Optical fiber wiring method and device based on fiber complexity prediction

Abstract

The application provides a fiber distribution method and device based on fiber complexity prediction, belongs to the technical field of fiber communication, and globally and uniformly numbers the two end connectors of all fiber connection loops in a fiber distribution robot, and constructs a connection seat arrangement state sequence according to the position sequence of each connection seat on a fiber cross connection coupling panel; real-time operation state data of the fiber distribution robot is acquired; before each optical path construction, the comprehensive complexity score is calculated through three dimensions of the number of bypasses, the moving distance of a mechanical hand and the loop plug-in wear factor, and the fiber connection loop with the lowest comprehensive complexity score is selected to perform the optical path construction operation. Thus, the overall bypass complexity is actively maintained at a low level in long-term operation, and the scheduling efficiency of the fiber distribution robot is improved.

Description

Technical Field

[0001] This application belongs to the field of optical fiber communication technology, and specifically relates to an optical fiber distribution method and apparatus based on fiber migration complexity prediction. Background Technology

[0002] With the continuous and rapid development of broadband internet, 5G mobile communication, cloud computing, and big data services, the scale of optical fiber networks has expanded dramatically. The number of optical fiber cores and the demand for optical path connections in backbone transmission networks, metropolitan area networks, and data center interconnection networks are all growing exponentially. Taking large data centers as an example, the number of optical fiber interfaces in a single site can reach tens of thousands or even hundreds of thousands of ports. The high frequency and large amount of changes in optical path connection scheduling operations place extremely high demands on the real-time performance, accuracy, and reliability of cabling operations.

[0003] In traditional fiber optic network operation and maintenance, the insertion and removal of fiber optic patch cords relies entirely on manual operation. Manual patching presents several significant problems: first, it is inefficient, as completing a large number of patch cord operations at high-density patch panels is time-consuming; second, it has a high error rate, with manual operations prone to mis-insertion and omissions, leading to service interruptions; third, it cannot be remotely operated, requiring maintenance personnel to be physically present in the equipment room, and does not support 24 / 7 unattended operation; and fourth, in high-density port environments, fiber optic management is chaotic, making traceability and auditing difficult. These problems severely restrict the improvement of intelligent and automated operation and maintenance management of fiber optic networks.

[0004] A fiber optic distribution robot is an automated optical cross-connect system that uses a built-in robotic arm to automatically perform fiber optic patch cord insertion and removal operations, enabling remote dynamic scheduling of fiber optic links instead of manual labor. Inside the robot, a fiber optic loopback unit (consisting of a fiber optic connector and a loopback fiber) is inserted into the connector on the fiber optic cross-connect coupling panel to form an optical loopback. The robotic arm grasps one end of a specific loopback unit and inserts it into the target connector, thus establishing an optical path between any two ports.

[0005] To prevent fiber optic loopback connections from tangling under the influence of a robotic arm, existing technologies employ anti-tangling fiber-moving algorithms. These algorithms ensure that tangling does not occur during a single operation. However, as the fiber optic distribution robot's operating time increases, the numbering of the fiber optic connectors plugged into the connectors deviates from the initial natural order (1, 2, ..., N), forming a random arrangement. In this random arrangement, the robotic arm needs to frequently "detour" the connectors along the path each time it performs a new optical path establishment operation, based on directional rules. The more detours, the more complex the robotic arm's movement path, the longer the operation time, and the lower the overall cabling efficiency. Summary of the Invention

[0006] In view of this, the purpose of this application is to provide a fiber optic distribution method and apparatus based on fiber movement complexity prediction, which can actively maintain the orderly arrangement of optical fibers, reduce the number of detours, shorten the operation time, and improve the scheduling efficiency and reliability of fiber optic distribution robots.

[0007] In a first aspect, this application provides an optical fiber distribution method based on fiber migration complexity prediction, the method comprising the following steps: All the two ends of the fiber optic connection loopback devices in the fiber optic distribution robot are globally and uniformly numbered, and the connection arrangement state sequence is constructed according to the position order of each connector on the fiber optic cross-connection coupling panel. The system acquires real-time operational status data of the fiber optic cabling robot. This status data includes the occupancy status of the fiber optic connection loopback device, the position of the connected connectors and the cumulative number of insertions and removals, as well as the current position of the robot arm. Based on the received optical path connection request, a set of candidate loopers in an idle state is selected from all optical fiber connection loopers. For each candidate looper in the set of candidate loopers, the corresponding comprehensive complexity score is calculated by combining the number of detours after operation, the distance the robot moves, and the looper insertion and removal wear factor. The optical fiber connection loopback unit with the lowest overall complexity score is selected to perform the optical path establishment operation, and the operating status data of the optical fiber distribution robot is updated after the optical path is established.

