Modular access method and system for a biological sample storage system

Abstract

The application relates to the technical field of biological sample storage and access, and discloses a modular access method and system of a biological sample storage system, which comprises the following steps: obtaining a sample access instruction, determining a target storage cabin from a plurality of storage cabins according to the sample access instruction, determining an operation cabin that is connected with the target storage cabin, determining a docking mode and a moving path according to the state of the operation cabin, the target storage cabin, a passing unit and a docking position, when the passing unit and the target docking position corresponding to the moving path are in an available state, controlling the operation cabin or the target storage cabin to move to the target docking position and complete docking, carrying out tube picking, storage or extraction through the operation cabin, and updating state information. Through the cooperative processing of a module state table, a candidate docking combination, passing resource reservation and docking resource reservation, the application completes resource availability judgment before moving, triggers an avoidance shunting process when resources are not satisfied, reduces track interference and concurrent occupation of docking positions, and improves the continuity of sample access tasks.

Description

Technical Field

[0001] This invention relates to the field of biological sample storage technology, specifically to a modular storage method and system for a biological sample storage system. Background Technology

[0002] With the development of biomedical technology, the demand for large-scale storage and high-frequency retrieval of biological samples is increasing. To improve access efficiency, biobanks are gradually introducing modular automated access systems. These systems typically include multiple movable storage tanks, operating chambers, and mobile support mechanisms, which need to work together within limited space to complete complex sample transfer and docking tasks.

[0003] However, existing automated access methods have shortcomings in multi-entity collaborative control and operation execution. In the initial stages of task scheduling, the system typically handles the right-of-way for spatial paths and the allocation of target docking interfaces independently. This can lead to trajectory interference between physical entities during movement, or passive waiting upon reaching the target location due to concurrent occupation of docking positions. When multiple tasks cause channel congestion, existing systems lack proactive diversion and buffering mechanisms. Furthermore, when a cyclical blocking state forms between multiple physical entities, it is difficult to effectively identify and break closed resource dependencies, easily causing regional interlocking and stagnation. In addition, when an entity arrives at the docking position to perform access operations, existing verification methods are relatively simple, lacking comprehensive confirmation of position, attitude, and sealing status. Moreover, there is a lack of real-time closed-loop monitoring of the operating environment and equipment load during operation. In the event of mechanical misalignment, jamming, or abnormal temperature, emergency stop protection actions cannot be triggered in a timely manner, increasing the risk of equipment failure and sample damage.

[0004] In summary, traditional control logic has limitations in dealing with resource allocation conflicts, congestion and deadlock states, and abnormal interference during access operations in complex spaces. Therefore, providing a modular access method for biological sample storage systems that enables joint reservation of space and terminal resources, has the ability to actively divert congestion and resolve deadlocks, and supports multi-dimensional verification and monitoring throughout the entire operation is a problem that needs to be solved in this field. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a modular access method and system for biological sample storage, which solves the problems of trajectory interference and concurrent occupation conflicts caused by independent allocation of paths and interfaces in existing access processes, the system stagnation caused by the lack of active diversion and interlock release mechanisms when multiple tasks are running concurrently, and the risks of device collision and sample damage caused by single interface verification and lack of real-time anomaly monitoring.

[0006] To address the above problems, the present invention provides the following technical solution: The first aspect of this invention provides a modular access method for a biological sample storage system, employing the following technical solution: A modular access method for a biological sample storage system, the biological sample storage system comprising multiple storage compartments, at least one operating compartment, and a mobile support mechanism, the mobile support mechanism being used to drive the storage compartments and / or the operating compartments to move within a passage area, each of the operating compartments being used to dock with the storage compartments and perform biological sample access operations, the method comprising: Get sample access instructions; The target storage compartment is determined from multiple storage compartments according to the sample access command, and the operation compartment that docks with the target storage compartment is determined. The docking mode and movement path are determined based on the status of the operating cabin, the target storage cabin, the passage unit, and the docking position. When the access unit corresponding to the movement path and the target docking position are in an available state, control the operation cabin or the target storage cabin to move to the target docking position and complete the docking; The control module is used to pick up, store, or extract biological samples from the target storage compartment, and to update the status information of the access unit and docking position.

[0007] By adopting the above technical solution, after obtaining the sample access command, the target storage compartment and the operating compartment that docks with it are determined. The docking mode and movement path are then determined based on the status of the operating compartment, target storage compartment, access unit, and docking position. When the corresponding access unit and target docking position are available, the operating compartment or target storage compartment is controlled to move and complete the docking, enabling the movement and docking processes to be executed according to the status of physical entities and space resources.

[0008] Furthermore, the storage chamber is a storage tank for cryogenic storage of biological samples; Determining the target storage compartment from multiple storage compartments according to the sample access command specifically includes: The target storage compartment is determined from among the plurality of storage compartments based on at least one of the sample identification code, internal storage level coordinates, and access task type of the target storage compartment corresponding to the sample access instruction.

[0009] By adopting the above technical solution, the target storage compartment is determined based on at least one of the sample identification code, internal storage level coordinates, and access task type, so that the sample access command can be associated with the corresponding cryogenic storage object, providing target information for subsequent determination of the operation compartment and execution of docking.

[0010] Furthermore, the operating cabin is a movable operating cabin, and the storage cabin is a movable storage cabin; After identifying the target storage compartment, identify the available operating compartments; Identify the coordinates corresponding to the idle operating bay, and plan at least one planning path based on the coordinates corresponding to the idle operating bay and the storage level coordinates of the target storage bay; With the objective constraint of ensuring the planned path is unobstructed and having the shortest possible path, the optimal planned path is selected. The operation cabin is determined based on the optimal planned path. The movable operation cabin is then controlled to move to the corresponding position of the target storage cabin according to the optimal planned path, and the movable operation cabin is docked with the target storage cabin to perform tube picking, storage, or extraction of biological samples from the target storage cabin.

[0011] By adopting the above technical solution, after determining the target storage compartment, a path is planned based on the coordinates of the idle operating compartment and the coordinates of the target storage compartment. The optimal planned path is determined by using the absence of obstacles and the shortest path as screening conditions, so that the mobile operating compartment can move to the position corresponding to the target storage compartment according to the optimal planned path and complete the docking.

[0012] Furthermore, it also includes an AGV robot mounted on the mobile carrier mechanism; After identifying that the movable operating cabin is docked with the target storage cabin, the AGV robot is controlled to move to the position where it docks with the operating cabin or the storage cabin, for transferring biological samples, sample tubes, sample boxes or sample carriers during the storage or extraction of biological samples.

[0013] By adopting the above technical solution, after the mobile operating cabin and the target storage cabin are docked, the AGV robot is controlled to move to the corresponding docking position, so that the AGV robot can perform the transfer of biological samples, sample tubes, sample boxes or sample carriers during the storage or extraction of biological samples.

[0014] Furthermore, the status information is recorded through a module status table, which records the status of the storage compartment, the operation compartment, the mobile carrier mechanism, and the space resources. The space resources status includes the status of the passage unit, the docking position, the waiting area, and the transfer area. Establishing the module status table specifically includes: The task status management module parses the sample access instruction into feature data including task type, target sample parameters, task priority, and allowed waiting time. The physical entity status vector and space resource status vector are obtained through the task status management module. The physical entity includes at least one of the storage compartment, the operation compartment and the mobile carrier mechanism. The space resource status vector corresponds to at least one of the passage unit, the docking position, the waiting area and the transfer area. The task status management module associates the discrete spatial topology of the biological sample storage system, the physical entity status vector, and the spatial resource status vector to construct the module status table. The storage compartment status includes coordinate position, internal environmental parameters, and docking interface physical status; the operation compartment status includes coordinate position, working mode identifier, and internal mechanism operation status; the mobile carrier status includes coordinate position, carrier status, and operating status; and the space resource status vector includes at least one of occupancy identifier, reservation identifier, and area remaining capacity value.

[0015] By adopting the above technical solution, the physical entity state vectors corresponding to the storage compartment, operation compartment and mobile carrier mechanism, as well as the spatial resource state vectors corresponding to the passage unit, docking position, waiting area and transfer area, are associated with the discrete spatial topology. This enables the module state table to record the physical entity state and spatial resource state participating in the movement and docking scheduling, providing state data for docking mode determination, movement path generation and resource reservation.

[0016] Furthermore, the discrete spatial topology, the physical entity state vector, and the spatial resource state vector are associated to construct the module state table, specifically including: The passage unit, the docking position, the waiting area and the transfer area are respectively identified as spatial resource nodes. Node identifiers are configured for each spatial resource node, and node topology records are established based on the passable connection relationships between each spatial resource node. Based on the coordinate positions of each physical entity and the coordinate range corresponding to each spatial resource node, determine the spatial resource node currently corresponding to each physical entity, and establish the association between the physical entity state vector and the corresponding node identifier; Each of the spatial resource state vectors is associated with its corresponding node identifier; Using the node identifier as the association field, the node topology record, the spatial resource state vector, and the physical entity state vector currently corresponding to the spatial resource node are written into the same node state record; The node status records corresponding to multiple spatial resource nodes are combined to form the module status table, and the module status table is updated in each control cycle according to the data output by the status detector.

[0017] By adopting the above technical solution, the node identifier of the spatial resource node is used as the association field. The node topology record, spatial resource status vector and the current corresponding physical entity status vector are written into the same node status record. Multiple node status records form a module status table, so that the spatial topology relationship, spatial resource status and physical entity status can be recorded and updated according to the spatial resource node.

[0018] Furthermore, the docking mode includes at least one of the following: the storage tank moving to the fixed operation cabin mode, the operation cabin moving to the fixed storage tank mode, and the anti-congestion mode of the physical entity entering the waiting area or the transfer area. Determining the docking mode specifically includes: When the movement attribute of the storage tank to be docked is movable and the movement attribute of the operation cabin to be docked is fixed, the dynamic docking decision module determines that the docking mode is the mode in which the storage tank moves to the fixed operation cabin. When the movement attribute of the storage tank to be docked is fixed and the movement attribute of the operating cabin to be docked is movable, the docking mode is determined to be the mode in which the operating cabin moves to the fixed storage tank. When the occupancy rate of the passage unit in the main channel exceeds a preset threshold, the anti-congestion mode is triggered, and physical entities without passage permissions are guided into the waiting area or the transfer area. The dynamic docking decision module filters out invalid docking modes based on the boundary constraint that the sum of the expected movement time and the expected operation time is less than or equal to the allowed waiting time. It also calculates a matching weight score by comprehensively considering the expected movement energy consumption value, the predicted idle cycle value of the operation module to be docked, and the sample state risk value, and outputs the docking mode with the highest matching weight score as the basis for planning and execution.

[0019] By adopting the above technical solution, the corresponding docking mode is determined based on the movement attributes of the storage tank and the operation cabin, and an anti-congestion mode is triggered when the occupancy rate of the main channel exceeds a preset threshold. Invalid docking modes are filtered out by boundary constraints corresponding to the allowed waiting time, and a matching weight score is determined based on the expected movement energy consumption value, the predicted idle cycle value, and the sample state risk value, thus determining the basis for planning execution from the candidate docking modes.

[0020] Furthermore, the determination of the expected mobile energy consumption value specifically includes: The dynamic docking decision module calculates the total path length of the movement path based on the physical center distance between each adjacent passage unit in the movement path; Based on the physical type of the storage tank or the operating cabin to be moved and the load-bearing status of the mobile carrier, the corresponding energy consumption coefficient per unit distance is determined from the preset energy consumption parameter table. The estimated travel energy consumption value is determined by multiplying the total path length by the energy consumption coefficient per unit distance.

[0021] By adopting the above technical solution, the total path length is determined based on the physical center distance between each adjacent passage unit in the movement path, and the unit distance energy consumption coefficient is determined based on the entity type of the entity to be moved and the bearing status of the moving carrier mechanism, so that the expected movement energy consumption value can be determined based on the total path length and the corresponding unit distance energy consumption coefficient.

