S120. Determine the instrument movement path through the above-mentioned previous instrument information and the next instrument information.

[0066] S130. Determine the relationship between the sample features in the previous sample information and the instrument movement path through the above-mentioned previous sample information and the instrument movement path; traverse the above-mentioned working image set to determine the relationship between the sample features and the instrument movement path.

[0067] S140. Establish an influencing factor model through the above-mentioned relationship between the sample features and the instrument movement path.

[0068] S150. Input the values of the above-mentioned sample features into the influencing factor model to obtain the influence value of the above-mentioned sample features on the instrument movement path.

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

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

[0071] A reference usage scenario is as follows. In a urological experiment, the first working image is collected at time t, the second working image is collected at time t + 1, and the third working image is collected at time t + 2. The first working image, the second working image, and the third working image form the working image set; when determining the influencing factors of the instrument, first extract the three - dimensional coordinates of the arm key points, the three - dimensional coordinates of the wrist key points, the three - dimensional coordinates of the finger key points, and the three - dimensional coordinates of the instrument from the first working image to obtain the first three - dimensional coordinates of the arm key points, the first three - dimensional coordinates of the wrist key points, the first three - dimensional coordinates of the finger key points, and the first three - dimensional coordinates of the instrument. Then extract the three - dimensional coordinates of the instrument from the second working image to obtain the second three - dimensional coordinates of the instrument; through the first three - dimensional coordinates of the instrument and the second three - dimensional coordinates of the instrument, the movement path of the instrument from time t to time t + 1 is obtained. This movement path is a vector and can be moved as a whole; by the three - dimensional coordinates of the arm key points, the three - dimensional coordinates of the wrist key points, and the three - dimensional coordinates of the finger key points, the relative relationships between the key point coordinates (such as the extension length of the arm, the rotation angle of the wrist, the bending angle of the finger, etc.) are determined, and thus the relative relationships between the corresponding key point coordinates when the instrument moves along this instrument movement path are obtained, avoiding the individual differences of the knife - holding personnel.

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

[0073] Third Embodiment:

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

[0075] S210. Create a feature relationship table, add the influencing factors, influence values of the above - mentioned instrument movement path, and the sample feature data of this influencing factor to the feature relationship table, associating the instrument movement path, influencing factors, influence values, and the sample feature data of this influencing factor.

[0076] S220. Obtain the above sample information at the previous time, and extract the sample features and sample feature data from this sample information;

[0077] S230. Match the above sample features with the influencing factors in the feature relationship table;

[0078] When the above sample features are successfully matched, match the above sample feature data with the sample feature data of the matched influencing factor;

[0079] When the above sample feature data is successfully matched, obtain the instrument movement path associated with this influencing factor and sample feature data;

[0080] When the above sample feature data fails to match, it indicates that this sample feature data does not meet the requirements for influencing the instrument movement path;

[0081] When the above sample features fail to match, it indicates that this sample feature is a non-influencing factor;

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

[0083] Establish an associated database or table (i.e., the feature relationship table) to record various factors affecting the instrument movement path, including influencing factors, their corresponding influence values, and sample feature data. Obtain the 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 the relevant sample features and sample feature data in the feature relationship table, initially filter out several instrument movement paths, traverse all sample features and their data, and filter out the instrument movement paths that meet all sample features and sample feature data to obtain the final predicted path.

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

[0085] S250. Obtain the distance of the above predicted path and the time taken for the instrument to move on the predicted path; wherein, the instrument characteristics of the above instrument information also include the time taken for the instrument to move on the instrument movement path;

[0086] S260. Calculate the movement speed of the instrument through the distance and time of the above predicted path to obtain the predicted speed.

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

[0088] , wherein, the three-dimensional coordinates of the first instrument , the three-dimensional coordinates of the second instrument , the three-dimensional coordinates of the third instrument , represents the predicted 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 spacing between the above-mentioned predicted path and the initial adjustment path is greater than the lower limit spacing and less than the upper limit spacing.

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

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

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

[0096] When the distance between the above-mentioned laparoscope and the instrument is equal to the upper limit spacing, a close instruction is generated to control the laparoscope to move closer to the instrument.

[0097] Provide real-time distance feedback, enabling the system to make a quick response according to the current situation, ensuring the safety of the operation process and the field of view range captured by the laparoscope.

[0098] Fifth Embodiment:

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

[0100] Obtain the start time of the movement of the above-mentioned instrument and the start time of the movement of the laparoscope;

[0101] Determine the movement delay of the laparoscope based on the start time of the movement of the above-mentioned instrument and the start time of the movement of the laparoscope.

[0102] According to the calculated movement delay, formulate corresponding adjustment strategies to advance or postpone the movement of the laparoscope to ensure the synchronization between the two; by adjusting the delay, ensure the action synchronization between the laparoscope and the instrument, reduce the waiting time and action delay, and thereby reduce the risk of collision between the laparoscope and the instrument.

[0103] Sixth Embodiment:

[0104] A computer-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the above-mentioned system control method is implemented.

[0105] The specific embodiments described above further elaborate on the purpose, technical solutions, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims

1. A system control method based on robot-laparoscopic collaboration, the system control method is used for laparoscopic collaborative instrument testing, the test target is a human model, and is 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 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, the specific steps 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 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; S120, determining a moving path of the device according to the previous device information and the next device information; 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 also include: 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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