[0008] In some embodiments, N connectors for plugging N / 2 fiber optic loopback connectors are arranged on the fiber optic cross-connect coupling panel. The connectors at both ends of the k-th fiber optic loopback connector are numbered as 2k-1 and 2k, respectively, where k = 1, 2, ..., N / 2. The constructed connector arrangement state sequence is denoted as S=[S[1], S[2],…,S[N]], where S[i] represents the connector number inserted on the connector at position i, i=1,2,…,N; and in the initial state, the connector arrangement state sequence is set to a naturally increasing sequence. =[1,2,…,N], all fiber optic connection loopbackers are marked as idle.

[0009] In some embodiments, the overall complexity score is calculated using the following formula:

[0010] in, The sequence of connector arrangement states after using fiber optic connection loopback unit k. The normalized value of the number of detours, This is the normalized value of the total distance traveled by the robotic arm to complete this operation. Let K be the insertion and removal wear factor for the fiber optic connection loopback unit k. , , For the corresponding weight coefficients and .

[0011] In some embodiments, it is obtained as follows : Based on the order in which the connectors at both ends of the fiber optic loopback device are moved, and the sequential or cross pairing of the connectors at both ends of the fiber optic loopback device with the two target connectors, four operation schemes are formed. For each operation plan, the total travel distance for the four segments—moving the robot to the connector, moving with the connector, picking up another connector, and moving with the connector again—is calculated. The minimum value is then normalized to obtain the total travel distance. .

[0012] In some embodiments, the following formula is used for calculation. :

[0013] in, For the connection seat arrangement state sequence The number of times the relationship between the size of adjacent connector numbers is reversed; connectors at both ends of the same fiber optic loopback unit that are adjacent are not included in the count. For two operational schemes—sequential pairing and cross-pairing—between the connectors at both ends of the fiber optic loopback unit and the two target connectors, simulated insertion was performed to generate new connector arrangement sequences for each scheme. and And according to the above formula, respectively, we obtain and .

[0014] In some embodiments, the following formula is used for calculation. :

[0015] Wherein, cnt_plug_loop[k] is the total number of times the connectors at both ends of the fiber optic loopback unit k are individually plugged and unplugged, obtained by adding cnt_plug[2k-1] and cnt_plug[2k].

[0016] In some embodiments, if multiple fiber optic loopbackers achieve the lowest overall complexity score in parallel, the distances from the two ends of each fiber optic loopbacker to the target connector are calculated, and the smaller single-end distance is taken as the distance basis for that fiber optic loopbacker. The fiber optic loopbacker with the smallest distance basis is selected to perform optical path establishment.

[0017] Secondly, this application also provides an optical fiber distribution device based on fiber migration complexity prediction, the device comprising: The unified numbering module is used to globally and uniformly number the two ends of all fiber optic connection loopback devices in the fiber optic distribution robot, and to construct a connection arrangement sequence based on the position order of each connection on the fiber optic cross-connection coupling panel. The data maintenance module is used to acquire the real-time operating status data of the fiber optic cabling robot. The status data includes the occupancy status of the fiber optic connection loopback device, the position of the connected connector and the cumulative number of insertions and removals, as well as the current position of the robot arm. The complexity prediction module is used to filter out a set of candidate loopers that are in an idle state from all optical fiber connection loopers based on the received optical path connection request, and calculate the corresponding comprehensive complexity score for each candidate looper in the candidate looper set by comprehensively considering the number of detours after operation, the robot arm movement distance, and the looper insertion and removal wear factor. The execution module is used to select the fiber optic connection loopback unit with the lowest overall complexity score to perform the optical path establishment operation, and update the operating status data of the fiber optic distribution robot after the optical path is established.

[0018] Thirdly, this application also provides an electronic device, including: a processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the memory via the bus, and when the machine-readable instructions are executed by the processor, the steps of the fiber optic cabling method based on fiber migration complexity prediction described in any one of the first aspects are executed.