[0022] Furthermore, the movement path and the target docking position belong to a candidate docking combination. The candidate docking combination also includes an expected time window and a target object. The target object includes a target storage tank and a candidate operating cabin. The expected time window includes an expected passage time window and an expected docking time window. Generating the candidate docking combinations specifically includes: The physical state data of the docking interface of the target storage tank is extracted and compared with the mechanical interface feature data of each candidate operating cabin. The target docking positions that are within a set threshold range in terms of spatial distance from the current coordinates of the target storage tank and the current coordinates of each candidate operating cabin are selected. Using the current coordinates of the corresponding physical entity as the starting coordinates and the target docking coordinates as the ending coordinates, a discrete sequence of access units is calculated using a graph theory pathfinding search algorithm to generate the movement path containing multiple access units. Based on the preset moving speed and the physical center distance between adjacent passage units, the time nodes for the corresponding physical entities to enter and exit each passage unit are calculated, and the expected passage time window is generated. Based on the expected arrival time at the endpoint coordinates and the expected operation duration, the expected docking time window occupying the target docking position is calculated.

[0023] By adopting the above technical solution, when generating candidate docking combinations, the interfaces between the target storage tank and the candidate operating compartment are compared for compatibility, and a movement path is generated based on the starting point coordinates and the target docking position coordinates. Based on the movement path, the expected travel time window and the expected docking time window are determined, enabling the candidate docking combination to record the target object, movement path, target docking position, and corresponding expected time window.

[0024] Furthermore, determining whether the movement path and target docking point are in an available state specifically includes: The joint resource reservation module performs access resource reservation for the mobile path and docking resource reservation for the target object and the target docking position. The joint resource reservation module compares the overlap between each of the estimated passage time windows and the corresponding reserved intervals of the passage units on the time axis. When there is no overlap among all the passage units of the movement path, the passage resource reservation is determined to be successful. The joint resource reservation module maps the expected docking time window onto the future timeline of the target storage tank, the candidate operating cabin, and the target docking position, and verifies the availability of the working status of the mechanical interfaces, sealing components, and internal mechanisms of the target storage tank, the candidate operating cabin, and the target docking position within the expected docking time window. When the mechanical interfaces, sealing components, and internal mechanisms are not occupied by concurrent services and there are no abnormal faults, the docking resource reservation is determined to be successful. The judgment results of the access resource reservation and the docking resource reservation are logically ANDed. When both the access resource reservation and docking resource reservation are deemed to be successful, a resource lock record is written and the candidate docking combination is marked as executable. When the access resource reservation or the docking resource reservation fails, an avoidance and diversion process is triggered.

[0025] By adopting the above technical solution, access resources are reserved for access units in the movement path, and docking resources are reserved for target objects and target docking positions. When both access resource reservations and docking resource reservations are successful, a resource locking record is written and the candidate docking combination is marked as executable. If either reservation fails, an avoidance and diversion process is triggered.

[0026] Furthermore, the avoidance and diversion process includes controlling the corresponding physical entity to enter the waiting area; Controlling the corresponding physical entity to enter the waiting area specifically includes: If the determination result of the passage resource reservation or the determination result of the docking resource reservation is not approved, the congestion diversion control module detects through the module status table that the target docking position is occupied but the main channel is unobstructed and there is free buffer space, and retrieves the remaining capacity value of the area in the space resource status. When it is confirmed that the remaining capacity value of the corresponding waiting area is greater than zero and the passage resource verification of the corresponding physical entity to the corresponding waiting area is passed, the instruction to move to the target docking position is intercepted, and the redirection coordinate parameters are issued to guide the current physical entity to enter and stay in the nearest waiting area.

[0027] By adopting the above technical solution, when the target docking position is occupied, the main channel is unobstructed and there is free buffer space, the corresponding physical entity is controlled to enter the waiting area based on the remaining capacity value of the waiting area and the verification result of the passage resources to the waiting area, so that the physical entity can stay in the corresponding waiting area when the target docking position is temporarily unavailable.

[0028] Furthermore, the avoidance and diversion process also includes controlling the corresponding physical entity to enter the transfer area; Controlling the corresponding physical entity to enter the transit area specifically includes: When the main channel is blocked or a space occupancy conflict is detected, the congestion diversion control module extracts the status parameters of each associated physical entity in the conflict link and calculates the avoidance weight. The calculation of the avoidance weight takes into account the task priority, the entity vacancy status and the actual path distance from the current physical location to the nearest transit area coordinates. The lower the priority of the associated physical entity, the more it is in an idle state and the closer it is to the transfer area, the higher the avoidance weight calculated. The congestion diversion control module locks the associated physical entity with the largest avoidance weight value as the avoidance object, issues a scheduling instruction to the avoidance object to enter the corresponding transfer area, and releases the passage unit of the main channel that is occupied.

[0029] By adopting the above technical solution, when the main channel is blocked or a space occupation conflict occurs, the avoidance weight of each associated physical entity is calculated based on the task priority, the entity's empty status, and the actual path distance to the transfer area. The associated physical entity with the largest avoidance weight is identified as the avoidance object, so that the avoidance object enters the transfer area and releases the corresponding main channel passage unit.

[0030] Furthermore, the avoidance and diversion process also includes the detection and resolution of interlocking waiting deadlocks. The interlocking waiting deadlock is a closed-loop waiting state in which multiple physical entities in a waiting state wait for the next passage unit that the corresponding physical entity intends to enter to be released by the associated physical entity occupying that passage unit. The detection and resolution of the interlocked waiting deadlock specifically includes: The congestion diversion control module uses each physical entity currently in a waiting state as a graph node, and the waiting relationship caused by another physical entity occupying the next passage unit that the corresponding physical entity is trying to enter as a directed edge, to construct a directed resource dependency graph based on the module's state table. The loop dependency topology of the directed resource dependency graph is detected to be closed. When a closed loop is detected, an interlocking waiting deadlock is determined to have occurred. Extract all graph nodes in the closed-loop link and evaluate the avoidance weight of each graph node. Issue a forced retreat and replanning instruction to the graph node with the largest avoidance weight value in the closed loop, forcing the graph node with the largest avoidance weight value to move to the transit area of ​​the non-main channel or to retreat along the original path, thereby breaking the closed-loop dependency relationship and releasing the interlock waiting deadlock.

[0031] By adopting the above technical solution, a directed resource dependency graph is constructed, which encapsulates the waiting physical entities and the waiting relationships between them caused by the occupancy of the next passage unit. The graph is then used to determine whether an interlocking waiting deadlock has occurred based on the closed loops within the graph. Upon detecting an interlocking waiting deadlock, the graph node to execute the forced backoff replanning instruction is determined based on the avoidance weights of each node in the closed loop, thereby breaking the closed-loop dependency relationship.

[0032] Furthermore, the process of selecting, storing, or retrieving biological samples from the target storage chamber via the operating cabin specifically includes: Upon reaching the target docking position, a multi-dimensional docking verification is performed, which includes at least position parameter verification, attitude parameter verification, sealing status verification, and communication status verification. The system acquires the position parameter compliance indicator, attitude parameter compliance indicator, sealing status compliance indicator, and communication status compliance indicator, and fuses them to generate a docking verification pass indicator to confirm that the multi-dimensional docking verification has passed. After the calculation result of the docking verification pass mark is passed, the internal mechanism within the target object is driven to perform physical sample access operation and verify the sample identification code; During operation, the temperature sensor values ​​inside the operating compartment and storage tank, as well as the real-time feedback current value of the drive motor, are monitored in real time. When the temperature sensor value jumps beyond the cold chain temperature control threshold, or the real-time feedback current value of the drive motor increases sharply beyond the rated torque current threshold, the emergency stop action of the internal mechanism is triggered.

[0033] By adopting the above technical solution, the position parameters, attitude parameters, sealing status, and communication status are verified before the physical sample storage and retrieval operation, and a docking verification pass mark is generated based on the various compliance marks. After the docking verification is passed, the physical sample storage and retrieval operation is performed, and the temperature sensor value and the real-time feedback current value of the drive motor are detected during the operation. When the corresponding value exceeds the set threshold, the emergency stop action of the internal mechanism is triggered.

[0034] A second aspect of this invention provides a modular storage and retrieval system for biological samples, employing the following technical solution: A modular access system for biological samples, and a modular access method for the aforementioned biological sample storage system, comprising at least one operating compartment, multiple storage compartments, a mobile carrying mechanism, a passage area, a docking position, a waiting area, a transfer area, a status detector, and a scheduling controller. The storage chamber includes a storage tank for cryogenic storage of biological samples. The operating chamber can dock with each of the storage chambers and perform tube picking, storage or extraction of biological samples in the docked storage chambers. The mobile support mechanism is used to carry the storage compartment or the operating compartment for spatial displacement; The status detector is used to collect status information of the storage compartment, the operating compartment, the mobile carrier mechanism, and space resources; The scheduling controller includes a task status management module, a dynamic docking decision module, a joint resource reservation module, a congestion diversion control module, and an execution feedback update module. The scheduling controller is used to determine the docking mode and movement path based on the status information. When the passage unit and target docking position corresponding to the movement path are in an available state, the controller controls the operation cabin or the storage cabin to move to the target docking position and perform physical sample storage and retrieval operations. When the passage unit or target docking position corresponding to the movement path is not in an available state, the controller triggers an avoidance diversion process.

[0035] By adopting the above technical solution, the status detector collects status information of the storage compartment, operating compartment, mobile carrier mechanism, and space resources, and the scheduling controller determines the docking mode and movement path based on the status information. When the passage unit and the target docking position are available, the operating compartment or storage compartment is controlled to move and perform physical sample storage and retrieval operations; when the passage unit or the target docking position is not available, an avoidance and diversion process is triggered.

[0036] Furthermore, the modular biological sample storage and retrieval system also includes an AGV robot; The AGV robot is used to dock with the operating cabin or the storage cabin and to transfer biological samples, sample tubes, sample boxes or sample carriers during the storage or extraction of biological samples. The status detector is also used to collect the status information of the AGV robot.

[0037] By adopting the above technical solution, the AGV robot docks with the operating cabin or storage cabin and performs the transfer of biological samples, sample tubes, sample boxes or sample carriers. The status detector collects the status information of the AGV robot, so that the status of the AGV robot can be recorded as part of the system status information.

[0038] Furthermore, the modules in the scheduling controller include: The task status management module is used to acquire sample access instructions, establish a module status table based on the collected physical entity information, and generate docking tasks based on the sample access instructions. The dynamic docking decision module is used to determine the docking mode by combining the module status table, and generate a candidate docking combination that includes a movement path, an expected time window, a target object, and a target docking position according to the docking mode. The joint resource reservation module is used to perform access resource reservation for the mobile path, perform docking resource reservation for the target object and the target docking position, and mark the candidate docking combination as executable when both the access resource reservation and the docking resource reservation are satisfied. The congestion diversion control module is used to trigger the avoidance diversion process when the access resource reservation or the docking resource reservation is not satisfied, and control the corresponding physical entity to perform the avoidance action and release the interlock waiting state. The execution feedback update module is used to control the target object to move to the target docking position when the candidate docking combination is marked as the executable state, and to perform physical sample storage and retrieval operations and update the module status table after reaching the target docking position and passing the multi-dimensional docking verification.

[0039] By adopting the above technical solutions, the task status management module is used to establish a module status table and generate docking tasks, the dynamic docking decision module is used to determine the docking mode and generate candidate docking combinations, the joint resource reservation module is used to execute passage resource reservation and docking resource reservation, the congestion diversion control module is used to execute avoidance diversion when resource reservation is not met, and the execution feedback update module is used to control the movement of target objects, execute physical sample storage and retrieval operations, and update the module status table.