[0019] Fourthly, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps of the fiber optic cabling method based on fiber displacement complexity prediction as described in any one of the first aspects.

[0020] The fiber optic cabling method and apparatus described in this application, based on fiber movement complexity prediction, calculates a comprehensive complexity score before each optical path construction based on three dimensions: the number of detours, the robot's movement distance, and the wear factor of the loopback connector insertion / removal. The optical path establishment operation is then performed using the fiber optic connection loopback connector with the lowest comprehensive complexity score. This proactively maintains a low overall detour complexity during long-term operation, improving the scheduling efficiency of the fiber optic cabling robot.

[0021] In other embodiments, this application proposes an optimal movement path model with four schemes and four segments, taking into account the physical characteristics of the fiber optic connection loopback device having two independent connectors. This model effectively reduces the movement distance of the robot arm in a single operation and accelerates the establishment speed of the optical path in a single operation. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart of the fiber optic cabling method based on fiber migration complexity prediction as described in an embodiment of this application is shown; Figure 2 A schematic diagram of the internal structure of the fiber optic cabling robot according to an embodiment of this application is shown; Figure 3 A schematic diagram of the internal logic structure of the fiber optic cabling robot according to an embodiment of this application is shown; Figure 4 A schematic diagram of the fiber optic distribution device based on fiber migration complexity prediction according to an embodiment of this application is shown; Figure 5 A schematic diagram of the structure of the electronic device described in an embodiment of this application is shown. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0025] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0026] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0027] In view of the technical problems raised in the background art, this application provides an optical fiber distribution method and device based on fiber movement complexity prediction, which can actively maintain the orderly arrangement of optical fibers, reduce the number of detours, shorten the operation time, and improve the scheduling efficiency and reliability of optical fiber distribution robots.

[0028] See the instruction manual appendix Figure 1 This application provides a fiber optic cabling method based on fiber migration complexity prediction, comprising the following steps: S1. Give a global unified number to the two ends of all fiber optic connection loopers in the fiber optic distribution robot, and construct a connection arrangement state sequence according to the position order of each connection on the fiber optic cross-connection coupling panel. S2. Real-time acquisition of the operating status data of the fiber optic cabling robot; the status data includes the occupancy status of the fiber optic connection loopback device, the position of the connected connector and the cumulative number of insertions and removals, and the current position of the robot arm; S3. Based on the received optical path connection request, select a set of candidate loopers that are in an idle state from all optical fiber connection loopers, and for each candidate looper in the candidate looper set, calculate the corresponding comprehensive complexity score by combining the number of detours after operation, the robot arm movement distance, and the looper insertion and removal wear factor. S4. Select the fiber optic connection loopback unit with the lowest overall complexity score to perform the optical path establishment operation, and update the operating status data of the fiber optic distribution robot after the optical path is established.

[0029] To clearly understand the technical solutions of the embodiments of the present invention, an exemplary description of the fiber optic distribution robot is provided first. See the appendix to the specification. Figure 2 The fiber optic distribution robot mainly comprises a fiber optic cross-connect coupling panel, a fiber optic connection loopback unit, a fiber optic distribution robot equipment panel, and a robotic arm. The fiber optic cross-connect coupling panel is the core cross-connection layer of the entire distribution system. Fiber optic connectors are arranged on the coupling panel, providing standardized fiber optic adapter interfaces for connecting internal fiber optic connection loopback units and external access fiber optic cable cores and service equipment connected via the equipment panel. The fiber optic connection loopback unit is a key component for the robot's automation capabilities, consisting of one optical fiber and two fiber optic connectors. The fiber optic connectors can be freely grasped, moved, and placed at designated connector positions by the robotic arm, enabling dynamic cross-connections between any ports. The fiber optic connectors are the end connectors of the fiber optic connection loopback unit, specifically designed for robotic arm grasping operations. The fiber optic distribution robot equipment panel is the fixed-end equipment interface layer inside the robot, used to connect external fiber optic cable cores and service equipment.

[0030] Due to the relatively large number of optical fibers connected by the fiber loop-back connector, when the manipulator accurately grasps the optical fiber connector of a certain fiber loop-back device and establishes or removes the optical path between the specified connectors, the manipulator moves with the optical fiber and must follow certain rules, otherwise fiber entanglement will occur. See the attached Figure 3 The rules for the optical fiber distribution robot to use the manipulator for optical path switching are as follows: (1) Define the optical fiber connectors to be numbered from 1 to N; (2) When the manipulator moves with the optical fiber (for example, the manipulator carries the optical fiber connector numbered m), compare the number of the optical fiber connector on the next connector (for example, numbered n). If m < n, the manipulator moves the optical fiber connector m of the optical fiber from the left side of the connector corresponding to the optical fiber connector n; if m > n, the manipulator moves the optical fiber connector m from the right side of the connector corresponding to the optical fiber connector n; (3) When the manipulator moves with the optical fiber in the reverse direction, this rule is also followed; (4) When the manipulator moves with the optical fiber from connector i to connector i + 1, if the passing direction (left side / right side) required by two operations according to the direction rule is reversed, it is called a single loop. The increase in the number of loops will lead to a decrease in the fiber transfer efficiency of the optical fiber distribution robot.

[0031] Among them, step S1 mainly establishes a unique and ordered numbering system to accurately identify each optical fiber connector and provide a data basis for subsequent complexity calculation. Specifically, inside the optical fiber distribution robot, each optical fiber connection loop-back device consists of an optical fiber connecting two optical fiber connectors. The two ends of the connector are respectively called the A end and the B end. In this application, the two ends of all optical fiber connection loop-back devices in the optical fiber distribution robot are globally numbered uniformly. There are N connectors arranged on the optical fiber cross-connection and coupling panel for plugging in the two ends of N / 2 optical fiber connection loop-back devices. The numbers of the two ends of the kth optical fiber connection loop-back device are respectively recorded as 2k - 1 and 2k, where k = 1, 2,..., N / 2. And a connector arrangement state sequence S = [S[1], S[2],..., S[N]] is constructed according to the connector position sequence. Among them, S[i] represents the number of the connector plugged in at the connector position i, where i = 1, 2,..., N; and in the initial state, the connector arrangement state sequence is set to the natural increasing sequence = [1, 2,..., N], and all optical fiber connection loop-back devices are marked as idle states to ensure that the initial arrangement is a natural ordered sequence and reduce entanglement and loops at the source.

[0032] Step S2 mainly involves acquiring the real-time operating status data of the fiber optic distribution robot to provide real-time input for subsequent candidate selection, path calculation, wear assessment, and detour prediction. Specifically, the status data includes a looper status table and the current position of the robot arm, pos_cur_gripper. The looper status table includes the occupancy status (idle / occupied) of each fiber optic connection looper k, the position of the connected connector, and the cumulative number of plug-in / plug-out operations. The current position of end A is pos_cur_socket[2k-1], and the current position of end B is pos_cur_socket[2k]. The cumulative number of plug-in / plug-out operations at end A is cnt_plug[2k-1], and the cumulative number of plug-in / plug-out operations at end B is cnt_plug[2k].

[0033] Steps S3 and S4 mainly involve constructing a three-dimensional weighted comprehensive complexity scoring model to predict and select the idle looper with the lowest score to perform operations before each optical path is established, thereby proactively maintaining a low overall circumvention complexity and improving the scheduling efficiency of the fiber optic distribution robot.

[0034] Specifically, for new connection requests, the loopback status table is scanned, and loopbacks currently in an idle state are added to the candidate set LOOPSET. Loopbacks with established optical paths that are currently occupied by services are not selected for the candidate set LOOPSET. For candidate loopback k (A-end number 2k-1, current position pos_cur_socket[2k-1]; B-end number 2k, current position pos_cur_socket[2k]), the complexity calculation considers three dimensions: the normalized value of the number of detours after using candidate loopback k. Normalized value of the total moving distance of the robotic arm in this operation Looper insertion / removal factor .

[0035] The weighted calculation yields the overall complexity score. for:

[0036] in, The simulation uses a loop closure k to determine the normalized number of hops required to reach the final state S' after the robot establishes a connection. For a given permutation state S', all adjacent connection pairs (i, i+1) (i = 1, ..., N-1) in the sequence are traversed, and the total number of hops required according to the direction rules is calculated. T(S') represents the number of times the order of the relative sizes (ascending / descending) of adjacent elements in sequence S' changes, i.e., the number of extreme points in the sequence. A smaller T(S') indicates a more monotonic sequence, meaning a more ordered permutation state and fewer hops required for subsequent operations; a larger T(S') indicates more frequent sequence fluctuations and more hops required for subsequent operations.