[0040] This invention provides a modular access method and system for biological sample storage. It offers the following advantages: 1. This invention determines the target storage compartment from multiple storage compartments based on sample access instructions, and determines the operation compartment that docks with the target storage compartment. A module status table is established through the task status management module, and the docking mode is determined in combination with the dynamic docking decision module. Then, a candidate docking combination containing the movement path and the expected time window is generated. Subsequently, the joint resource reservation module is used to simultaneously execute the reservation of access resources and the reservation of docking resources, so that the physical entity can complete the judgment and locking of the availability status of spatial access resources and target docking positions before moving. This reduces the interference of movement trajectory during the movement process and the concurrent occupation conflict of the target docking position, which is conducive to the continuous execution of sample access tasks.

[0041] 2. This invention triggers an avoidance and diversion process when the reservation of passage resources or docking resources is not met through the congestion diversion control module. It guides physical entities to enter the waiting area or transfer area to perform avoidance actions in combination with the spatial resource status. Furthermore, it constructs a directed resource dependency graph to detect the loop dependency topology relationship of the closed loop. When the loop is detected to be closed, a forced retreat and replanning instruction is issued based on the avoidance weight to break the closed loop dependency relationship and release the interlock waiting state, thereby releasing the occupied main channel to maintain the overall traffic status of the system.

[0042] 3. This invention confirms successful multi-dimensional docking verification by acquiring position parameter compliance indicators, attitude parameter compliance indicators, sealing status compliance indicators, and communication status compliance indicators after reaching the target docking position. Then, during the physical sample storage and retrieval operation of the internal mechanism, the temperature sensor value and the real-time feedback current value of the drive motor are detected in real time. When the corresponding parameters exceed the threshold, the internal mechanism is triggered to stop, which reduces the risk of equipment collision caused by mechanical misalignment and sample temperature control failure, and achieves protection of biological samples. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of a modular storage and retrieval system architecture for biological samples according to an embodiment of the present invention; Figure 2 This is a flowchart of a modular access method for a biological sample storage system according to an embodiment of the present invention; Figure 3 This is a flowchart illustrating how to obtain sample access instructions and establish a module status table according to an embodiment of the present invention; Figure 4 This is a flowchart illustrating the generation of docking tasks and determination of docking modes according to an embodiment of the present invention; Figure 5 This is a flowchart illustrating the generation of candidate docking combinations according to an embodiment of the present invention; Figure 6 This is a flowchart illustrating the execution of access resource reservation and connection resource reservation according to an embodiment of the present invention; Figure 7 This is a flowchart illustrating the process of determining target docking combinations and executing congestion-prevention motion control according to an embodiment of the present invention. Figure 8 This is a flowchart illustrating the execution of docking verification, sample access, and resource release according to an embodiment of the present invention; Figure 9 This is a comparison diagram of the power spectrum occupied by a passage unit according to an embodiment of the present invention; Figure 10 This is a comparison diagram of the power spectrum of the driving current of the mobile bearing mechanism in one embodiment of the present invention; Figure 11 This is a schematic diagram of a modular storage and retrieval system for biological samples according to an embodiment of the present invention. Detailed Implementation

[0044] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0045] See attached document Figure 1 The present invention provides a modular storage and retrieval system for biological samples, including a storage compartment, an operation compartment, a mobile carrying mechanism, an AGV robot, a passage area, a docking position, a waiting area, a transfer area, a status detector, and a scheduling controller.

[0046] The storage chamber is configured for cryogenic storage of biological samples. The structural components of the storage chamber include a storage tank, an internal sample carrier, and a docking interface structure. The storage tank, as the main cryogenic storage component of the chamber, maintains the necessary cryogenic environment for the biological samples. The internal sample carrier holds sample tubes, sample boxes, or cryopreservation racks. The docking interface structure establishes mechanical alignment, a sealed connection, or a sample transfer channel with the operating chamber. The storage chamber has an independent identification identifier and outputs data on its current location, internal temperature, pressure, remaining liquid nitrogen level, and the physical status of the docking interface.

[0047] In specific implementation, refer to Figure 11 The modular biological sample storage and retrieval system includes at least one operating compartment 2 and multiple storage compartments 1. The operating compartment 2 can dock with any target storage compartment 1 among the multiple storage compartments 1, and perform biological sample picking, storage, or retrieval operations on the docked target storage compartment after docking is completed. Each of the multiple storage compartments has an independent identification and storage location information. The scheduling controller determines the target storage compartment according to the sample storage and retrieval instructions and generates the corresponding docking task.

[0048] Operation chamber 2 is configured to perform operations such as tube picking, extraction, storage, retrieval, transfer, barcode scanning, and fluid replenishment of biological samples. Operation chamber 2 is internally equipped with mechanical execution components, including at least one of the following: a sample gripping mechanism, a tube picking mechanism, a barcode scanning mechanism, a transfer mechanism, a cap opening mechanism, and a cap closing mechanism. The operation chamber has an independent identification identifier and outputs data on its current location, the physical status of its interfaces, and the operational status of its internal mechanisms.

[0049] In one embodiment, the operating cabin is a fixed operating cabin, and the storage cabin is moved to the docking position corresponding to the operating cabin via a mobile carrier mechanism and then docks with the operating cabin. In another embodiment, the operating cabin is a movable operating cabin, which is mounted on the mobile carrier mechanism or has its own walking mechanism. After receiving a movement control command from the scheduling controller, the movable operating cabin moves to the position corresponding to the target storage cabin and completes docking with the target storage cabin.

[0050] In one embodiment, the storage compartment is a fixed storage compartment, and the operating compartment or AGV robot moves to the docking position corresponding to the fixed storage compartment to perform sample storage and retrieval operations. In another embodiment, the storage compartment is a movable storage compartment, which is mounted on a mobile carrier mechanism or has its own walking mechanism. After receiving a movement control command from the scheduling controller, the movable storage compartment moves to the target docking position according to the set route and docks with the fixed or movable operating compartment.

[0051] The mobile carrier mechanism is configured to carry storage compartments or operating compartments for spatial displacement. The mobile carrier mechanism is controlled to perform linear, rotational, or curvilinear displacement to transport the carried physical entity to a specified spatial coordinate position. The mobile carrier mechanism can be a track-mounted mobile platform, a lifting and transfer platform, an AGV robot, or other actuators capable of moving storage compartments or operating compartments.

[0052] AGV robots are configured to move within a traversable area and perform sample or physical transport. AGV robots can dock with operating or storage compartments for transferring biological samples, sample tubes, sample boxes, or sample carriers during biological sample storage or retrieval. AGV robots can also serve as a type of mobile carrier, used to move operating or storage compartments to a target docking position. AGV robots have independent identification and output data on their current position, load status, docking status, battery status, and movement status.

[0053] The passage area is configured as a physical space for the movement of mobile carriers. Logically, the passage area is divided into multiple gridded passage units. Each passage unit has independent coordinate range attributes, occupancy status attributes, and passable direction attributes.

[0054] The docking position is configured as a fixed spatial physical node. It provides the mechanical alignment structure and sealed connection interface between the storage tank and the operating compartment. The docking position has occupancy status and estimated release time attributes.

[0055] The waiting area is configured as a temporary parking physical space. It is used to receive and park storage tanks or operating bays that have entered the service sequence but have not yet obtained further movement permissions. The waiting area has remaining capacity and occupancy status attributes.

[0056] The transfer area is configured as a conflict-avoidance physical space. It is used to receive and temporarily store storage tanks or operating compartments in a conflict-avoidance state when there is an occupancy conflict in the physical space. The transfer area has remaining capacity and entrance / exit direction attributes.

[0057] Status detectors are deployed in the passage area, docking position, and each mobile node. The status detectors are configured to collect and output real-time location and status attribute data of storage tanks, operating cabins, mobile carrier mechanisms, and various space resources.

[0058] The dispatch controller communicates with the status detector, mobile carrier, storage tank, and operations cabin. Internally, the dispatch controller contains multiple logical execution units, including a task status management module, a dynamic docking decision-making module, a joint resource reservation module, a congestion diversion control module, and an execution feedback update module.

[0059] The task status management module is configured to receive sample access commands from external input. Based on these commands, the module parses and generates structured docking task data. Furthermore, it constructs a global physical state matrix based on data returned by the status detector, which synchronously records the real-time attributes of all hardware entities.

[0060] The dynamic docking decision module communicates with the task status management module. The dynamic docking decision module is configured to receive docking task data output by the task status management module. Based on the docking task data and the global physical state matrix data, the dynamic docking decision module determines the current docking action mode. Based on the determined docking action mode, the dynamic docking decision module generates candidate docking combination data containing the target object and its movement path.

[0061] The joint resource reservation module communicates with the dynamic docking decision module. The joint resource reservation module is configured to receive candidate docking combination data output by the dynamic docking decision module. The joint resource reservation module performs time-dimensional availability calculations on the access units included in the candidate docking combination data. Simultaneously, the joint resource reservation module performs time-dimensional status calculations on the target operating cabin, target docking position, and related mechanisms, and outputs a comprehensive resource reservation determination result.

[0062] The congestion diversion control module is communicatively connected to the joint resource reservation module. The congestion diversion control module is configured to trigger execution when the joint resource reservation module outputs a negative decision or detects a space occupancy conflict. The congestion diversion control module calculates the avoidance weights of moving objects based on priority evaluation parameters. Based on the avoidance weight calculation results, the congestion diversion control module generates space allocation instructions for the corresponding moving objects to enter the waiting area or transfer area.

[0063] The execution feedback update module communicates with both the joint resource reservation module and the congestion diversion control module. The execution feedback update module is configured to extract the final target docking combination data when the joint resource reservation module outputs a positive result. Based on the target object, movement path, target docking position, and estimated time window in the target docking combination data, the execution feedback update module issues corresponding drive control commands to the mobile carrier mechanism, AGV robot, mobile operating cabin, or mobile storage cabin.

[0064] In embodiments where the operating cabin is a movable operating cabin, after receiving the sample storage and retrieval command, the execution feedback update module determines the location of the target storage cabin, the corresponding target docking position, and the movement path of the operating cabin to the target docking position according to the module status table. It then controls the operating cabin to move to the corresponding position of the target storage cabin, enabling the operating cabin to dock with the target storage cabin. After the operating cabin reaches the target docking position, the execution feedback update module triggers the docking verification procedure, and after the docking verification is successful, it controls the operating cabin to perform tube picking, storage, or retrieval operations on the target storage cabin.

[0065] In embodiments where the storage compartment is a movable storage compartment, after receiving the sample access command, the execution feedback update module controls one or more storage compartments to move to the target docking position according to the docking mode and candidate docking combinations output by the dynamic docking decision module, and docks the moved storage compartment with the operation compartment. When multiple storage compartments move concurrently, the execution feedback update module sequentially issues movement control commands based on the resource locking records written by the joint resource reservation module, so that each storage compartment enters the corresponding passage unit according to the corresponding expected passage time window.

[0066] In the implementation of AGV robot-assisted transfer, the execution feedback update module determines whether to invoke the AGV robot to perform the transfer task based on the sample retrieval instructions and the module status table. When the AGV robot is invoked, the execution feedback update module sends the AGV robot a movement path, target docking position, or transfer node coordinates, causing the AGV robot to move and dock with the operating cabin or storage cabin to transfer biological samples, sample tubes, sample boxes, or sample carriers. After the AGV robot completes the transfer, the execution feedback update module updates the AGV robot's load status, docking status, and current position data.

[0067] After the physical entity arrives at the target docking position, the execution feedback update module performs a physical verification procedure. Upon successful verification, it controls the operation cabin to perform a sample storage and retrieval operation. After the sample storage and retrieval operation is completed, the execution feedback update module releases the passage resources and docking resources corresponding to the target docking assembly and updates the global physical state matrix data.

[0068] In the following method embodiments, the storage tank, as the cryogenic storage body of the storage compartment, participates in status acquisition, path planning, and docking control; without specifically distinguishing the structural hierarchy, the status detection, movement control, and docking control of the storage tank can be understood as the status detection, movement control, and docking control of the storage compartment.

[0069] See attached document Figure 2 This invention provides a modular access method for a biological sample storage system, comprising the following steps: S1. Obtain sample access instructions through the task status management module, and establish a module status table based on the physical entity information collected by the status detector. The module status table records the status of the storage tank, the operation cabin, the mobile bearing mechanism, the passage unit, the docking position, and the waiting area or transfer area. S2. The task status management module generates docking tasks based on sample access instructions, and the dynamic docking decision module determines the docking mode based on the docking task and the module status table. The docking mode includes at least one of the following: storage tank moving to fixed operation cabin mode, operation cabin moving to fixed storage tank mode, and physical entity entering waiting area or transfer area anti-congestion mode. S3. The dynamic docking decision module generates candidate docking combinations based on the docking mode. The candidate docking combinations include the target storage tank, the candidate operation cabin, the target docking position, the movement path containing multiple passage units, the expected passage time window, and the expected docking time window. S4. Through the joint resource reservation module, perform passage resource reservation in the dimension of passage time for each passage unit in the movement path, and perform docking resource reservation in the dimension of status for the target storage tank, candidate operation cabin and target docking position. Under the condition that both types of reservations are satisfied, the candidate docking combination is marked as executable. Under the condition that either reservation is not satisfied, trigger the replanning process or the avoidance and diversion process. S5. If both types of reservations are satisfied, the target docking combination is determined by the execution feedback update module and the corresponding storage tank or operating cabin is controlled to move toward the target docking position. If the reservation is not satisfied or a space occupation conflict occurs, the corresponding storage tank or operating cabin is controlled to enter the waiting area or transfer area by the congestion diversion control module to perform avoidance actions and release the interlocking waiting state of the passage resources. S6. Perform a multi-dimensional docking verification at the target docking position, including position parameters, attitude parameters, and sealing status. After the verification is passed, control the operation cabin to perform physical sample storage and retrieval operations. After the sample storage and retrieval operations are completed, release the various passage and docking space resources corresponding to the target docking combination through the execution feedback update module, and synchronously update the module status table and business task queue.

[0070] To more clearly illustrate the technical details and implementation principles of the present invention, the specific logic control steps in the above overall process will be explained in detail below.

[0071] See attached document Figure 3 The task status management module, as the upper-level data access and global information mapping hub of the entire scheduling system, is responsible for completing the digital transformation of business requirements and the mathematical modeling of the global topology of the system before physical actions are triggered.

[0072] S101. The task status management module acquires externally input sample access instructions. The task status management module parses the sample access instructions into machine-readable data containing task type, target sample parameters, task priority, and allowed waiting time. Specifically, the task status management module extracts the text features of the instructions and establishes an access instruction feature vector. Access instruction feature vector The mathematical model is defined as follows: ; in, This is the feature vector of the access instruction; Number the task type; For target sample parameters; As a task priority weight; This is the maximum allowed waiting time.

[0073] Task type number The values ​​cover preset integer identifiers corresponding to inbound, outbound, transfer, and inventory counts; target sample parameters. Includes sample physical identifier and internal storage hierarchy coordinates; task priority weights. The value range is set to an integer from 1 to 10, with a larger value indicating a higher level of business urgency.

[0074] S102. The task status management module collects real-time physical status data of each hardware entity in the system based on status detectors. Status detectors are deployed in the passage area, docking positions, and each moving node, outputting the physical coordinates, environmental parameters, operating mode, and mechanical interface characteristics of each entity. The task status management module constructs corresponding status vectors according to hardware categories. The task status management module establishes the storage tank status vector. : ; in, This is the state vector of the storage tank; The coordinates of the storage tank; This refers to the internal temperature of the storage tank. This refers to the internal pressure value of the storage tank. This describes the physical state of the storage tank's docking interface.

[0075] The mission status management module establishes the operation cabin status vector. : ; in, The state vector of the control cabin; The coordinates of the control cabin; This indicates the current operating mode of the control cabin. This indicates the operational status of the internal mechanisms of the control cabin.

[0076] The task status management module establishes the state vector of the mobile carrier mechanism. : ; in, The state vector of the mobile carrier mechanism; This indicates the current coordinate position of the mobile support mechanism; The current carrying status of the mobile carrier mechanism; This indicates the current operating status of the mobile carrier.

[0077] The task status management module establishes spatial resource status vectors. To record the status of the passage unit, docking position, waiting area, or transfer area: ; in, This is a spatial resource state vector; For identifying space resource occupancy; This serves as a reservation identifier for spatial resources; This represents the remaining capacity value for the region.

[0078] For different types of spatial resource nodes, from , and Select the corresponding status parameters. For example, the passage unit and docking position should at least record the occupancy indicator and reservation indicator, and the waiting area and transfer area should at least record the occupancy indicator and the remaining capacity value of the area.

[0079] S103, the task status management module associates the discrete spatial topology, the real-time acquired physical entity status vectors, and the spatial resource status vectors to construct a module status table for global scheduling. .

[0080] Specifically, the task status management module identifies passage units, docking positions, waiting areas, and transfer areas as spatial resource nodes, and assigns a unique node identifier to each spatial resource node. Each spatial resource node corresponds to a node topology record, which includes the node identifier, resource type, coordinate range, and a set of adjacent nodes. The set of adjacent nodes records the node identifiers of other spatial resource nodes that can be directly accessed from the current spatial resource node. Multiple spatial resource nodes and their interconnected accessibility relationships collectively constitute a discrete spatial topology.

[0081] The mission status management module compares the coordinate positions of each storage compartment, operation compartment, and mobile carrier with the coordinate range of each space resource node. The space resource node whose coordinate position falls within the corresponding coordinate range is identified as the current space resource node of the corresponding physical entity, and the node identifier of the space resource node is recorded as the current node identifier corresponding to the state vector of the physical entity.

[0082] The task status management module further associates each spatial resource status vector with the node identifier of the corresponding spatial resource node, and uses the node identifier as the association field to write the node topology record, the corresponding spatial resource status vector, and the physical entity status vector corresponding to the current spatial resource node into the same node status record.

[0083] No. Node status records corresponding to each spatial resource node Represented as: ; in, For the first The node topology record corresponding to each spatial resource node; For the first The spatial resource status vector corresponding to each spatial resource node; For the current corresponding to the first A set of physical entity state vectors for each space resource node, wherein the set of physical entity state vectors includes at least one of storage compartment state vector, operation compartment state vector, and mobile carrier mechanism state vector.

[0084] Within the system The node status records corresponding to each spatial resource node together constitute the module status table. : ; in, This represents the total number of spatial resource nodes.

[0085] Module Status Table The data is synchronously refreshed in each control cycle according to the sampling frequency of the state detector. When the physical layout of the system remains unchanged, the topology records of each node remain unchanged. The task status management module updates the status vectors of each spatial resource, the status vectors of each physical entity, and the association between the physical entity status vectors and the node identifiers based on the data output by the state detector.

[0086] The dynamic docking decision module reads the module status table. The node topology records determine the passability relationship between adjacent spatial resource nodes, and the occupancy and reservation status of each spatial resource node are determined by reading the corresponding spatial resource status vector, thus providing a data foundation for determining docking mode, generating movement path and reserving access resources.

[0087] The data frame decoding and message format verification during the instruction parsing process, as well as the data synchronization acquisition and state matrix storage update mechanism of multi-source sensor networks, are all well-known technologies that are implemented by those skilled in the art using common protocol parsing libraries, distributed data caching structures, and timestamp alignment algorithms. Therefore, they will not be elaborated here.

[0088] See attached document Figure 4 After completing the upper-layer data access and global physical state matrix construction, the dynamic docking decision module triggers specific entity connection and scheduling planning preparatory steps, mapping discrete business instructions into device collaboration modes with execution conditions.

[0089] S201. The task status management module generates structured docking task data by associating access instruction feature vectors with the module status table matrix. The task status management module retrieves hardware attribute records from the module status table matrix, filters out available resource nodes with physical components capable of executing the target function, and encapsulates the parameters of these resource nodes with task requirements to generate tuple task objects.

[0090] Feature vector of the docking task output by the task status management module In mathematical terms, it is defined as: ; in, For the docking task feature vector; This is the feature vector of the access instruction; For the target storage tank identification code; A collection of candidate operating cabins; For the candidate docking position set; This is the estimated operation time; This represents the risk value of the sample state.

[0091] Candidate Operations Module Set Includes all alternative cabin parameters that meet operational requirements; sample status risk value. The sensitivity coefficient is calibrated by multiplying the ambient temperature tolerance by the sample's sensitivity coefficient to external temperature fluctuations. In practical applications, this sensitivity coefficient is pre-configured by a backend medical database based on the temperature-controlled attenuation characteristics of different biological samples such as cells, nucleic acids, and blood.

[0092] S202. The dynamic docking decision module receives the docking task feature vector and determines the docking mode based on the hardware mobility and current space load. The dynamic docking decision module reads the Boolean values ​​of the movement attributes of each entity in the target storage tank and the candidate operation cabin set in the module status table matrix, breaks through the physical connection binding logic of fixed equipment, and dynamically establishes a temporary cooperative correspondence.

[0093] When the target storage tank's movement attribute is movable and the target operating cabin's movement attribute is fixed, the dynamic docking decision module determines the docking mode for the corresponding sub-task to be the storage tank moving to the fixed operating cabin mode; when the target storage tank's movement attribute is fixed and the target operating cabin's movement attribute is movable, the module determines the docking mode for the corresponding sub-task to be the operating cabin moving to the fixed storage tank mode. For multi-device concurrent scenarios, the dynamic docking decision module divides time window sequences according to task priority, generating a topology coordination mode where multiple storage tanks sequentially enter the same target operating cabin.

[0094] The dynamic docking decision module monitors the spatial resource status vector in the module status table matrix in real time. When the occupancy rate of the main channel's passage units exceeds a preset threshold, it automatically triggers an anti-congestion mode. This preset threshold is set between 80% and 90%, specifically determined based on the physical ratio between the total channel width and the size of the moving entity. In anti-congestion mode, the dynamic docking decision module guides physical entities without current passage permissions into the waiting area or transfer area, replacing the instruction to remain stationary and wait in their original positions.

[0095] S203. During the process of determining the docking mode, the dynamic docking decision module performs decision weight calculation and boundary constraint condition determination. The dynamic docking decision module comprehensively calculates the motion energy consumption of hardware equipment and the time window occupancy span, filtering out invalid docking modes that cannot meet the timeliness requirements.

[0096] The dynamic docking decision module performs the first round of boundary judgment based on time constraints. The preset time boundary constraint formula is defined as follows: ; in, For estimated travel time; This is the estimated operation time; This is the maximum allowed waiting time.

[0097] Estimated travel time The calculation starts at the current coordinates and ends at the target docking position. If the inequality does not hold, the dynamic docking decision module determines that the docking mode is infeasible and removes it from the candidate list.

[0098] For each candidate docking mode that satisfies the boundary constraints, the dynamic docking decision module determines the expected movement energy consumption value based on the corresponding movement path.

[0099] Specifically, suppose the movement path includes sequentially adjacent... Each access unit has a dynamic docking decision module that calculates the total path length of the movement path based on the physical center distance between adjacent access units. : ; in, The total length of the movement path; The first in the movement path The passage unit and the first The physical center distance between each passage unit; The number of passage units contained in the movement path.

[0100] The dynamic docking decision module determines the corresponding energy consumption coefficient per unit distance from a preset energy consumption parameter table based on the physical type of the storage tank or operating cabin to be moved and the load-bearing status of the moving carrier. The preset energy consumption parameter table records at least the correspondence between entity type, load-bearing status, and energy consumption coefficient per unit distance.