[0037] This is the normalized value of the total distance traveled by the robotic arm to complete this fiber optic connection operation. The total distance traveled by the robotic arm mainly includes four distances: Idle distance 1, from the current position of the robotic arm pos_cur_gripper to the connector position at end A or B of the fiber optic connection loopback unit (the preceding connector position); Movement with fiber optic connector 1, the distance from the preceding connector to the first target connector; Idle distance 2, from the first target connector to the other connector position of the fiber optic connection loopback unit (the following connector position); Movement with fiber optic connector 2, the distance from the following connector to the second target connector. The total distance traveled by the robotic arm is calculated to obtain the Span. Normalized to:

[0038] The wear level of looper k among all loopers is represented by the total cumulative number of insertions and removals of the connectors at both ends of looper k, calculated as cnt_plug_loop[k] = cnt_plug[2k-1] + cnt_plug[2k], and then normalized. In other words, this application maintains the insertion and removal counts for the A and B ends of each looper separately, and uses the sum of the two ends as the total wear amount in the score. It counts the ends of connectors that actually underwent physical movement during the operation, accurately reflecting the actual wear level of each connector. When a connector at a certain end is already at the target position and does not need to be moved, the wear amount at that end does not increase, further achieving refined wear equalization.

[0039] The weighting coefficients satisfy: , All values ​​are non-negative real numbers and can be flexibly configured according to application scenarios. The comprehensive complexity score considers three dimensions simultaneously: subsequent detour complexity, current movement distance, and loopback lifetime balancing. Through configurable weighting coefficients α, β, and γ, users can flexibly adjust strategies based on their different priorities regarding long-term efficiency, single-operation speed, and lifetime. For throughput-sensitive data center scenarios, the weight of α can be increased to prioritize improving the arrangement state; for scenarios with high real-time requirements, the weight of β can be increased to prioritize shortening the single-operation time; and for scenarios with high equipment reliability requirements, the weight of γ can be increased to achieve load balancing and extend equipment life. This three-dimensional decoupled modeling and weighted fusion design scheme has good versatility and scalability.

[0040] Among them, in calculating the overall complexity score First calculate , then calculate or .

[0041] For looper k in the candidate looper set, when establishing a connection, the connectors at both ends of A and B need to be moved to the target connectors M and N respectively, that is, the A and B ends are moved to posM or posN respectively. After the robot arm operates, the changes in the robot arm position and the sequence of the connector arrangement state S need to be considered from two dimensions: (1) which connector is moved first; (2) the pairing method between the connector and the target (whether the A end is inserted into the connector posM or posN). After the first connector is moved and the connection is completed, the robot arm stays at the first target connector, and the S sequence has also been updated to the intermediate state. The robotic arm then moves from the first target to retrieve the rear connector, and then to the second target. Therefore, the starting point of the idle journey of the rear connector is the connector seat of the first target, not the initial position of the robotic arm.

[0042] The order in which the robotic arm moves the connector and the pairing method between the connector and the target both affect the total moving distance, resulting in four possible operation schemes.

[0043] Option 1: A moves first, A→posM, B→posN. The total movement distance of the robotic arm includes the following four segments:

[0044] Option 2: A goes first, A → posN, B → posM

[0045] Option 3: B goes first, B → posN, A → posM

[0046] Option 4: B goes first, B → posM, A → posN

[0047] After normalization calculation, we get , , , .

[0048] For the four schemes mentioned above, Schemes 1 and 3 use the same fiber optic connector-connector pairing scheme [A→posM, B→posN], denoted as P1; Schemes 2 and 4 also use the same pairing scheme [A→posN, B→posM], denoted as P2. The difference between the two schemes with the same pairing scheme (Schemes 1 and 3, Schemes 2 and 4) is whether end A or end B is moved first. Different pairing schemes P1 and P2 result in different connector arrangement sequences S completed by the robotic arm. Therefore, the calculation of the subsequent number of passes T(S') needs to be performed separately for P1 and P2.