[0101] The estimated mobile energy consumption value The calculation formula is: ; in, This represents the projected mobile energy consumption value. The total length of the movement path; The energy consumption coefficient per unit distance, corresponding to the type of entity to be moved and the load-bearing state of the mobile carrier.

[0102] The energy consumption coefficient per unit distance is obtained through calibration using historical operational data. For multiple historical movement tasks of the same entity type and carrying state, historical movement energy consumption and historical movement distance are acquired respectively, and the corresponding energy consumption coefficient per unit distance is determined based on the ratio of the total historical movement energy consumption to the total historical movement distance. The historical movement energy consumption is determined based on the change in power consumption of the mobile carrying mechanism before and after performing the historical movement task, or based on the integral of the power supply voltage and drive current of the mobile carrying mechanism's drive motor over time.

[0103] The dynamic docking decision module performs matching weight scoring on the mode solutions that meet the boundary constraints. Matching weight score. The calculation formula is established as follows: ; in, To match weight scores; The first static adjustment weight coefficient; This represents the projected mobile energy consumption value. The second static adjustment weight coefficient; Predict idle cycle values ​​for the target operations bay; The third static adjustment weight coefficient; This represents the risk value of the sample state.

[0104] First, second, and third static adjustment weight coefficients , , All are statically adjusted weighting coefficients, with values ​​ranging from 0 to 1, and satisfying the following conditions: The specific values ​​are determined through analysis and statistics of historical equipment operation big data or expert experience. This comprehensive scoring mechanism essentially seeks the Pareto optimal solution among minimizing hardware mobility energy consumption, minimizing equipment idle time, and minimizing sample transfer exposure risk during the optimization process. The dynamic docking decision module outputs the docking mode with the highest matching weight score as the basis for subsequent planning and execution.

[0105] The data normalization process used in multi-objective decision evaluation is implemented by those skilled in the art using the range transformation method, which is a well-known technique and will not be elaborated here.

[0106] See attached document Figure 5 After establishing the dynamic collaboration and matching logic of the underlying hardware, the dynamic docking decision module further transforms the abstract corresponding cooperation relationship into a specific execution plan with detailed spatiotemporal displacement constraints, so as to ensure that the physical entity can arrive at the correct spatial node at the correct time.

[0107] S301. The dynamic docking decision module, based on the pre-determined docking mode, performs matching and optimization of physical entities and candidate resources in the global resource pool. The module extracts and compares the physical state data of the target storage tank's docking interface with the mechanical interface feature data of each candidate operating cabin, eliminating operating cabin entities with hardware connection interference or incompatible gas path communication protocols. Simultaneously, the module filters out target docking point entities whose spatial distance from the current coordinates of the target storage tank and the candidate operating cabins meets a set threshold range, generating a set of mutually compatible target operating cabins and target docking points. The set threshold range is defined as the maximum physical radius distance that the moving entity can travel under the current battery power.

[0108] S302. The dynamic docking decision module calls the discrete spatial topology in the module status table to perform mobile path planning based on the passage unit.

[0109] Specifically, the dynamic docking decision module uses each access unit as a graph node and determines the connection relationships between graph nodes based on the node topology records corresponding to each access unit. When the node identifiers corresponding to two access units are recorded in each other's neighboring node sets, graph edges are established between the corresponding two graph nodes, thereby constructing a topology graph for movement path planning. : ; in, This is the topology graph; This is the set of graph nodes corresponding to the passage unit; It is the set of graph edges between adjacent passage units.

[0110] The dynamic docking decision module compares the current coordinates of the moving entity with the coordinate range of each passage unit, determines the passage unit where the current coordinates are located as the starting passage unit, and determines the graph node corresponding to the starting passage unit as the starting graph node.

[0111] The dynamic docking decision module determines the access units directly connected to the target docking position based on the node topology record corresponding to the target docking position, and identifies the graph nodes corresponding to the access units as target graph nodes. When there are multiple access units directly connected to the target docking position, the graph nodes corresponding to each of the multiple access units are identified as candidate target graph nodes.

[0112] This embodiment uses The search algorithm is the graph theory pathfinding search algorithm. For adjacent i-th The graph node and the first For each graph node, the physical center distance between the corresponding two passage units is determined as the movement cost of the graph edge. .

[0113] During the path search process, the first The comprehensive search value corresponding to each graph node Represented as: ; in, To move from the starting graph node to the... The cumulative movement cost of each graph node; For from the first The estimated mobility cost from the first graph node to the target graph node, the estimated mobility cost being based on the first... The spatial distance between the physical center of each passage unit and the target docking position coordinates is determined.

[0114] The dynamic docking decision module adds the starting graph node to the set of nodes to be searched and sets the cumulative movement cost of the starting graph node to zero. During each search, the graph node with the lowest comprehensive search cost is selected from the set of nodes to be searched as the current graph node, and the node topology record corresponding to the current graph node is read to determine the adjacent graph nodes directly connected to the current graph node.

[0115] For the current graph node of the first The dynamic docking decision module calculates the distance to the th adjacent graph node via the current graph node. Candidate cumulative move cost of adjacent graph nodes : ; in, The cumulative movement cost to reach the current graph node; For the current graph node and the first The cost of movement between adjacent graph nodes.

[0116] When the Neighboring graph nodes have not yet been searched, or the cumulative move value of the candidates is... Less than the The original cumulative movement value of each adjacent graph node At that time, the cumulative moving value of the candidate will be... Updated to the number The cumulative movement cost of the nth adjacent graph nodes is calculated, and the current graph node is recorded as the nth node. The predecessor graph node of each adjacent graph node.

[0117] The dynamic docking decision module repeatedly selects the graph node with the lowest comprehensive search cost until the target graph node is selected. Then, starting from the target graph node, it backtracks back to the starting graph node according to the predecessor graph nodes recorded by each graph node, and reverses the sequence of graph nodes obtained by backtracking to obtain the discretized travel unit sequence.

[0118] When there are multiple candidate target graph nodes, the dynamic docking decision module calculates the cumulative movement cost from the starting graph node to each candidate target graph node, and determines the discretized passage unit sequence corresponding to the candidate target graph node with the smallest cumulative movement cost as the movement path.

[0119] Planned generated movement path Represented as: ; in, For the movement path; Identify the first passage unit in the movement path; Identify the second passage unit in the movement path; For the first in the movement path Individual access unit identifiers; This represents the total number of access units traversed by the movement path.

[0120] S303, the dynamic docking decision module, combines the mechanical kinematic parameters of the mobile carrier mechanism to deduce the time interval data of the physical entity occupying each spatial node. The dynamic docking decision module calculates the specific time node when the physical entity enters each passage unit based on the preset moving speed. The principle of deduce the time window lies in converting the displacement in physical space into the occupancy span on the time axis, thereby providing a basic data verification model for subsequently constructing a collision-free scheduling system with 3D spatial displacement and 1D time evolution.

[0121] For the movement path The first in The first access unit identifier, dynamically connected to the decision module, calculates its first... One expected passage time window The formula is defined as: ; in, For the first One estimated travel time window; For the first The estimated entry time for each passage unit; For the first The estimated departure time for each passage unit.

[0122] The derivation of the time points satisfies the following kinematic transformation relationship formula: ; in, For the first The estimated departure time of each passage unit; For the first The estimated entry time for each passage unit; The physical center distance between adjacent passage units; Preset movement speed.

[0123] Based on the estimated time of arrival at the destination coordinates and the estimated operation duration The dynamic docking decision module calculates the estimated docking time window for the physical entity to occupy the target docking position. The formula is defined as: ; in, For the expected docking time window; This is the estimated arrival time; This is the estimated operation time.

[0124] S304. The dynamic docking decision module packages and aggregates the determined physical entity parameters, the planned movement path sequence, and the calculated spatiotemporal occupancy time window data. The dynamic docking decision module outputs a candidate docking combination data package with multi-dimensional attributes. Candidate docking combination data packets The mathematical expression structure is established as follows: ; in, For candidate docking combination data packets; For the target storage tank identification code; For candidate operating cabin identification codes; The target docking identifier; For the movement path; This is a set of expected travel time windows; This is the expected docking time window.

[0125] Expected travel time window set Includes The first One expected passage time window The candidate docking combination data package outputs the full estimated parameters during the entity displacement process in a standardized structure, providing complete data input variables for the subsequent joint resource reservation module to perform deeper joint resource reservation and spatiotemporal availability calculations.

[0126] See attached document Figure 6 After completing the spatiotemporal simulation and parameter estimation, the joint resource reservation module enters the pre-verification phase to prevent spatial interference and deadlock risks that may occur during the actual movement of physical entities. Based on the spatiotemporal parameters calculated from the candidate docking combination data packets, the joint resource reservation module performs underlying spatial collision avoidance and hardware readiness status scheduling verification.

[0127] S401, the joint resource reservation module executes a spatiotemporal constraint-based access resource reservation algorithm based on the movement paths and expected access time window sets in the candidate docking combination data packets. The joint resource reservation module reads the underlying occupancy time axis data of each access unit in the module status table matrix, and compares the overlap between each planned expected access time window and the corresponding historical reservation interval that already exists on the time axis.

[0128] The joint resource reservation module calculates the independent occupancy state function of a single passage unit within the target time interval by determining the intersection state of time intervals. If the corresponding passage unit identifier has no overlap with any reservation records within the corresponding expected passage time window, the independent occupancy status function takes a value of 1, indicating that the spatiotemporal node is available; otherwise, if there is a time overlap, the value takes a value of 0, indicating that a spatiotemporal occupancy conflict has occurred.

[0129] After completing the state calculation for a single passage unit, the joint resource reservation module performs a spatial availability product verification of the entire path sequence. The joint resource reservation module then establishes the passage resource reservation determination result. Its mathematical model is established as follows: ; in, The result of the reservation of access resources; The multiplication operator indicates that the terms in the sequence are multiplied consecutively. This represents the total number of access units traversed along the movement path; For the sequence index of the passage unit; This is an independent occupancy state function; For the first Individual access unit identifiers; For the first One estimated travel time window.

[0130] If the result of the access resource reservation determination The calculation result is 1, indicating that the spatiotemporal resources of the entire path are continuously available, and the passage resource reservation for this path in the time dimension has been approved.

[0131] S402, the joint resource reservation module, while performing resource calculations, performs a multi-component status synchronization and reservation determination for the target storage tank, candidate operating compartment, and target docking position based on the expected docking time window. This logic introduces hardware readiness status verification to ensure that the physical entity can immediately execute process actions after arriving at the target spatial coordinates.

[0132] The joint resource reservation module retrieves the underlying hardware interface operation records corresponding to the target storage tank identifier, candidate operation compartment identifier, and target docking position identifier. The module maps the expected docking time window onto the future timeline of these three hardware entities, and verifies the operational availability of the entities' mechanical interfaces, sealing components, and internal access mechanisms within the expected docking time window.

[0133] The availability function is set to 1 only if the relevant component is not occupied by other concurrent services and does not report any hardware fault codes within the expected integration time window; otherwise, it is set to 0. The joint resource reservation module comprehensively calculates the integration resource reservation judgment result. Its formula is defined as: ; in, To determine the results of resource reservations; This is a function for interface status availability. A function for the availability of the sealing component; This is an internal organization availability function.

[0134] If the resource reservation determination result A value of 1 indicates that the physical states of multiple hardware components are synchronized and available in the time dimension, and the overall docking resource reservation has been approved.

[0135] S403. The joint resource reservation module logically integrates the verification calculation results of access resources and docking resources, and performs a joint access condition assessment. The joint resource reservation module establishes a joint access judgment value. The results of the access resource reservation determination and the connection resource reservation determination are then logically ANDed, and the formula is defined as follows: ; in, This is a joint admission determination value; The result of the reservation of access resources; The results of the appointment were used to determine the allocation of resources.