[0049] In calculation When it comes to pairing schemes P1 and P2, simulate insertion and generate new permutation states respectively and , calculate and . Taking as an example, for the loopback device k in the set of candidate loopback devices, insert the A end of the loopback device k into posM and the B end into posN to generate a new permutation state after the simulated operation

[0050] Let the current connection block permutation state be , and the calculation steps of the number of detours are as follows Initialize T = 0 and set the direction variable dir_prev = NULL From i = 1 to N - 1, successively take adjacent connection block pairs (i, i + 1) If S[i] and S[i + 1] belong to the A end and B end of the same loopback device (the two connector numbers are adjacent in odd and even, and even - odd = 1, that is, it satisfies: min(S[i], S[i + 1]) is odd, max(S[i], S[i + 1]) is even, and max(S[i], S[i + 1]) - min(S[i], S[i + 1]) = 1), then the optical fiber between these two connectors is the loopback optical fiber of this loopback device itself, there is no risk of winding across loopback devices, it does not participate in the detour statistics, keep dir_prev unchanged, and skip this pair Otherwise, calculate the direction dir_curr from connection block i to i + 1: if S[i] < S[i + 1], then dir_curr = LEFT (the manipulator goes on the left side), if S[i] > S[i + 1], then dir_curr = RIGHT (the manipulator goes on the right side) If dir_prev ≠ NULL and dir_curr ≠ dir_prev, then T = T + 1 (a detour occurs and the manipulator needs to change the passing direction) Set dir_prev = dir_curr and continue to process the next pair After the traversal is completed, return .

[0051] According to the above method, obtain and , and perform normalization

[0052]

[0053] Obtain and . The smaller the obtained value, the more orderly the permutation after the operation and the fewer subsequent detours

[0054] Calculate the complexity scores of the four schemes, and take the minimum value as the complexity score of the k-looper.

[0055] Option 1:

[0056] Option 2:

[0057] Option 3:

[0058] Option 4:

[0059] k-looper complexity score:

[0060] Then, the complexity score of all loopers in the candidate looper set is calculated, and the minimum complexity score is selected. The corresponding loopback unit Ks. Among them, if there are multiple loopback units with the same C(k) value, the fiber optic connector closest to posM is selected first (i.e., min(|pos_cur_socket[2k-1]-posM|, |pos_cur_socket[2k]-posM|)).

[0061] The connection command and optimal operation plan of Ks (which connector the robot moves first and inserts into which position, i.e., the final selection plan) are sent to the robot fiber jumper control unit to perform the optical path establishment operation: the robot first grabs the preceding connector and moves it to the first target connector, and then grabs the following connector and moves it to the second target connector; after the operation is completed, the following status updates are performed: S[posM] and S[posN] are updated to the connector number of the final pairing plan selected by the loopback unit Ks; the connector positions of the A and B ends of the loopback unit Ks are updated to pos_cur_socket[2k-1] / pos_cur_socket[2k]; for the connectors that actually moved this time: if the end actually moved, the corresponding cnt_A or cnt_B is incremented by 1 (if an end is already in the target position and has not moved, it is not counted); Ks is marked as occupied; the connector number where pos_cur_gripper is located is updated, which is usually the connector number of the last one inserted this time, or it can be the initial position of the robot.

[0062] As can be seen, the fiber optic cabling method based on fiber movement complexity prediction provided in this application constructs a standardized sequence of connector numbers and connector arrangement states using a fiber optic cabling robot. Relying on real-time, multi-dimensional system status data, it filters a set of idle candidate loopbackers. Multiple operation schemes are formed through connector movement sequence and connector pairing methods. A comprehensive complexity score is calculated by integrating the number of detours, the robot's movement distance, and the insertion / removal wear factor. A distance-based selection rule is set for cases with the same score to select the optimal loopbacker to complete optical path establishment and system status update. This effectively optimizes the global operation of fiber optic cabling, accurately predicts fiber movement complexity, shortens the robot's movement distance, balances the insertion / removal wear of each loopbacker, reduces the problem of disordered fiber entanglement, significantly improves optical path scheduling efficiency and automated cabling stability, extends the overall lifespan of the equipment, and adapts to the long-term, efficient operation and maintenance needs of large-scale fiber optic networks.