[0136] Joint access determination value When the value equals 1, the Joint Resource Reservation module marks the current candidate docking combination data packet as executable. The Joint Resource Reservation module simultaneously writes a formal resource lock record to the underlying data table, which serves as the basis for allowing the physical entity to enter the global movement execution sequence.

[0137] Joint access determination value When the value equals 0, it indicates that the candidate solution has a potential for spatiotemporal overlap or hardware occupancy conflict in any aspect of spatiotemporal travel or hardware docking. The joint resource reservation module directly rejects the candidate solution and feeds back the blocking status signal to the upper-level control logic, thereby triggering the scheduling system to execute the replanning process of the corresponding physical entity or forcibly trigger the avoidance and diversion process, eliminating the risk of physical interference and deadlock caused by the movement of underlying hardware.

[0138] The row-level locking protection and transaction commit mechanism during concurrent writes to the underlying data table are well-known technologies and can be implemented using common database transaction management tools, so they will not be elaborated here.

[0139] See attached document Figure 7 After completing the spatiotemporal collision verification and access assessment of the underlying logic, the execution feedback update module and the congestion diversion control module enter the control closed loop at the physical execution level. This stage is not only responsible for converting logical instructions into mechanical displacements, but also ensures the smooth flow of the global spatial transportation network through diversion and deadlock elimination mechanisms when facing resource competition and spatial conflicts caused by complex concurrent scenarios.

[0140] S501, when the candidate docking combination data packet is marked as executable, the execution feedback update module extracts the optimal target docking combination data from the executable sequence. The execution feedback update module parses the movement path sequence and time window requirements in the target docking combination data, and sends the corresponding physical entity vector displacement command to the underlying driver layer to start the physical movement process.

[0141] In the specific lower-level hardware implementation, the execution feedback update module converts the continuous movement path coordinates into motor control messages containing linear velocity, angular velocity and acceleration limit parameters, and sends them to the motion controller inside the mobile carrier mechanism through the bus network to drive the underlying servo motor to perform linear or rotary motion.

[0142] S502. When the congestion diversion control module detects through the module status table matrix that the target docking position is occupied but the main channel is open and there is free buffer space, it triggers an automatic waiting area allocation mechanism based on space detection. The congestion diversion control module continuously retrieves the remaining capacity value of the area from the space resource status vector in the module status table matrix.

[0143] When the remaining capacity of the corresponding waiting area is confirmed to be greater than 0 and the passage resource verification for the moving entity to the waiting area is passed, the congestion diversion control module intercepts the original instruction to move to the target docking position. The congestion diversion control module sends redirection coordinate parameters to the execution feedback update module, guiding the current moving object to enter and stay in the nearest available waiting area, thereby avoiding the moving object from stopping in place on the main channel and causing passage blockage of related entities.

[0144] S503. When the reservation in the joint resource reservation module is not fulfilled and a main channel blockage or space occupancy conflict is detected, the congestion diversion control module executes a main channel blockage risk assessment and transfer zone avoidance logic. The congestion diversion control module uses a comprehensive scoring function to calculate the concession priority weight of each related entity that caused the conflict, and forces low-priority or empty entities to leave the main channel.

[0145] The congestion diversion control module extracts state parameters for any moving entity in a conflicting link and calculates the avoidance weight. Avoid weight The mathematical model is defined as follows: ; in, To avoid weighting; This is the first avoidance adjustment coefficient; As a task priority weight; This is the second avoidance adjustment coefficient; This is a sign indicating that the entity is unoccupied. This is the third avoidance adjustment coefficient; This represents the actual path distance.

[0146] Physical empty sign The value is 1 when the entity is in an empty state without loading biological samples, and 0 when it is fully loaded; actual path distance The calculation starts at the current physical coordinates and ends at the coordinates of the nearest transit area; the first, second, and third avoidance adjustment coefficients. , , All values ​​are positive, and the specific weights are dynamically adjusted based on actual traffic flow stress test results. Entities with lower task priority, no cargo, and closer physical location to the transfer area will have a smaller negative impact on overall business efficiency if they make a retreat action, and their calculated avoidance weight will be higher.

[0147] Based on the calculation results, the congestion diversion control module locks the avoidance weight. The entity with the largest value is designated as the avoidance target. The congestion diversion control module forcibly issues a scheduling instruction to the avoidance target to enter the corresponding transfer area, thereby freeing up the main channel passage unit occupied by it and restoring other high-priority business flows that are parked or traveling on the main channel.

[0148] S504. The congestion diversion control module continuously runs an interlocking wait detection and forced release mechanism during the global scheduling process. In a multi-concurrent scheduling scenario, when multiple physical entities in a waiting state occupy their corresponding passage units and wait for other physical entities to release their intended next passage unit, forming a cyclical waiting relationship where no physical entity in the cyclical waiting relationship can move further, this state is defined as an interlocking waiting deadlock. The congestion diversion control module uses graph theory algorithms to construct a directed resource dependency graph based on the module's state table.

[0149] The congestion diversion control module uses each physical entity currently in a waiting state as a graph node, and the waiting relationship created when the next passage unit that an entity is trying to enter is occupied by another entity as a directed edge. The congestion diversion control module detects whether there are closed-loop dependency topologies in the directed resource dependency graph. If a closed loop is detected, the system is determined to have entered an interlocking waiting deadlock.

[0150] Upon detecting the interlocking waiting deadlock, the congestion diversion control module extracts all graph nodes in the closed-loop link and applies avoidance weights. The calculation formulas evaluate the concession priority of each node. The congestion diversion control module assigns weights to avoidance factors in the closed loop. The node with the largest value issues a forced backtracking and replanning instruction, forcing it to move to a transit area on a non-main road or to reverse along the original route, thereby breaking the closed-loop dependency relationship and releasing the interlocking waiting deadlock.

[0151] The closed-loop regulation and servo drive signal conversion mechanism of the underlying motion controller, and the depth-first search traversal algorithm for the loop structure in the directed graph, are well-known technologies that can be implemented by those skilled in the art using general industrial motion control cards combined with encoder feedback and standard graph theory function libraries, and will not be elaborated here.

[0152] See attached document Figure 8 Once a physical entity traverses a complex spatial network and finally arrives at its designated target spatial coordinates, the control logic of the scheduling system shifts from macroscopic traffic collision avoidance scheduling to microscopic precision process operation. This stage aims to ensure the physical safety of high-value biological samples during cross-entity transfer under extremely low temperature conditions and to complete the closed loop of software and hardware interaction data flow.

[0153] S601, After the target storage tank or operating cabin reaches the target docking position, the execution feedback update module pre-triggers a multi-dimensional docking verification procedure. The execution feedback update module reads the underlying data of various sensors deployed at the docking interface and performs hardwired checks covering four dimensions: mechanical limit, visual pose, air pressure sealing, and communication handshake.

[0154] The execution feedback update module obtains the position parameter compliance indicator by reading the status feedback of the mechanical micro switch, obtains the attitude parameter compliance indicator by analyzing the docking feature mark image collected by the industrial camera, obtains the sealing status compliance indicator by reading the air pressure sensor value inside the sealing flange, and obtains the communication status compliance indicator by sending industrial Ethernet heartbeat packets.

[0155] The execution feedback update module integrates multi-dimensional detection data and calculates and generates a comprehensive docking verification pass identifier. The docking verification has passed. The mathematical model is defined as follows: ; in, This indicates that the docking verification has passed. This indicates that the location parameters meet the standards. Indicates that the attitude parameters meet the standards; This indicates that the sealing condition meets the standards. This indicates that the communication status has met the standards.

[0156] The corresponding compliance flag is set to 1 only if the detection status of all four underlying dimensions meets the preset tolerance range; otherwise, it is set to 0. (If the docking verification passes, the flag is...) If the calculation result is 1, the feedback update module determines that the physical connection of the target docking assembly has been successfully established; if the calculation result is 0, the feedback update module blocks subsequent actions and throws a docking anomaly alarm code to the external system.

[0157] S602. After the docking verification is successful, the execution feedback update module officially issues sample storage and retrieval execution instructions to the target operating cabin. Upon receiving the instructions, the underlying control unit inside the operating cabin drives the multi-axis robotic arm and end effector gripper to perform preset precision operations such as opening the lid, grasping the sample carrier, and transferring its position.

[0158] During the physical displacement of the sample, the visual recognition and barcode scanning module configured inside the operating cabin simultaneously reads the barcode or QR code on the outer wall of the sample to verify whether the actual physical identification code of the sample is consistent with the instruction parameters issued by the business system.

[0159] During the execution of the process, the execution feedback update module continuously monitors for process anomalies. This module detects the temperature and pressure sensor values ​​inside the operating chamber and storage tank in real time, while simultaneously reading the real-time feedback current values ​​of the drive motors at each joint of the robotic arm. When the temperature sensor value jumps beyond the cold chain temperature control threshold, or the real-time feedback current value of the drive motor suddenly increases beyond the rated torque current threshold, the execution feedback update module determines that a physical interference or temperature control failure has occurred and triggers an emergency stop of the robotic arm to prevent physical damage or sample degradation.

[0160] The cold chain temperature control threshold is set based on specific sample storage specifications such as -80℃ or -196℃, combined with an allowable fluctuation deviation of ±2℃; the rated torque current threshold is taken as 1.5 to 2 times the calibrated current of the robotic arm motor under no-load operation. Abnormal surges in current are often direct electrical manifestations of physical collisions or jamming at the end of the robotic arm. By monitoring the underlying electrical signals and executing millisecond-level cutoff, hardware damage can be prevented.

[0161] S603. After the sample retrieval operation is successfully completed and the hardware mechanism is reset, the execution feedback update module controls the docking mechanism of the target docking position and related entities to perform an unlocking action, disconnecting the physical and gas path connections between the devices. The execution feedback update module then feeds back the task completion status signal to the task status management module.

[0162] Upon receiving a completion signal, the task status management module releases and logically resets spatiotemporal physical resources. The task status management module iterates through the module status table matrix. The spatial unit occupancy identifiers for the movement path access units, docking positions, and transfer nodes in the waiting area associated with this task. Space unit reservation sign Rewrite it as 0.

[0163] The task status management module clears the corresponding instruction execution stack records in the business task queue and updates the sample storage level coordinates in the underlying database to the latest actual physical location. At this point, the task status management module releases all access and docking space resources corresponding to the target docking combination, restores the standby and schedulable attributes of relevant hardware devices in the global resource pool, and achieves a closed-loop control process for a single business instruction from issuance to execution to resource recovery.

[0164] Specific application examples: To better understand the technical solution of this invention, the following description combines specific application scenarios with appendices. Figure 9 Appendix Figure 10 The present invention will be further described in detail below. This specific application embodiment is built on a modular sample storage and retrieval system for cryogenic storage of biological samples. The system operates in a sample storage environment that includes multiple storage tanks, a fixed operating chamber, a circular passage area, a waiting area, and a transfer area. It is responsible for obtaining sample storage and retrieval commands and executing a dynamic docking control closed loop between the storage tanks and the operating chamber.

[0165] In this embodiment, the sample library includes six storage tanks, one fixed operating cabin, one circular passageway, one docking station, two waiting areas, and one transfer area. Each storage tank is mounted on a mobile carrier and can move along the circular passageway. The passageway is divided into several passage units, each with occupancy status, reservation status, and passable direction attributes.

[0166] In a certain outbound task, the target sample is stored in storage tank No. 4. After the task status management module receives the sample storage and retrieval instruction, it parses the instruction into an outbound task and establishes a module status table. The status detector feeds back the following operating parameters: the current position of storage tank No. 4 is 6 passage units away from the target docking position, the physical center distance of each passage unit is 1.2m, the preset moving speed of the moving carrier mechanism is 0.4m / s, the estimated operation time is 45s, the maximum allowable waiting time is 90s, the predicted idle period of the target operation cabin is 30s, the sample status risk value is 0.15, the estimated moving energy consumption of storage tank No. 4 is 2.5, the first static adjustment weight coefficient is 0.4, the second static adjustment weight coefficient is 0.4, and the third static adjustment weight coefficient is 0.2.