[0063] Based on the same inventive concept, this application also provides an optical fiber distribution device based on fiber movement complexity prediction. Since the principle of the device in this application is similar to the optical fiber distribution method based on fiber movement complexity prediction described above in this application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0064] As per the instruction manual Figure 4 As shown in the figure, this application embodiment also provides an optical fiber distribution device based on fiber migration complexity prediction, the device comprising: The unified numbering module 401 is used to globally and uniformly number the two ends of all fiber optic connection loopers in the fiber optic distribution robot, and to construct a connection arrangement state sequence based on the position order of each connection on the fiber optic cross-connection coupling panel. The data maintenance module 402 is used to acquire the real-time operating status data of the fiber optic cabling robot; the status data includes the occupancy status of the fiber optic connection loopback device, the position of the connected connector and the cumulative number of insertions and removals, and the current position of the robot arm; The complexity prediction module 403 is used to filter out a set of candidate loopers that are in an idle state from all optical fiber connection loopers according to the received optical path connection request, and calculate the corresponding comprehensive complexity score for each candidate looper in the candidate looper set by comprehensively considering the number of detours after operation, the robot arm movement distance and the looper insertion and removal wear factor. The execution module 404 is used to select the fiber optic connection loopback device with the lowest comprehensive complexity score to perform the optical path establishment operation, and update the operating status data of the fiber optic distribution robot after the optical path is established.

[0065] The fiber optic distribution device based on fiber movement complexity prediction described in this application calculates a comprehensive complexity score based on three dimensions—number of detours, robot arm movement distance, and looper insertion / removal wear factor—before each optical path construction. It then selects the fiber optic connection looper with the lowest comprehensive complexity score to perform the optical path establishment operation. This proactively maintains a low overall detour complexity during long-term operation, improving the scheduling efficiency of the fiber optic distribution robot.

[0066] Based on the same concept of the present invention, as shown in the appendix to the specification. Figure 5 As shown in the embodiment of this application, an electronic device 500 is provided. The electronic device 500 includes: at least one processor 501, at least one network interface 504 or other user interface 503, a memory 505, and at least one communication bus 502. The communication bus 502 is used to enable communication between these components. The electronic device 500 may optionally include a user interface 503, including a display (e.g., touchscreen, LCD, CRT, holographic imaging, or projector), a keyboard, or a clicking device (e.g., mouse, trackball, touchpad, or touchscreen).

[0067] Memory 505 may include read-only memory and random access memory, and provides instructions and data to processor 501. A portion of memory 505 may also include non-volatile random access memory (NVRAM).

[0068] In some implementations, memory 505 stores executable modules or data structures, or subsets thereof, or extended sets thereof: The 5051 operating system contains various system programs used to implement various basic business functions and handle hardware-based tasks. Application module 5052 contains various applications, such as launchers, media players, and browsers, to implement various application functions.

[0069] In this embodiment of the application, the processor 501 executes steps such as those of an optical fiber distribution method based on fiber migration complexity prediction by calling a program or instruction stored in the memory 505.

[0070] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, performs steps such as those in a fiber optic cabling method based on fiber displacement complexity prediction.

[0071] Specifically, the storage medium can be a general-purpose storage medium, such as a portable disk or hard disk. When the computer program on the storage medium is run, it can actively maintain the orderly arrangement of optical fibers, reduce the number of detours, shorten the operation time, and improve the scheduling efficiency and reliability of the optical fiber distribution robot.

[0072] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the mutual coupling or direct coupling or communication connection shown or discussed may be through some communication interface, and the indirect coupling or communication connection of the apparatus or units may be electrical, mechanical, or other forms.

[0073] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0074] In addition, the functional units in the embodiments provided in this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0075] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0076] Finally, it should be noted that the above embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A fiber optic cabling method based on fiber transfer complexity prediction, characterized in that, The method includes the following steps: All the two ends of the fiber optic connection loopback devices in the fiber optic distribution robot are globally and uniformly numbered, and the connection arrangement state sequence is constructed according to the position order of each connector on the fiber optic cross-connection coupling panel. The system acquires real-time operational status data of the fiber optic cabling robot. This status data includes the occupancy status of the fiber optic connection loopback device, the position of the connected connectors and the cumulative number of insertions and removals, as well as the current position of the robot arm. Based on the received optical path connection request, a set of candidate loopers in an idle state is selected from all optical fiber connection loopers. For each candidate looper in the set of candidate loopers, the corresponding comprehensive complexity score is calculated by combining the number of detours after operation, the distance the robot moves, and the looper insertion and removal wear factor. The optical fiber connection loopback unit with the lowest overall complexity score is selected to perform the optical path establishment operation, and the operating status data of the optical fiber distribution robot is updated after the optical path is established.

2. The fiber optic cabling method based on fiber movement complexity prediction according to claim 1, characterized in that, in, N connectors are arranged on the fiber optic cross-connect coupling panel for plugging the connectors at both ends of N / 2 fiber optic connection loopers. The connectors at both ends of the k-th fiber optic connection looper are numbered as 2k-1 and 2k, respectively, where k=1,2,…,N / 2. The constructed connector arrangement state sequence is denoted as S=[S[1], S[2],…,S[N]], where S[i] represents the connector number inserted on the connector at position i, i=1,2,…,N; and in the initial state, the connector arrangement state sequence is set to a naturally increasing sequence. =[1,2,…,N], all fiber optic connection loopbackers are marked as idle.

3. The fiber optic cabling method based on fiber movement complexity prediction according to claim 2, characterized in that, The overall complexity score is calculated using the following formula: in, The sequence of connector arrangement states after using fiber optic connection loopback unit k. The normalized value of the number of detours, This is the normalized value of the total distance traveled by the robotic arm to complete this operation. Let K be the insertion and removal wear factor for the fiber optic connection loopback unit k. , , For the corresponding weight coefficients and .

4. The fiber optic cabling method based on fiber movement complexity prediction according to claim 3, characterized in that, Obtained in the following way : Based on the order in which the connectors at both ends of the fiber optic loopback device are moved, and the sequential or cross pairing of the connectors at both ends of the fiber optic loopback device with the two target connectors, four operation schemes are formed. For each operation plan, the total travel distance for the four segments—moving the robot to the connector, moving with the connector, picking up another connector, and moving with the connector again—is calculated. The minimum value is then normalized to obtain the total travel distance. .

5. The fiber optic cabling method based on fiber movement complexity prediction according to claim 4, characterized in that, Calculated using the following formula : in, For the connection seat arrangement state sequence The number of times the relationship between the size of adjacent connector numbers is reversed; connectors at both ends of the same fiber optic loopback unit that are adjacent are not included in the count. For two operational schemes—sequential pairing and cross-pairing—between the connectors at both ends of the fiber optic loopback unit and the two target connectors, simulated insertion was performed to generate new connector arrangement sequences for each scheme. and And according to the above formula, respectively, we obtain and .

6. The fiber optic cabling method based on fiber movement complexity prediction according to claim 4, characterized in that, Calculated using the following formula : Wherein, cnt_plug_loop[k] is the total number of times the connectors at both ends of the fiber optic loopback unit k are individually plugged and unplugged, obtained by adding cnt_plug[2k-1] and cnt_plug[2k].

7. The fiber optic cabling method based on fiber movement complexity prediction according to claim 1, characterized in that, in, If multiple fiber optic loopbackers achieve the lowest overall complexity score, calculate the distance from each end connector of each fiber optic loopbacker to the target connector, and take the smaller single-end distance as the distance criterion for that fiber optic loopbacker. Select the fiber optic loopbacker with the smallest distance criterion to perform optical path establishment.

8. A fiber optic distribution device based on fiber transfer complexity prediction, characterized in that, The device includes: The unified numbering module is used to globally and uniformly number the two ends of all fiber optic connection loopback devices in the fiber optic distribution robot, and to construct a connection arrangement sequence based on the position order of each connection on the fiber optic cross-connection coupling panel. The data maintenance module is used to acquire the real-time operating status data of the fiber optic cabling robot. The status data includes the occupancy status of the fiber optic connection loopback device, the position of the connected connector and the cumulative number of insertions and removals, as well as the current position of the robot arm. The complexity prediction module is used to filter out a set of candidate loopers that are in an idle state from all optical fiber connection loopers based on the received optical path connection request, and calculate the corresponding comprehensive complexity score for each candidate looper in the candidate looper set by comprehensively considering the number of detours after operation, the robot arm movement distance, and the looper insertion and removal wear factor. The execution module is used to select the fiber optic connection loopback unit with the lowest overall complexity score to perform the optical path establishment operation, and update the operating status data of the fiber optic distribution robot after the optical path is established.

9. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, they perform the steps of the fiber optic cabling method based on fiber migration complexity prediction as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of an optical fiber distribution method based on fiber migration complexity prediction as described in any one of claims 1 to 7.

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