[0167] During the docking mode determination phase, the dynamic docking decision module extracts the movement path data corresponding to storage tank No. 4 and calculates the estimated movement time. The dynamic docking decision module uses the estimated movement time. Expected operation time Maximum allowed waiting time Substituting the time boundary constraint formula into the specific implementation method, determine whether the task meets the time constraint: ; In this embodiment, the estimated passage time for a single passage unit is 3 seconds. Storage tank No. 4 needs to pass through 6 passage units, therefore the estimated movement time is... The estimated operation time is 18 seconds. The maximum allowed waiting time is 45 seconds. The time is 90 seconds. The dynamic docking decision module substitutes the numerical values ​​for calculation: ; The results show that the system obtained a task execution time of 63 seconds. Maximum allowed waiting time. The calculated value is 90s. Since the calculated value of 63s is less than 90s, the time boundary condition is met. The dynamic docking decision module determines that the docking mode of moving storage tank No. 4 to the fixed operation cabin is feasible, and the system enters the matching weight calculation stage.

[0168] During the matching weight calculation phase, the dynamic docking decision module combines the predicted mobile energy consumption, the predicted idle cycle value of the target operating cabin, and the sample state risk value to calculate the matching weight score. First static adjustment weight coefficient Expected mobile energy consumption Second static adjustment weight coefficient Predicted idle cycle value of the target operating cabin Third static adjustment weight coefficient Sample status risk value Substituting into the matching weight formula in the specific implementation: ; For the candidate scheme of moving storage tank No. 4 to the fixed operation compartment, the first static adjustment weight coefficient The estimated mobile energy consumption value is 0.4. The second static adjustment weighting coefficient is 2.5. The target operating cabin's predicted idle cycle value is 0.4. The third static adjustment weighting coefficient is 30. The risk value for the sample state is 0.2. The value is 0.15. The dynamic docking decision module substitutes the value for calculation: ; The calculation result is 12.13.

[0169] When the other candidate, a mobile operations cabin, is moved to storage tank No. 4, the estimated energy consumption during the move is... The target operating cabin's predicted idle cycle value is 4.0. The risk value for the sample state is 18. The value is 0.15, with all other parameters remaining consistent. The dynamic docking decision module substitutes the numerical value for calculation: ; The calculated result is 7.27.

[0170] The results show that the matching weight score for moving the storage tank to the fixed operation cabin mode... The matching weight score for the mobile operating cabin moving to the fixed storage tank mode is 12.13. The value is 7.27. Since 12.13 is greater than 7.27, the dynamic docking decision module determines that the mode of moving the storage tank to the fixed operation cabin is the preferred docking mode for this mission, and the system generates candidate docking combinations based on this docking mode.

[0171] During the joint resource reservation phase, the joint resource reservation module performs access resource reservations for the access units along the movement path of storage tank No. 4, and performs docking resource reservations for the target storage tank, candidate operating compartment, and target docking position. The movement path of storage tank No. 4 contains 6 access units. After querying the reservation records, the joint resource reservation module finds that the independent occupancy status function of each of the 6 access units is 1 within the corresponding expected passage time window, therefore the access resource reservation determination result is... The result is 1. Simultaneously, the target storage tank interface is usable, the sealing components are usable, and the internal mechanisms of the operating cabin are not occupied by other tasks; therefore, the docking resource reservation determination result is [positive / necessary]. The value is 1. The joint resource reservation module uses a joint admission judgment value. Traffic resource reservation determination results Result of resource reservation and matching Substituting the joint admission determination formula in the specific implementation: ; The joint resource reservation module will pass the resource reservation judgment results. 1. Result of resource reservation assessment Substituting 1 into the formula, the joint admission determination value is calculated. The result is 1. The results show that the candidate docking combination meets the joint admission conditions. The joint resource reservation module marks the candidate docking combination as executable, and the execution feedback update module controls storage tank No. 4 to move towards the target docking position.

[0172] When concurrent tasks occur, the system re-executes the joint resource reservation step. For example, in another set of tasks, a passage unit in the movement path of storage tank No. 4 has already been reserved by storage tank No. 2 within the corresponding expected passage time window, and the passage resource reservation determination result... The value is 0; even if the resource reservation determination result is... Still 1, joint admission determination value The result is also 0. The results show that the candidate docking combination does not meet the joint admission conditions. The joint resource reservation module outputs a negative judgment result, the system activates the congestion diversion control module, and triggers a replanning process or an avoidance diversion process.

[0173] During the congestion diversion phase, the congestion diversion control module calculates the avoidance weight based on task priority weight, entity vacancy status, and actual path distance. Currently, both storage tanks 2 and 4 are requesting to enter the same target docking position, but storage tank 2 is already occupying the main passage unit, and storage tank 4 needs to give way. The congestion diversion control module uses the avoidance weight. First avoidance adjustment coefficient Task priority weight Second avoidance adjustment coefficient Physical empty sign Third avoidance adjustment coefficient Actual path distance Substituting into the avoidance weight formula in the specific implementation: ; In this embodiment, the first avoidance adjustment coefficient The second avoidance adjustment coefficient is 0.5. The third avoidance adjustment coefficient is 0.4. The task priority weight for storage tank #2 is 0.03. Number 8, Physical Unloaded Marker =0, actual path distance The value is 5m. The congestion diversion control module uses this value for calculation: ; The calculation result is .

[0174] Task priority weight for storage tank #4 Number 3, Physical Unloaded Marker The actual path distance is 1. The value is 3m. The congestion diversion control module uses this value for calculation: ; The calculation result is 0.4767.

[0175] The results show that the avoidance weight of storage tank No. 4 The avoidance weight for storage tank No. 2 is 0.4767. for Because storage tank No. 4 has a higher avoidance weight, the congestion diversion control module determines that storage tank No. 4 is the object to be avoided. The system controls storage tank No. 4 to enter the transfer area and releases the main channel resources, so that storage tank No. 2 can continue to perform the high-priority sample outbound task.

[0176] To verify the stability of the response strategy, which includes joint resource reservation and congestion diversion control mechanisms, during system operation, the system compared and output spectrum data of the traditional first-come, first-served scheduling method and the scheduling method of this invention under the same experimental environment. The experimental scenario included 6 storage tanks, 1 fixed operating cabin, 1 circular passageway, 2 waiting areas, and 1 transfer area. The test tasks included sample entry, sample exit, and sample transfer tasks, with a total of 120 random tasks set.

[0177] See attached document Figure 9 , Figure 9 The horizontal axis represents frequency, and the vertical axis represents power spectral density. In the traditional first-come, first-served scheduling method shown in the figure, due to the lack of reservation for passage and docking resources, the power spectrum occupied by passage units exhibits strong fluctuations in the low-frequency range of 0Hz to 0.18Hz, especially forming several obvious low-frequency peaks near 0.01Hz to 0.04Hz. This state corresponds to a situation where the main channel occupancy fluctuates significantly periodically.

[0178] Figure 9 The scheduling method of this invention, by employing reservation of passage resources, reservation of docking resources, and flow control in waiting areas and transfer zones, results in a lower power spectrum for passage unit occupancy in most low-frequency ranges compared to the traditional first-come, first-served scheduling method, and a reduction in low-frequency peaks. This result verifies the ability of this invention to reduce periodic fluctuations in passage unit occupancy.

[0179] Based on the verification of the power spectrum occupied by the passage unit, in order to further verify the effectiveness of the present invention in terms of the operational stability of the mobile carrier mechanism, the system compared the power spectrum of the driving current of the mobile carrier mechanism under different scheduling methods.

[0180] See attached document Figure 10 , Figure 10 The horizontal axis represents frequency, and the vertical axis represents power spectral density. The traditional first-come, first-served scheduling method in the figure lacks joint resource reservation and congestion diversion control mechanisms. Its driving current power spectrum generally decreases with increasing frequency in the range of 0Hz to 15Hz, but exhibits a significant spectral peak in the range of 4Hz to 8Hz. Particularly, the power spectral density near 4.5Hz and 7.5Hz is higher than that of the scheduling method of this invention. This frequency band corresponds to numerous start-stop and dynamic adjustment actions during the operation of mobile carriers.

[0181] Figure 10 The scheduling method of this invention, by introducing dynamic docking decision-making, passage resource reservation, docking resource reservation, and current control in waiting areas and transfer zones, exhibits a smoother power spectrum curve for its drive current. Within the 3Hz to 9Hz range, the overall power spectral density corresponding to the scheduling method of this invention is lower than that of the traditional first-come, first-served scheduling method, and the local peaks are weaker. This result verifies the ability of this invention to reduce mid-frequency disturbances in the drive current.

Claims

1. A modular access method for a biological sample storage system, characterized in that, The biological sample storage system includes: multiple storage compartments, at least one operating compartment, and a mobile carrier mechanism. The mobile carrier mechanism is used to drive the storage compartments and / or the operating compartments to move within a passage area. Each operating compartment is used to dock with the storage compartments and perform biological sample storage and retrieval operations. The method includes the following steps: Get sample access instructions; The target storage compartment is determined from multiple storage compartments according to the sample access command, and the operation compartment that docks with the target storage compartment is determined. The docking mode and movement path are determined based on the status of the operating cabin, the target storage cabin, the passage unit, and the docking position. When the access unit corresponding to the movement path and the target docking position are in an available state, control the operation cabin or the target storage cabin to move to the target docking position and complete the docking; The control module is used to pick up, store, or extract biological samples from the target storage compartment, and to update the status information of the access unit and docking position.

2. The modular access method for a biological sample storage system according to claim 1, characterized in that, The storage chamber is a storage tank used for cryogenic storage of biological samples; Determining the target storage compartment from multiple storage compartments according to the sample access command specifically includes: The target storage compartment is determined from among the plurality of storage compartments based on at least one of the sample identification code, internal storage level coordinates, and access task type of the target storage compartment corresponding to the sample access instruction.

3. The modular access method for a biological sample storage system according to claim 2, characterized in that, The operating cabin is a movable operating cabin, and the storage cabin is a movable storage cabin; After identifying the target storage compartment, identify the available operating compartments; Identify the coordinates of the idle operation bay, and plan at least one path based on the coordinates of the idle operation bay and the storage level coordinates of the target storage bay; With the objective constraints of an unobstructed planned path and the shortest planned path, the optimal planned path is selected. The operation cabin is determined based on the optimal planned path. The movable operation cabin is controlled to move to the corresponding position of the target storage cabin according to the optimal planned path, and the movable operation cabin is docked with the target storage cabin to perform tube picking, storage or extraction of biological samples in the target storage cabin.

4. The modular access method for a biological sample storage system according to claim 3, characterized in that, It also includes AGV robots mounted on the mobile carrier mechanism; After identifying that the movable operating cabin is docked with the target storage cabin, the AGV robot is controlled to move to the position where it docks with the operating cabin or the storage cabin, for transferring biological samples, sample tubes, sample boxes or sample carriers during the storage or extraction of biological samples.

5. The modular access method for a biological sample storage system according to claim 2, characterized in that, The status information is recorded through a module status table, which records the status of the storage compartment, the operation compartment, the mobile carrier mechanism, and the space resources. The space resources status includes the status of the passage unit, the docking position, the waiting area, and the transfer area. Establishing the module status table specifically includes: The task status management module parses the sample access instruction into feature data including task type, target sample parameters, task priority, and allowed waiting time. The physical entity status vector and space resource status vector are obtained through the task status management module. The physical entity includes at least one of the storage compartment, the operation compartment and the mobile carrier mechanism. The space resource status vector corresponds to at least one of the passage unit, the docking position, the waiting area and the transfer area. The task status management module associates the discrete spatial topology of the biological sample storage system, the physical entity status vector, and the spatial resource status vector to construct the module status table. The storage compartment status includes coordinate position, internal environmental parameters, and docking interface physical status; the operation compartment status includes coordinate position, working mode identifier, and internal mechanism operation status; the mobile carrier status includes coordinate position, carrier status, and operating status; and the space resource status vector includes at least one of occupancy identifier, reservation identifier, and area remaining capacity value.

6. The modular access method for a biological sample storage system according to claim 5, characterized in that, The module state table is constructed by associating the discrete spatial topology, the physical entity state vector, and the spatial resource state vector, specifically including: The passage unit, the docking position, the waiting area and the transfer area are respectively identified as spatial resource nodes. Node identifiers are configured for each spatial resource node, and node topology records are established based on the passable connection relationships between each spatial resource node. Based on the coordinate positions of each physical entity and the coordinate range corresponding to each spatial resource node, determine the spatial resource node currently corresponding to each physical entity, and establish the association between the physical entity state vector and the corresponding node identifier; Each of the spatial resource state vectors is associated with its corresponding node identifier; Using the node identifier as the association field, the node topology record, the spatial resource state vector, and the physical entity state vector currently corresponding to the spatial resource node are written into the same node state record; The node status records corresponding to multiple spatial resource nodes are combined to form the module status table, and the module status table is updated in each control cycle according to the data output by the status detector.

7. The modular access method for a biological sample storage system according to claim 6, characterized in that, The docking modes include at least one of the following: the storage compartment moving to the fixed operation compartment mode, the operation compartment moving to the fixed storage tank mode, and the anti-congestion mode for physical entities entering the waiting area or the transfer area. Determining the docking mode specifically includes: When the movement attribute of the storage tank to be docked is movable and the movement attribute of the operation cabin to be docked is fixed, the dynamic docking decision module determines that the docking mode is the mode in which the storage tank moves to the fixed operation cabin. When the movement attribute of the storage tank to be docked is fixed and the movement attribute of the operating cabin to be docked is movable, the docking mode is determined to be the mode in which the operating cabin moves to the fixed storage tank. When the occupancy rate of the passage unit in the main channel exceeds a preset threshold, the anti-congestion mode is triggered, and physical entities without passage permissions are guided into the waiting area or the transfer area. The dynamic docking decision module filters out invalid docking modes based on the boundary constraint that the sum of the expected movement time and the expected operation time is less than or equal to the allowed waiting time. It also calculates a matching weight score by comprehensively considering the expected movement energy consumption value, the predicted idle cycle value of the operation module to be docked, and the sample state risk value, and outputs the docking mode with the highest matching weight score as the basis for planning and execution.

8. The modular access method for a biological sample storage system according to claim 7, characterized in that, The determination of the estimated mobile energy consumption value specifically includes: The dynamic docking decision module calculates the total path length of the movement path based on the physical center distance between each adjacent passage unit in the movement path; Based on the physical type of the storage tank or the operating cabin to be moved and the load-bearing status of the mobile carrier, the corresponding energy consumption coefficient per unit distance is determined from the preset energy consumption parameter table. The estimated travel energy consumption value is determined by multiplying the total path length by the energy consumption coefficient per unit distance.

9. A modular access method for a biological sample storage system according to claim 7, characterized in that, The movement path and the target docking position belong to a candidate docking combination. The candidate docking combination also includes an expected time window and a target object. The target object includes a target storage tank and a candidate operating cabin. The expected time window includes an expected passage time window and an expected docking time window. Generating the candidate docking combinations specifically includes: The physical state data of the docking interface of the target storage tank is extracted and compared with the mechanical interface feature data of each candidate operating cabin. The target docking positions that are within a set threshold range in terms of spatial distance from the current coordinates of the target storage tank and the current coordinates of each candidate operating cabin are selected. Using the current coordinates of the corresponding physical entity as the starting coordinates and the target docking coordinates as the ending coordinates, a discrete sequence of access units is calculated using a graph theory pathfinding search algorithm to generate the movement path containing multiple access units. Based on the preset moving speed and the physical center distance between adjacent passage units, the time nodes for the corresponding physical entities to enter and exit each passage unit are calculated, and the expected passage time window is generated. Based on the expected arrival time at the endpoint coordinates and the expected operation duration, the expected docking time window occupying the target docking position is calculated.

10. A modular access method for a biological sample storage system according to claim 9, characterized in that, Determining whether the movement path and target docking point are in an available state specifically includes: The joint resource reservation module performs access resource reservation for the mobile path and docking resource reservation for the target object and the target docking position. The joint resource reservation module compares the overlap between each of the estimated passage time windows and the corresponding reserved intervals of the passage units on the time axis. When there is no overlap among all the passage units of the movement path, the passage resource reservation is determined to be successful. The joint resource reservation module maps the expected docking time window onto the future timeline of the target storage tank, the candidate operating cabin, and the target docking position, and verifies the availability of the working status of the mechanical interfaces, sealing components, and internal mechanisms of the target storage tank, the candidate operating cabin, and the target docking position within the expected docking time window. When the mechanical interfaces, sealing components, and internal mechanisms are not occupied by concurrent services and there are no abnormal faults, the docking resource reservation is determined to be successful. The judgment results of the access resource reservation and the docking resource reservation are logically ANDed. When both the access resource reservation and docking resource reservation are deemed to be successful, a resource lock record is written and the candidate docking combination is marked as executable. When the access resource reservation or the docking resource reservation fails, an avoidance and diversion process is triggered.

11. A modular access method for a biological sample storage system according to claim 10, characterized in that, The avoidance and diversion process includes controlling the corresponding physical entity to enter the waiting area; Controlling the corresponding physical entity to enter the waiting area specifically includes: If the determination result of the passage resource reservation or the determination result of the docking resource reservation is not approved, the congestion diversion control module detects through the module status table that the target docking position is occupied but the main channel is unobstructed and there is free buffer space, and retrieves the remaining capacity value of the area in the space resource status. When it is confirmed that the remaining capacity value of the corresponding waiting area is greater than zero and the passage resource verification of the corresponding physical entity to the corresponding waiting area is passed, the instruction to move to the target docking position is intercepted, and the redirection coordinate parameters are issued to guide the current physical entity to enter and stay in the nearest waiting area.

12. The modular access method for a biological sample storage system according to claim 11, characterized in that, The avoidance and diversion process also includes controlling the corresponding physical entity to enter the transfer area; Controlling the corresponding physical entity to enter the transit area specifically includes: When the main channel is blocked or a space occupancy conflict is detected, the congestion diversion control module extracts the status parameters of each associated physical entity in the conflict link and calculates the avoidance weight. The calculation of the avoidance weight takes into account the task priority, the entity vacancy status and the actual path distance from the current physical location to the nearest transit area coordinates. The lower the priority of the associated physical entity, the more it is in an idle state and the closer it is to the transfer area, the higher the avoidance weight calculated. The congestion diversion control module locks the associated physical entity with the largest avoidance weight value as the avoidance object, issues a scheduling instruction to the avoidance object to enter the corresponding transfer area, and releases the passage unit of the main channel that is occupied.

13. A modular access method for a biological sample storage system according to claim 12, characterized in that, The avoidance and diversion process also includes the detection and resolution of interlocking waiting deadlocks. An interlocking waiting deadlock is a closed-loop waiting state in which multiple physical entities in a waiting state wait for the next passage unit that the corresponding physical entity intends to enter to be released by the associated physical entity occupying that passage unit. The detection and resolution of the interlocked waiting deadlock specifically includes: The congestion diversion control module uses each physical entity currently in a waiting state as a graph node, and the waiting relationship caused by another physical entity occupying the next passage unit that the corresponding physical entity is trying to enter as a directed edge, to construct a directed resource dependency graph based on the module's state table. The loop dependency topology of the directed resource dependency graph is detected to be closed. When a closed loop is detected, an interlocking waiting deadlock is determined to have occurred. Extract all graph nodes in the closed-loop link and evaluate the avoidance weight of each graph node. Issue a forced retreat and replanning instruction to the graph node with the largest avoidance weight value in the closed loop, forcing the graph node with the largest avoidance weight value to move to the transit area of ​​the non-main channel or to retreat along the original path, thereby breaking the closed-loop dependency relationship and releasing the interlock waiting deadlock.

14. A modular access method for a biological sample storage system according to claim 10, characterized in that, The specific procedures for selecting, storing, or retrieving biological samples from the target storage chamber via the operating cabin include: Upon reaching the target docking position, a multi-dimensional docking verification is performed, which includes at least position parameter verification, attitude parameter verification, sealing status verification, and communication status verification. The system acquires the position parameter compliance indicator, attitude parameter compliance indicator, sealing status compliance indicator, and communication status compliance indicator, and fuses them to generate a docking verification pass indicator to confirm that the multi-dimensional docking verification has passed. After the calculation result of the docking verification pass mark is passed, the internal mechanism within the target object is driven to perform physical sample access operation and verify the sample identification code; During operation, the temperature sensor values ​​inside the operating compartment and storage tank, as well as the real-time feedback current value of the drive motor, are monitored in real time. When the temperature sensor value jumps beyond the cold chain temperature control threshold, or the real-time feedback current value of the drive motor increases sharply beyond the rated torque current threshold, the emergency stop action of the internal mechanism is triggered.

15. A modular storage and retrieval system for biological samples, characterized in that, A modular access method for a biological sample storage system as described in any one of claims 1-14 includes at least one operating compartment, multiple storage compartments, a mobile carrying mechanism, a passage area, a docking position, a waiting area, a transfer area, a status detector, and a scheduling controller. The storage chamber includes a storage tank for cryogenic storage of biological samples. The operating chamber can dock with each of the storage chambers and perform tube picking, storage or extraction of biological samples in the docked storage chambers. The mobile support mechanism is used to carry the storage compartment or the operating compartment for spatial displacement; The status detector is used to collect status information of the storage compartment, the operating compartment, the mobile carrier mechanism, and space resources; The scheduling controller includes a task status management module, a dynamic docking decision module, a joint resource reservation module, a congestion diversion control module, and an execution feedback update module. The scheduling controller is used to determine the docking mode and movement path based on the status information. When the passage unit and target docking position corresponding to the movement path are in an available state, the controller controls the operation cabin or the storage cabin to move to the target docking position and perform physical sample storage and retrieval operations. When the passage unit or target docking position corresponding to the movement path is not in an available state, the controller triggers an avoidance diversion process.

16. A modular storage and retrieval system for biological samples according to claim 15, characterized in that, The modular storage and retrieval system for biological samples also includes AGV robots; The AGV robot is used to dock with the operating cabin or the storage cabin and to transfer biological samples, sample tubes, sample boxes or sample carriers during the storage or extraction of biological samples. The status detector is also used to collect the status information of the AGV robot.

17. A modular storage and retrieval system for biological samples according to claim 15, characterized in that, The modules in the scheduling controller include: The task status management module is used to acquire sample access instructions, establish a module status table based on the collected physical entity information, and generate docking tasks based on the sample access instructions. The dynamic docking decision module is used to determine the docking mode by combining the module status table, and generate a candidate docking combination that includes a movement path, an expected time window, a target object, and a target docking position according to the docking mode. The joint resource reservation module is used to perform access resource reservation for the mobile path, perform docking resource reservation for the target object and the target docking position, and mark the candidate docking combination as executable when both the access resource reservation and the docking resource reservation are satisfied. The congestion diversion control module is used to trigger the avoidance diversion process when the access resource reservation or the docking resource reservation is not satisfied, and control the corresponding physical entity to perform the avoidance action and release the interlock waiting state. The execution feedback update module is used to control the target object to move to the target docking position when the candidate docking combination is marked as the executable state, and to perform physical sample storage and retrieval operations and update the module status table after reaching the target docking position and passing the multi-dimensional docking verification.

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